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Mastercard Incorporated Common Stock (NYSE:MA)

Real-time price:$540.61

Founded in 1966 and headquartered in Purchase, NY, Mastercard Inc. is a leading global payment solutions company that provides an array of services in support of credit, debit, mobile, web-based and contactless payments, and other related electronic payment programs to financial institutions and other entities.The company's payment solutions include payment programs, marketing, product development, technology, processing, consulting and information services. It also provides worldwide transaction processing and other payment-related services, which include facilitating the authorization, clearing and settlement process of transactions, as well as processing cross-border and currency conversion transactions.In May 2001, the company was incorporated as a Delaware stock corporation. Mastercard has one reportable operating segment, Payment Solutions.The company manages and licenses payment card brands including MasterCard, Maestro and Cirrus....

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Here we provide our AYA proprietary alpha stock signals for all premium members on our AYA fintech network platform. Specifically, a high Fama-French multi-factor dynamic conditional alpha suggests that the stock is likely to consistently outperform the broader stock market benchmarks such as S&P 500, Dow Jones, Nasdaq, Russell 3000, MSCI USA, and MSCI World etc. Since March 2023, our proprietary alpha stock signals retain U.S. Patent and Trademark Office (USPTO) fintech patent protection, approval, and accreditation for 20 years. Our homepage and blog articles provide more details on this proprietary alpha stock market investment model with robust long-term historical backtest evidence.

Sharpe-Lintner-Black CAPM alpha (Premium Members Only) Fama-French (1993) 3-factor alpha (Premium Members Only) Fama-French-Carhart 4-factor alpha (Premium Members Only) Fama-French (2015) 5-factor alpha (Premium Members Only) Fama-French-Carhart 6-factor alpha (Premium Members Only) Dynamic conditional 6-factor alpha (Premium Members Only) Last update: Saturday 29 March 2025

Apple Boston

2025-03-25 04:03:08

Bullish

Quantitative fundamental analysis

Our AYA fun podcasts deep-dive into the current global trends, topics, and issues in macro finance, political economy, public policy, strategic management, innovation, entrepreneurship, and broader technological advancement in artificial intelligence (AI), virtual reality (VR), electric vehicles (EV), autonomous robotaxis (AR), graphics processing units (GPU), cloud services, high-speed broadband networks, the metaverse, and many more.


We would like to share our current AYA podcasts in reverse chronological order.

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In addition to our U.S. fintech patent publication, we provide all of our recent podcasts available on our AYA fintech network platform: https://ayafintech.network/blog/aya-fintech-network-platform-podcasts-on-global-trends-topics-and-issues-in-macro-finance/

These podcasts discuss the latest global trends, topics, and issues in macro finance, political economy, public policy, strategic management, innovation, entrepreneurship, and broader technological advancement in artificial intelligence (AI), virtual reality (VR), central bank digital currencies (CBDC), algorithmic asset management (Algo AM), recurrent and convolutional neural networks (RNN and CNN) for smart asset return prediction, electric vehicles (EV), autonomous robotaxis (AR), green power plants, cloud services, the metaverse, and many more.

Each fun podcast is about 10 minutes long (with AI podcast generation from Google NotebookLM).

In the broader context of stock market valuation, financial statement analysis, and smart-beta asset portfolio optimization, our AYA flagship podcasts, research surveys, research articles, literature reviews, analytic reports, ebooks, blog posts, and social media comments, discussions, and connections can help inform better stock market investment decisions for long-term investors, asset managers, hedge funds, investment banks, insurers, broker-dealers, and many other non-bank financial institutions and intermediaries (credit unions, building societies, and finance companies).

These better stock market investment decisions often lead to reasonably higher, more stable, more robust, and more profitable capital gains, cash dividends, and share repurchases in a cost-effective manner.

With U.S. fintech patent approval, accreditation, and protection for 20 years, our AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors worldwide.

We build, design, and delve into our new and non-obvious proprietary algorithmic system for smart asset return prediction and fintech network platform automation. Unlike our fintech rivals and competitors who chose to keep their proprietary algorithms in a black box, we open the black box by providing the free and complete disclosure of our U.S. fintech patent publication. In this rare unique fashion, we help stock market investors ferret out informative alpha stock signals in order to enrich their own stock market investment portfolios. With no need to crunch data over an extensive period of time, our freemium members pick and choose their own alpha stock signals for profitable investment opportunities in the U.S. stock market.

Smart investors can consult our proprietary alpha stock signals to ferret out rare opportunities for transient stock market undervaluation. Our analytic reports help many stock market investors better understand global macro trends in trade, finance, technology, and so forth. Most investors can combine our proprietary alpha stock signals with broader and deeper macro financial knowledge to win in the stock market.

Through our proprietary alpha stock signals and personal finance tools, we can help stock market investors achieve their near-term and longer-term financial goals. High-quality stock market investment decisions can help investors attain the near-term goals of buying a smartphone, a car, a house, good health care, and many more. Also, these high-quality stock market investment decisions can further help investors attain the longer-term goals of saving for travel, passive income, retirement, self-employment, and college education for children. Our AYA fintech network platform empowers stock market investors through better social integration, education, and technology.

Today, tech titans, billionaires, serial entrepreneurs, and venture capitalists continue to reshape and even disrupt global pharmaceutical investments for both better healthspan and longer lifespan.

Artificial intelligence continues to reshape the current global market for better biotech advances, medical innovations, and healthcare services.

The global market for GLP-1 anti-obesity weight-loss treatments now grows substantially to benefit more than 1 billion people worldwide by 2030.

Is higher stock market concentration good or bad for Corporate America?

As he moves into his second term, President Trump continues to blame China for the long prevalent U.S. trade deficits and several other social and economic deficiencies.

Geopolitical alignment often reshapes and reinforces asset market fragmentation in the broader context of financial deglobalization.

The global cloud infrastructure helps accelerate the next high-tech revolutions in electric vehicles (EV), virtual reality (VR) headsets, artificial intelligence (AI) online services, and the metaverse.

The new homeland industrial policy stance tilts toward greater global resilience across the major high-tech supply chains worldwide.

China poses new threats to the U.S. and its western allies.

How can generative AI tools and LLMs help enhance human productivity?


Our fun podcasts deep-dive into the current global trends, topics, and issues in support of better stock market investment decisions. - Blog - AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors.

AYA fintech network platform podcasts shine light on the current global trends, topics, and issues i...

https://ayafintech.network/blog/aya-fintech-network-platform-podcasts-on-global-trends-topics-and-issues-in-macro-finance/These

Monica McNeil

2025-03-23 03:41:22

Bullish

Quantitative fundamental analysis

Our latest podcast deep-dives into why, whether, and how today tech titans, billionaires, serial entrepreneurs, and venture capitalists continue to reshape and even disrupt global pharmaceutical investments for both better healthspan and longer lifespan.


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$MRK $AMGN $UNH $MRNA $T $VZ $TMUS $AEO $AMC $CVS $WMT $TGT $COST $V $MA $AXP 

$MSFT $GOOG $GOOGL $AMZN $AAPL $META $NVDA $TSLA $CSCO $ORCL $IBM $ASML $SNPS 

$NET $CRWD $PARA $NFLX $DIS $BILI $IQ $JD $PDD $BABA $TME $BIDU $BLK $STT $IONQ $C 




This fun podcast is about 10 minutes long (with smart AI podcast generation from Google NotebookLM). https://bit.ly/41KDNLp

We discuss, describe, and delve into the new medical sciences of longer longevity and their broader implications for stock market investments. In our modern human history since 1950, the average life expectancy worldwide has incrementally risen by 3 months to 5 months each year. The vast majority of men and women can now expect to live well beyond 70 years in many of the rich countries. This demographic mega trend reflects new medications, treatments, and therapies for many common diseases, disorders, symptoms, and other health conditions in association with old age. These diseases, disorders, and other health conditions include heart diseases, diabetes, Alzheimer’s and Parkinson’s diseases, sleep apnea and other disorders, peripheral arterial diseases, liver and kidney diseases, some sorts of cancers, non-alcoholic steato-hepatitis, knee osteoarthritis, and so forth. Many tech titans have invested heavily on high-efficacy medications, treatments, and therapies for these diseases, disorders, and other health conditions in support of both longer lifespan and substantial improvements in the health quality of life.

However, there are at least 2 major caveats. First, the increases in human lifespan are only incremental and so eventually confront the upper limit. Although the global number of centenarians continues to grow over time, this number seems to stretch its limit in due course. A recent Pew Research survey shows the new projection of more than 3.7 million centenarians worldwide by 2050, or almost 3 times as many centenarians per head of population as in 2015. Nonetheless, only one in 1,000 of these centenarians can live beyond 110 years, and almost no one can live beyond 120 years in modern human history. The maximum human age seems to rise at a much slower pace than the average human life expectancy does in recent decades. Second, the average healthspan, or the number of healthy vital years, may or may not keep pace with longer lifespan. For this reason, many tech titans have invested heavily in modern AI technological advancements in new medications, treatments, and therapies to support both longer lifespan and substantial health improvements in the quality of life for many men and women worldwide. Further, pharmaceutical titans have invested significantly in brand-new third-generation anti-obesity weight-loss medications primarily due to their increasingly higher efficacy and other health benefits. As many men and women now live longer lives, longer lifespan reflects a mix of clean, lean, and healthy lifestyle changes, choices, and decisions from good diet and regular exercise to smarter and better sleep, mood control, less or minimal stress, and deeper, greater, and broader social integration with family and friends. Today, new biomedical innovations, research endeavors, and capital investments help slow down and even reverse human age progression.

Several stock market magnates, moguls, tycoons, and key venture capitalists have been instrumental in the creation of lean startups in support of both longer lifespan and better healthspan. For instance, the serial venture capitalist and co-founder of PayPal and Facebook etc, Peter Thiel, invested a hard, high, and hefty fraction of his personal net worth in many medtech advances and lean startups in health care, precision medicine, and biotechnology. These ventures include Palantir, Women’s Healthcare Fund, Founders Fund, and Lindus Health. Specifically, Thiel invested more than $410 million in a strategic partnership between Palantir and the British National Health Service (NHS) to completely revamp the NHS patient data system. In addition, Thiel supported Recharge Capital’s $200 million Women’s Healthcare Fund to focus on high-efficacy alternative medications, treatments, and therapies for breast cancer, endometriosis, and polycystic ovary syndrome (PCOS). Through Founders Fund, Thiel invested many millions of dollars in 5 major lean startups for better biotech and medtech advances, inventions, and solutions. These major lean startups span Forward Health, Emerald, Cambrian, Counsyl, and Stemcentrx (now as part of AbbVie). In the meantime, these ventures focus on the new, non-obvious, and next-generation technical advances and medical innovations in biometric body scans, blood tests, stem cell therapies, and genetic modifications for better disease prevention. In recent years, Thiel contributed to the $6 million venture investment fund for the London company, Lindus Health, to dramatically speed up clinical trials for new medications, treatments, and therapies.

The Stanford co-founders of Google, Larry Page and Sergey Brin, invested heavily in better biotech, healthcare, and precision medicine too, primarily through 2 major Alphabet subsidiaries Verily and Calico. Today, Verily focuses on new medications, treatments, and therapies for dyspraxia, dyslexia, sleep apnea, insomnia, anxiety, depression, and other mental health and movement disorders. Furthermore, Verily seeks to eradicate all sorts of infectious diseases by killing insects and mosquitoes with the Zika, dengue fever, and other viruses and bacteria etc. In addition, Google DeepMind applies machine-learning algorithms and other AI-driven instruments to substantially sharpen the medical predictions of fatal diseases such as kidney and liver failures, stroke, cardiac arrest, sepsis, and pulmonary embolism.

Google DeepMind has built a new program, AlphaFold, from the previous success of AlphaGo in outperforming the top Go chess players worldwide. With AlphaFold, biomedical scientists help accelerate the major identification of new compounds in better clinical trials. Specifically, AlphaFold analyzes how some sequence of amino acids folds into the particular shape for some sort of protein. In essence, AlphaFold helps identify the more complex set of rules for some sequence of amino acids to fold biomedically into the same shape for some sort of protein in the human body. With tremendous success worldwide, AlphaFold accelerates and so revolutionizes the new wave of innovative drug discovery in support of smarter, faster, and better AI-driven medications, treatments, and therapies. In 2024, Google DeepMind CEO and Co-Founder Sir Demis Hassabis and DeepMind Director Dr John Jumper won the Nobel Prize in Chemistry for their recent design and development of AlphaFold for predicting the structures of different proteins from their amino acid sequences. Hassabis and Jumper shared this Nobel Prize with Dr David Baker who worked on computational protein design.

Many clever biomedical scientists had been trying hard to create computer models of the structural processes for folding amino acids into proteins in the human body for many decades. Just as AlphaGo trounced the best Go chess human players in recent years, AlphaFold substantially improved the best efforts of many biomedical scientists in past decades. Specifically, the shape of each protein reveals immense practical importance in terms of what the protein does alone, what other molecules can do to this protein, and the complex chemical interactions between each protein itself and its nearby and adjacent molecules and chains of amino acids. Almost all the basic structural processes of life depend on new complex chemical interactions among vital proteins, molecules, amino acid chains, and so forth. The vast majority of new drug discovery programs aim to find some sorts of molecules in support of desirable chemical interactions. Sometimes these molecules block specific protein actions, and sometimes these molecules encourage and stimulate specific protein actions. Before AlphaFold, more than 50 years of structural biology had produced several hundred thousand reliable protein structures through the traditional X-rays and nuclear-magnetic resonance techniques. AlphaFold and its closest rivals and competitors, ESMFold by Meta AI, OmegaFold by Helixon, and RoseTTAFold by Baker Lab, have provided more than 600 million sharp and accurate predictions of protein shapes for AI-driven medications, treatments, and therapies. Today, these deep machine-learning algorithms and Gen AI models, robots, and instruments etc continue to accelerate new technological advancements in structural biology.

Nowadays, Larry Page and Sergey Brin drive and steer Calico’s scientific research endeavors to build up new longitudinal patient databases. The next steps can help reveal the mainstream medical mechanisms for human age progression. In close collaboration with top institutions such as Harvard Medical School and Mayo Clinic, Calico delves into how biomedical doctors, scientists, and other health specialists can use new medications, treatments, and therapies to help slow down the natural course of human age progression. Today, the Food and Drug Administration (FDA) still does not recognize old age as a disease state and therefore as a proper target for treatment in America. Despite this current obstacle, Calico now navigates many health factors, forces, and biochemical interactions for medical intervention. These best efforts can combine to help each patient return to the new normal steady state. Even though these best efforts cannot reverse human age progression, these best efforts can perhaps help extend human healthspan dramatically in due course.

The founder and serial entrepreneur of Amazon, Jeff Bezos, invested in numerous companies in support of early cancer detection (Grail), immunotherapy (Juno), and anti-aging research (Unity) primarily through his venture fund, Bezos Expeditions. In recent years, the CEO and co-founder of OpenAI, Sam Altman, backed the $1 billion round for the AI-driven healthcare startup, Retro Biosciences, in support of new medications, treatments, and therapies for common diseases, disorders, and other health ailments. Through the Gates Foundation, Bill Gates invested heavily in new high-efficacy medications, vaccines, treatments, therapies, and healthcare services worldwide. Specifically, the Gates Foundation provides a $90 million prize for the new, non-obvious, next-generation pneumococcal conjugate vaccine (PCV). In accordance with the original prize proposal by Nobel Laureate Michael Kremer, the Gates Foundation strives to prevent pneumococcal infections by providing the new vaccine to each person at the $2.00 marginal cost. In recent years, the Gates Foundation continues to finance global biomedical research programs to eradicate HIV-AIDS, tuberculosis, polio, and malaria, especially in sub-Saharan Africa. With Quantum Biosciences, the Gates Foundation now aims to advance mRNA vaccine design, research, and mass production for efficient Covid prevention. Through the Dementia Discovery Fund, Bill Gates supports many lean-startup ventures on new medications and treatments for Alzheimer’s and Parkinson’s diseases. In addition, Gates continues to finance Foundation Medication in support of the new discovery of DNA sequences for cancer medications. Today, Bill Gates serves as one of the major investors in Ginkgo Bioworks. This biotech company helps tailor biochemical health products and medications to men and women with specific DNA sequences. We believe these resultant biomedical research developments can come to fruition in due course.

Beneath the forest canopy of pharmaceutical titans and startups with tech royalty, an undergrowth of lean startups continues to work on new medications, treatments, and therapies against some aspects of human age progression. The basic insight catches on of prolonging both lifespan and healthspan with some pills and potions, in addition to the more conventional baseline approach of diet, exercise, and high-quality sleep. New diagnostic tools, machines, and instruments provide the means for biomedical scientists to calculate the biological ages of both bodies and organs by comparison to actual calendar ages. In principle, this new capability allows both lifespan and healthspan studies to attain remarkable results in less than a lifetime. New gene modifications further help analyze vast amounts of gene sequence data. This new capability helps personalize new stem cells, medications, and treatments with a broader menu of therapeutic options.

Unlike many machines, bodies both make themselves and repair themselves. Why do human bodies age progressively with so many imperfections? Perhaps the high designer of life, natural evolution, focuses on better reproduction instead of longer lifespan. Life arises as a result of genes, development, behavior, and the broader environment. With accidents, predators, and diseases, the environment kills many creatures. Genes with health benefits that show up only over a longer lifespan than the broader environment allows in practice are not likely to perform particularly well in reproduction unless these genes provide some other health benefits. Genes that provide a fertile youth with successful reproduction are often onto a winner. There is some evidence that one variant of a specific gene in association with Alzheimer’s and Parkinson’s diseases provides reproductive advantages to young people.

From the evolutionary point of view of the genes, a person is a way to make further copies of the genes. In this wider view, a person’s life is a means to an end but not an end in itself. Keeping the human body’s repair mechanisms in tip-top conditions is worthwhile only if the human body gets more genes into the next generation. In this disposable soma approach, the person is a means to an end, and we abandon the life if it is no longer fit for the mainstream purpose of reproduction. This broader perspective helps explain why many diseases and other health conditions are often common in old age but relatively rare in early life. These diseases and other health conditions include Alzheimer’s and Parkinson’s diseases, diabetes, heart diseases, some sorts of cancers, retinal degeneration, osteoarthritis, and so forth.

Many genes have variants, also known as alleles, and all of these alleles work but may cause slightly different effects. With the genetic manipulation of lab organisms, some studies of the genes of human centenarians have identified alleles of specific genes that have been proven experimentally to prolong lifespan. These genes also result in significant improvements in the health quality of life. In recent years, these new studies can often help illuminate the natural course of human age progression. In recent years, these new studies suggest 12 hallmarks of human age progression. The dirty dozen spans genomic instability, telomere attrition, epigenetic alteration, metabolic decline for nutrient energy, mitochondrion dysfunction, proteostasis loss, stem cell exhaustion, chronic inflammation, autophagy decline, dysbiosis, cellular senescence, and intercellular breakdown. We delve into the mainstream scientific progress on each of these 12 hallmarks of human age progression. The devil is in the detail. Biomedicine can be quite complex. Sometimes a biomedical intervention may perform well in more than one field. At other times, there may be trade-offs in new medications, treatments, and therapies. We discuss, describe, and delve into the biomedical sciences of both longer lifespan and smarter and better healthspan, as well as their broader implications for stock market investments.

With U.S. fintech patent approval, accreditation, and protection for 20 years, our AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors worldwide.

We build, design, and delve into our new and non-obvious proprietary algorithmic system for smart asset return prediction and fintech network platform automation. Unlike our fintech rivals and competitors who chose to keep their proprietary algorithms in a black box, we open the black box by providing the free and complete disclosure of our U.S. fintech patent publication. In this rare unique fashion, we help stock market investors ferret out informative alpha stock signals in order to enrich their own stock market investment portfolios. With no need to crunch data over an extensive period of time, our freemium members pick and choose their own alpha stock signals for profitable investment opportunities in the U.S. stock market.

Smart investors can consult our proprietary alpha stock signals to ferret out rare opportunities for transient stock market undervaluation. Our analytic reports help many stock market investors better understand global macro trends in trade, finance, technology, and so forth. Most investors can combine our proprietary alpha stock signals with broader and deeper macrofinancial knowledge to win in the stock market.

Through our proprietary alpha stock signals and personal finance tools, we can help stock market investors achieve their near-term and longer-term financial goals. High-quality stock market investment decisions can help investors attain the near-term goals of buying a smartphone, a car, a house, good health care, and many more. Also, these high-quality stock market investment decisions can further help investors attain the longer-term goals of saving for travel, passive income, retirement, self-employment, and college education for children. Our AYA fintech network platform empowers stock market investors through better social integration, education, and technology.

Today, tech titans continue to reshape and even disrupt global pharmaceutical investments for both better healthspan and longer lifespan. - Blog - AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors.

This report delves into how today tech titans, billionaires, and venture capitalists continue to res...

https://ayafintech.network/blog/today-tech-titans-reshape-global-pharmaceutical-investments-for-both-better-healthspan-and-longer-lifespan/\nThis

James Campbell

2025-03-21 05:43:14

Bullish

Quantitative fundamental analysis

Our latest podcast deep-dives into the fundamental reasons why President Donald Trump continues to blame China for the long prevalent U.S. trade deficits and several other social and economic deficiencies as he moves into his second term.

$META $AAPL $MSFT $GOOG $GOOGL $AMZN $NVDA $TSLA $BRK.A $BRK.B $AMD $QCOM $AVGO 

$BABA $BIDU $TME $BILI $JD $IQ $PDD $NIO $RIVN $IONQ $QUBT $QBTS $RGTI $ASML $ORCL $C 

$V $MA $AXP $BAC $JPM $WFC $PNC $MS $GS $CSCO $IBM $SNPS $NET $CRWD $AMC $AEO $T 





In recent years, President Donald Trump blames China for the long prevalent high U.S. trade deficits against the middle kingdom. Now China seems to hollow out the American industrial homeland from smartphones and semiconductor microchips to electric vehicles (EV), drones, high-speed broadband networks, cloud services, and even large language models (LLM) for generative artificial intelligence. President Trump further blames China for causing the Covid pandemic crisis worldwide. Also, President Trump accuses China of attacking the U.S. and its western allies with fentanyl in the current opioid crisis. Given his U.S. domestic economic protectionism, President Trump seeks to double down on the hardline trade war with China. Specifically, President Trump seeks to impose hefty tariffs, export restrictions, and indefinite bans on many foreign investment categories against China. As President Trump moves into his second term, he continues to view China as a geopolitical adversary in a zero-sum game. In order to make America great again, many supporters seem to think only President Trump and his hardcore cabinet members can come up with hardline economic policies, sanctions, and regulations to tame the respective foes and rivals in Beijing. Political tensions between the U.S. and China continue to persist and even exacerbate in recent years. As a result, the bilateral relations between the U.S. and China seem to rest on flimsy foundations. Nowadays, geopolitical alignment often reshapes and reinforces asset market fragmentation in the wider context of financial deglobalization. Around the world, several western governments seek to incorporate new elements of global resilience into economic statecraft.

In China, President Xi Jinping and his cabinet members may not view the new Trump second term with fear and trepidation. These Chinese leaders, technocrats, and diplomats already learned much from the Trump first term, the Biden administration, and the populist return of Donald Trump to the White House in recent years. President Trump tends to apply economic protectionism across many industrial sectors and categories with fresh geopolitical tensions and frictions on the global stage. Early in his second term, President Trump declares retreats from the international Paris climate agreement, Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP), and even the World Health Organization (WHO). In effect, these complete withdrawals highlight the fact that the new Trump administration tends to undertake unilateral measures in support of greater economic protectionism in America. Despite the growing trade tensions, disputes, and frictions between Beijing and Washington, the Xi administration still seeks to navigate new confrontations in global trade, finance, and technology. Also, the new Trump administration may impose new tariffs and other economic sanctions on Canada, Mexico, and some other western allies. This hardline approach would encourage many countries, such as France, Germany, Japan, and Australia, to hedge their foreign investment bets outside North America. Specifically, these countries may choose to build better ties with Beijing, partly through its Belt-and-Road Initiative, in response to greater economic policy uncertainty in Washington. Although the U.S. and China may inadvertently stumble into the proverbial Thucydides trap, we believe the best likelihood of military threats between these dual superpowers remains quite low. Over the past decade, President Trump has not shown any deep and extreme ideological inclinations. It does not seem likely for the current competition between the U.S. and China to further escalate into a more destructive New Cold War. Although President Trump sees more realism in the current balance of power between the U.S. and China, he strives to stop-and-prevent wars in the hot and lofty pursuit of world peace. In recent years, President Trump has reiterated his intentions to coordinate truces, ceasefires, and peaceful resolutions of the relentless Russia-Ukraine war in Eastern Europe, as well as the current conflicts between Israel and Iran, Lebanon, Hamas, and the Palestinians in the Middle East. The new Trump administration seeks to better contain China, its recent rise on the global stage of economic growth, and endless interference over Taiwan along the Pacific first island chain.

Beijing believes Trump’s presidential election victory has little or minimal influence over the near-term trajectory of U.S. foreign policies toward China. In U.S. Congress, the bipartisan consensus perceives China as a unique series of new economic, technological, military, and diplomatic threats to the U.S. and its western allies, regardless of who wins the presidential bid to enter the White House. To the extent that the U.S. seeks to further contain-and-derisk from China, Russia, Iran, and North Korea, geopolitical alignment reshapes and reinforces asset market fragmentation in the broader context of financial deglobalization. Through U.S. political history, not everything remains the same from one administration to another. During his second term, President Trump is likely to maintain the hardline approach to foreign affairs with China not only from his own first term, but also from the Biden administration. President Trump seems to have learned from his first term that the current hardline approach to China would need to refresh with new and much younger cabinet members, such as Secretary of State Marco Rubio and Secretary of Defense Peter Hegseth, both of whom serve as China hawks with strong anti-communist beliefs. The devil is in the details. President Trump needs more nuance in the new bilateral relations between the U.S. and China. This nuance directs President Trump’s nominations for foreign policy and national security positions away from right-wing extremists (who served in their rightful capacity in the first Trump administration). In support of calm and stable asset markets, President Trump picks new cabinet members as strategic partners who can help advise on a wide range of global economic, technological, military, and diplomatic themes and issues during the recent rise of China, Russia, Iran, and North Korea on the global stage. Many of the new cabinet members continue to view China as the primary threat to the U.S. with substantial economic and technological advancements. For this reason, these cabinet members tend to favor new hardline and coercive measures for the new Trump administration to constrain China’s sphere of influence. Unlike the former Soviet Union in the Cold War era, China retains virtually no or few global ambitions to expand its communist propaganda. Nonetheless, the Trump administration needs to remain careful and cautious toward China’s increasingly aggressive policy stances toward Taiwan, Japan, Hong Kong, South Korea, and other strategic partners in East Asia.

In the wider geopolitical context, the same hardline approach may not work well because so much has changed significantly since the first Trump administration. When President Trump entered the White House for the first time in early-2017, many governments thought Trump would serve like a conventional American leader, an ideologically neutral businessman, and an economically rational decision-maker. Indeed, many major western allies thought Trump would commit to their common prosperity and regional security worldwide. President Trump visited China, Vietnam, South Korea, and the Philippines in November 2017. Despite U.S. opposition to Russia’s annexation of Crimea from Ukraine back in 2014, the Kremlin invited President Trump to Moscow for Russia’s annual celebration of the victory in World War II in late-2017. Subsequently, President Trump met with Russian President Vladimir Putin in a summit in Helsinki, Finland, as part of a weeklong trip to Europe in July 2018.

This time may be a bit different. Many leaders and governments are now proactive to protect their own countries from substantial economic policy uncertainty in Washington as President Trump moves into his second term. French President Emmanuel Macron invited President Trump to visit Paris as Macron would like to indicate that Europeans are their own decision-makers with respect to their own common prosperity, security, and climate risk management. Also, Japan and Germany reiterate their current concern that President Trump may require bigger fractions of their respective fiscal budgets to guarantee American military protection in their countries. In South Korea, the interim government worries that President Trump may take advantage of its current lack of authority over domestic affairs to the detriment of many special interest groups. In Taiwan, the extant government further fears that President Trump may tap into more than 5% of its annual economic output in return for U.S. military presence in response to China’s constant aggression.

In Eastern Europe, President Trump needs to grapple with the fact that Russia continues to attack Ukraine even though the U.S. and its western allies provide military support to Kiev. In the Middle East, Washington continues to provide military aid and geopolitical support for Israel’s brutal and bloody operations in Gaza, where many mainstream pundits believe there is an ongoing humanitarian crisis. Specifically, this crisis has further exposed the hypocrisy of U.S. claims to champion international law, world peace, and human rights. In his second term, President Trump has to better coordinate truces, ceasefires, and peaceful resolutions of these regional wars and conflicts in the lofty pursuit of world peace. Indeed, these peaceful resolutions can be a good legacy for President Trump to leave behind in his second term.

President Donald Trump blames China for the long prevalent U.S. trade deficits and several other social and economic deficiencies. - Blog - AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors.

President Donald Trump blames China for the long prevalent U.S. trade deficits and several other soc...

https://ayafintech.network/blog/president-trump-blames-china-for-the-long-prevalent-us-trade-deficits-and-other-social-and-economic-woes/

Monica McNeil

2025-03-19 02:05:07

Bullish

Quantitative fundamental analysis

Our latest podcast deep-dives into the AI-driven technological advances for new medications, treatments, therapies, and healthcare services worldwide. With AlphaFold, specifically, biomedical scientists accelerate the major identification of new compounds for better clinical trials. Today, the global pharmaceutical sector benefits substantially from Generative AI (Gen AI) with more than $100 billion AI-driven worldwide sales for new medications.


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This fun podcast is about 10 minutes long (with smart AI podcast generation from Google NotebookLM). https://bit.ly/4hBVimM

As medical doctors, surgeons, and physicians now integrate artificial intelligence (AI) into the mainstream technological advancements in better biotech, healthcare, and medicine, this integration helps reshape the competitive landscape worldwide. We can identify several mega trends for AI-driven better biotech advances, health-care services, and medical innovations. First, some recent AI-driven technological advancements help enhance diagnostic accuracy, improve patient health results, and personalize treatment plans. For instance, deep machine-learning algorithms help develop custom cancer therapies, target medications, and pharmacogenomic treatments in accordance with individual genetic and biochemical profiles. Second, the global pharmaceutical sector benefits substantially from Generative AI (Gen AI) with more than $100 billion AI-driven worldwide sales for new medications. These new medications help cure heart diseases, peripheral arterial diseases, diabetes, sleep apnea and other sleep disorders, some sorts of cancers, chronic kidney and liver diseases, non-alcoholic steato-hepatitis, knee osteoarthritis, and so forth. This broader macro shift highlights the increasingly vital dependence on Gen AI for drug discovery. With AlphaFold, biomedical scientists accelerate the major identification of new compounds for optimal clinical trials. Third, AI helps develop fresh personal treatment plans in response to the unique needs of individual patients with higher efficacy and tolerance. This development often helps better manage rare diseases, complex conditions, side-effects, and even contraindications. AI can analyze large amounts of data to recommend better target therapies. Fourth, AI technology helps integrate new diagnostic machines and devices, surgical robots, medications, and other medical innovations into the broader patient care system. These AI advances often support substantial improvements in the quality of life for the average patient. Further, new AI predictive analytics help identify potential health issues, symptoms, diseases, disorders, and complications. In effect, these new AI predictive analytics allow for proactive biomedical interventions in time. Finally, AI technology can help alleviate increasingly severe global healthcare challenges such as longer longevity, obesity, and urbanization. These new broader demographic shifts seem to present additional opportunities and challenges for many mainstream AI-driven healthcare systems worldwide.

We delve into the 4 major fundamental forms of AI integration in the global market for better biotech advances, medical innovations, and healthcare services. Doctors leverage AI-driven diagnostic devices, machines, and instruments to better inform medical decisions. This leverage is quite important today because almost 800,000 Americans suffer from bad medical decisions each year. Also, many patients seek sound professional medical assistance with their symptoms, side-effects, diseases, disorders, complications, and other health issues etc. Further, AI-driven smart data analytics help accelerate scientific research endeavors in support of smarter, faster, and better medical treatments. Moreover, new AI data analytics help promote more fierce competition in each of the major medical fields, domains, and specialties. In time, the resultant pervasive rise in global market competition likely leads to more cost-effective medications, treatments, and therapies etc. New AI technology helps hospitals, clinics, and health care centers modernize the diagnostic devices, robots, instruments, and even perhaps central command dashboards for the more efficient allocation of both public and private health care resources. Specifically, some new surveys estimate a common shortage of 10 million healthcare workers by 2030, or almost 15% of total healthcare workers worldwide today. Many governments seek to apply AI technological advances more broadly to help bridge the key shortfall of healthcare workers worldwide.

With U.S. fintech patent approval, accreditation, and protection for 20 years, our AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors worldwide.

We build, design, and delve into our new and non-obvious proprietary algorithmic system for smart asset return prediction and fintech network platform automation. Unlike our fintech rivals and competitors who chose to keep their proprietary algorithms in a black box, we open the black box by providing the free and complete disclosure of our U.S. fintech patent publication. In this rare unique fashion, we help stock market investors ferret out informative alpha stock signals in order to enrich their own stock market investment portfolios. With no need to crunch data over an extensive period of time, our freemium members pick and choose their own alpha stock signals for profitable investment opportunities in the U.S. stock market.

Smart investors can consult our proprietary alpha stock signals to ferret out rare opportunities for transient stock market undervaluation. Our analytic reports help many stock market investors better understand global macro trends in trade, finance, technology, and so forth. Most investors can combine our proprietary alpha stock signals with broader and deeper macrofinancial knowledge to win in the stock market.

Through our proprietary alpha stock signals and personal finance tools, we can help stock market investors achieve their near-term and longer-term financial goals. High-quality stock market investment decisions can help investors attain the near-term goals of buying a smartphone, a car, a house, good health care, and many more. Also, these high-quality stock market investment decisions can further help investors attain the longer-term goals of saving for travel, passive income, retirement, self-employment, and college education for children. Our AYA fintech network platform empowers stock market investors through better social integration, education, and technology.

In the current global market for better biotech advances, medical innovations, and healthcare services, the new integration of artificial intelligence (AI) reshapes the competitive landscape worldwide. - Blog - AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors.

AI-driven advances help reshape the competitive landscape for new medications, treatments, therapies...

https://ayafintech.network/blog/the-new-integration-of-artificial-intelligence-reshapes-the-competitive-landscape-for-the-global-market-for-better-medical-innovations-and-healthcare-services/

Rose Prince

2025-03-08 04:18:17

Bullish

Quantitative fundamental analysis

Our latest podcast deep-dives into whether the recent increasingly higher stock market concentration of the Magnificent 7 tech titans is good or bad for stock market investors worldwide.

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$XOM $CSX $OXY $PSX $WMT $TGT $COST $IONQ $QBTS $QUBT $RGTI $MELI $BABA $TME $IQ $BIDU 


The original blog article is available on our AYA fintech network platform.

This fun podcast is about 10 minutes long (with smart AI podcast generation from Google NotebookLM). https://bit.ly/3F1fpgN

In recent years, S&P 500 stock market returns exhibit spectacular concentration in the top tech titans Meta ($META), Apple ($AAPL), Microsoft ($MSFT), Google ($GOOG), Amazon ($AMZN), Nvidia ($NVDA), and Tesla ($TSLA), also known as MAMGANT or Magnificent 7. In the past years from January 2022 to December 2024, the Magnificent 7 delivered a hefty stock market return of 41% (versus only 17% for the other 493 stocks in the S&P 500 index). As of early-March 2025, the S&P 500 index shows substantial stock market concentration. Specifically, the top 10 stocks account for more than 35% of S&P 500 market capitalization. Historically, the top 10 stocks represented more than 20% of S&P 500 market capitalization over the past few decades. Further, the market capitalization of the largest stock relative to the top quartile stock now shows the highest level of stock market concentration since 1932. Although there has been no clear relationship between stock market concentration and near-term return performance, some economists and institutional investors express their concern about increasingly higher stock market concentration in NYSE and Nasdaq. Solid sales and profits in Corporate America can help substantially boost the S&P 500 index, perhaps from 6,000 points to 6,500 points, in the next few years. In this positive light, we can expect S&P 500 stocks, specifically the Magnificent 7 tech titans, to out-perform with a hefty 9% average return per annum in the next few years. Our fundamental analysis combines our proprietary alpha stock signals with ESG scores to lend credence to some of the tech titans in S&P 500 and more broadly Corporate America, especially the top tech titans with significant AI-driven technological advancements.

Stock market investors need not worry about higher market concentration in the longer term. American history shows that high stock market concentration usually leads to lower average returns ceteris paribus over longer investment horizons. When we add market concentration as a distinct variable to the long-run stock market return model, the model forecasts average S&P 500 annual returns of 3%-5% in each decade. Although this subpar return performance falls short of the historical average return of 11% for S&P 500, this drag on long-run returns arises from the greater volatility of tech titan stock returns. In recent times, the current higher stock market valuations of the Magnificent 7 tech titans now appear to embed greater growth expectations in relation to the recent AI-led stock market rally. From Apple ($AAPL), Amazon ($AMZN), and Microsoft ($MSFT) to Meta ($META) and Google ($GOOG), these tech titans rely upon the steady flows of high-end semiconductor microchips, graphical processing units (GPU), and several other quantum advances to make iterative continuous improvements for their Generative AI large language models (Gen AI LLM). As of mid-March 2025, we believe the current Gen AI LLM bellwethers include: Google Gemini, Meta Llama, Microsoft-OpenAI ChatGPT, Anthropic Claude, Perplexity, Alibaba Qwen, DeepSeek, Amazon Nova, Mistral, and Twitter xAI Grok.

After all, stock market concentration per se should not be a major concern for U.S. investors. This concentration often turns out to be a mainstream mechanical result of winner-takes-all sales and profits in AI-driven markets such as Internet search, text, voice, vision, video, and some smart combinations of these common forms of content generation. Specifically, stock market concentration need not heighten the 2 key types of stock market risks: fundamental risks and disequilibrium risks. The former relate to unlikely structural declines in fundamental sales and profits for S&P 500 tech titans, and the latter relate to short-term deviations from fair market values. Although some of the S&P 500 tech stocks seem to reach a new steady state of stock market over-valuation, we believe the vast majority of S&P 500 tech titans can benefit substantially from the broader AI stock market rally to explore new niche markets for both institutional investors and retail investors. In a positive light, stock market concentration need not be a major concern for U.S. investors in a fundamental view. However, we believe U.S. investors should refrain from placing big bets on the recent extreme winners, because their substantially higher market valuations may or may not justify their fundamental forces in the broader context of medium-term competitive threats. At least some of the recent AI-driven winners cannot sustain their greater growth expectations and longer-term competitive advantages. It takes time for U.S. investors to better assess whether each of these AI-driven winners passes the baseline proof of concept for the optimal product-market fit.

Over the past 60 years, no more than 3% of S&P 500 companies were able to sustain 20%+ sales growth for 10 consecutive years. We can back up this empirical result with Jim Collins’s seminal research on what makes great companies tick in his strategic management books: Built to Last, Good to Great, Great by Choice, and Beyond Entrepreneurship 2.0. Therefore, it is hard for the recent AI-driven tech winners to sustain their stock market outperformance in the long run. For at least some of these recent growth stocks, the probable mean reversion of returns can result in future under-performance, especially when their future fundamental sales and profits dwindle, dry up, and then fail to allow these recent winners to dominate in the respective AI-driven markets and adjacent niche segments.

The U.S. regulators should step in when the AI-driven tech titans use their market power to stave off both their rivals and competitors with higher product prices. To the extent that stock market concentration may stifle subsequent disruptive innovations, the Securities Exchange Commission (SEC), Federal Trade Commission (FTC), and Department of Justice (DoJ) etc should introduce new antitrust rules and regulations to make American tech titans face fierce competitive pressure with no clear dominance in any particular AI-driven market. The classic examples include: Apple App Store and Google Play in the mobile software market; Amazon e-commerce in the retail market for consumer goods; Nvidia GPUs, microchips, and several other hardware advances in the semiconductor industry; and Tesla in the global market for electric vehicles (EV) and autonomous robotaxis (AR).

This current high stock market concentration serves as one of the mainstream reasons for U.S. investors to further diversify exposures across asset classes, regions, and strategies. The historically optimal portfolio mix of 60% stocks and 40% bonds remains empirically valid, relevant, profitable, and reasonable in a fundamental view. In light of the still-solid sales and profits in the AI-driven sections of Corporate America, we believe the optimal portfolio combo of 60% stocks and 40% bonds continues to serve as the mainstream economic engine for the global asset management industry, specifically BlackRock, State Street, and Vanguard. U.S. investors need to revisit their optimal choices of AI-driven stocks with new fundamental competitive moats, substantial safety margins, positive network effects, cost economies, and information cascades.

With U.S. fintech patent approval, accreditation, and protection for 20 years, our AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors worldwide.

We build, design, and delve into our new and non-obvious proprietary algorithmic system for smart asset return prediction and fintech network platform automation. Unlike our fintech rivals and competitors who chose to keep their proprietary algorithms in a black box, we open the black box by providing the free and complete disclosure of our U.S. fintech patent publication. In this rare unique fashion, we help stock market investors ferret out informative alpha stock signals in order to enrich their own stock market investment portfolios. With no need to crunch data over an extensive period of time, our freemium members pick and choose their own alpha stock signals for profitable investment opportunities in the U.S. stock market.

Smart investors can consult our proprietary alpha stock signals to ferret out rare opportunities for transient stock market undervaluation. Our analytic reports help many stock market investors better understand global macro trends in trade, finance, technology, and so forth. Most investors can combine our proprietary alpha stock signals with broader and deeper macrofinancial knowledge to win in the stock market.

Through our proprietary alpha stock signals and personal finance tools, we can help stock market investors achieve their near-term and longer-term financial goals. High-quality stock market investment decisions can help investors attain the near-term goals of buying a smartphone, a car, a house, good health care, and many more. Also, these high-quality stock market investment decisions can further help investors attain the longer-term goals of saving for travel, passive income, retirement, self-employment, and college education for children. Our AYA fintech network platform empowers stock market investors through better social integration, education, and technology.

Is higher stock market concentration good or bad for Corporate America? - Blog - AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors.

This article delves into the pros and cons of increasingly higher stock market concentration in Amer...

https://ayafintech.network/blog/is-higher-stock-market-concentration-good-or-bad-for-corporate-america/

Charlene Vos

2025-03-01 02:36:37

Bearish

Qualitative technical analysis

Our latest podcast deep-dives into the recent empirical results in relation to stock ownership dispersion and corporate governance worldwide.

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The original blog article is available on our AYA fintech network platform. https://ayafintech.network/blog/corporate-ownership-governance-theory-and-practice/

This fun podcast is about 10 minutes long (with smart AI podcast generation from Google NotebookLM). https://bit.ly/4gpMkIK

The genesis of modern corporate governance and ownership studies traces back to the seminal work of Berle and Means (1932). The Berle-Means theory serves as the canonical qualitative foundation for the separation of corporate ownership and control. According to this thesis, corporate control over physical assets reacts to a centripetal force and tends to concentrate in the hands of only a few incumbents, whereas, corporate ownership is centrifugal, splits into small units, and passes from person to person. In the Berle-Means image of the modern corporation, executives and directors gain their income primarily from the effort that these incumbents put into business decisions, but not from the return on their stock investment in the enterprise. To the extent that corporate structures evolve in response to competitive pressures in the capital markets, the Berle-Means thesis predicts gradual convergence toward diffuse incumbent stock ownership as the most efficient form.

The Berle-Means theory has influenced the subsequent development of agency theory that highlights a potential conflict of interest between corporate incumbents and shareholders (Jensen and Meckling, 1986; Fama and Jensen, 1983). Subsequent studies question the empirical prevalence of the Berle-Means image of the modern corporation (e.g. Demsetz (1983), Demsetz and Lehn (1985), Shleifer and Vishny (1986), Morck, Shleifer, and Vishny (1988), and Holderness and Sheehan (1988)). The recent strand of law-and-finance literature suggests that the Berle-Means widely held corporation should prevail primarily in rich common-law countries with sound legal protection of minority shareholder rights (La Porta, Lopez-de-Silanes, Shleifer, and Vishny, 1997, 1998). Whether Berle-Means functional convergence toward greater stock ownership dispersion takes place in practice remains an empirical puzzle.

La Porta, Lopez-de-Silanes, and Shleifer (1999) offer an empirical refutation of the Berle-Means thesis. La Porta et al analyze data on ownership structures of large corporations in 27 rich economies to identify the ultimate controlling shareholders of these firms via pyramidal chains and cross-ownership structures. The main evidence suggests that except in economies with robust legal protection of investor rights, few of these firms are widely held with diffuse stock ownership in the Berle-Means sense. Alternatively, these firms are typically family firms or state enterprises. Equity control by financial institutions prevails only in some bank-centric financial systems such as Japan and Germany. The controlling shareholders tend to have power over firms in excess of their cash flow rights primarily through direct managerial influence and the use of pyramidal chains and cross-ownership structures. As a result, the main implication of this empirical work is that the theory of corporate finance for most countries should focus on the incentives of controlling shareholders to both benefit and expropriate minority shareholders.

Claessens, Djankov, and Lang (2000) examine the separation of ownership and control for 2,980 corpora-tions in East Asian countries. In all these countries, voting rights frequently exceed cash-flow rights via pyramidal chains and cross-ownership structures. This separation of ownership and control is most pro-nounced among family firms and small firms. A single shareholder retains the ultimate corporate control in more than 66% of these East Asian corporations. Nevertheless, the concentration of corporate control generally dwindles with the level of a country’s economic development.

Political connections matter a great deal to Chinese CEOs in several major corporate decisions, whereas, these connections have a negative effect on corporate performance in terms of post-IPO earnings growth, sales growth, or profit margin (Fan, Wong, and Zhang, 2007). In East Asia, some large corporations often find it necessary to bribe senior bureaucrats to derive state protection in the form of exclusive trade rights, commercial privileges, and preferential state-enterprise contracts (Claessens, Djankov, and Lang, 2000). From a corporate governance standpoint, the concentration of voting rights is crucial as this concentration allows owners to determine capital investment, M&A, R&D innovation, dividend or repurchase payout, capital structure, managerial personnel, and so forth. To the extent that voting rights often exceed cash-flow rights in many East Asian conglomerates, this control-ownership wedge exacerbates the potential conflict of interest between inside blockholders and minority shareholders. For instance, the Li Ka-Shing conglomerate, which is the largest business group in Hong Kong, comprises 25 companies that are among the largest in Hong Kong in terms of market capitalization. The Li Ka-Shing family holds and controls 35% stock ownership of Cheung Kong Hutchison Group, whose pyramidal chains result in 34% voting control and 2.5% cash-flow ownership of Hong Kong Electric (Claessens, Djankov, and Lang, 2000: 97). This example suggests that a large family conglomerate retains effective control of a subsidiary company with relatively small stock ownership of cash flow rights in this subsidiary company. Both the prevalence and dominance of family firms suggest that significant corporate wealth tends to concentrate in the hands of a few hereditary elites from generation to generation (Piketty, 2014).

Corporate insiders who control firm-specific assets can potentially expropriate outside minority investors by diverting resources for their personal use or by committing funds to unprofitable investment projects that provide private benefits of control to these insiders. This diversion grants incumbents the opportunity to increase their current wealth or perquisite consumption without bearing the full cost of their actions (Shleifer and Vishny, 1997). While some earlier evidence suggests a concave quadratic relation between incumbent stock ownership and firm value (McConnell and Servaes, 1990; Morck, Shleifer, and Vishny, 1988; Holderness, Kroszner, and Sheehan, 1999), some recent studies point to the potential endogeneity issue that all of corporate ownership, investment availability, and firm valuation are jointly determined (Demsetz and Lehn, 1985; Cho, 1998; Himmelberg, Hubbard, and Palia, 1999; Core and Larcker, 2002). Controlling for this endogeneity may yield an unclear nexus between insider ownership and firm value.

Lemmon and Lins (2003) assess whether different corporate ownership structures can explain differences in firm performance during the East Asian financial crisis from July 1997 to August 1998. The crisis can serve as an exogenous shock that helps ameliorate the endogeneity issue around the relationship between corporate ownership and firm valuation. The main hypothesis is that during the crisis firm value should decline the most in firms where incumbents use ownership structures that permit these corporate insiders to effectively control the firm through high control-ownership leverage. With corporate ownership data for 800 East Asian firms, Lemmon and Lins (2003) find substantive stock return evidence in support of this hypothesis. In many East Asian firms, incumbents are able to effectively control the firm even though these corporate insiders hold relatively low cash flow ownership (i.e. the control-ownership leverage is about 2.17 times on average). During the crisis, the average cumulative stock return for firms in the high control-ownership leverage group is –56.2% in comparison to –46.5% for firms in the low leverage group. Ceteris paribus, the 9.7% difference is statistically significant at any conventional confidence level. Thus, firms with high control-ownership leverage exhibit significantly worse stock return performance during the crisis in comparison to firms with low leverage. The ability to control the firm’s assets is a necessary antecedent for the expropriation of minority shareholders.

Lemmon and Lins’s (2003) evidence resonates with a recent line of corporate ownership and governance literature that the widespread use of pyramidal chains and cross-ownership structures in East Asia allows corporate insiders to exercise effective control over the firm although these insiders hold relatively few of its cash flow rights (La Porta, Lopez-de-Silanes, and Shleifer, 1999; Claessens, Djankov, and Lang, 2000; Lins, 2003). In many emerging markets, the absence of robust legal protective rules and institutions or other external governance mechanisms such as takeovers and block-ownership limits further increases the severity of agency problems between inside blockholders and minority shareholders.

High incumbent stock ownership concentration exacerbates the deviation from the social optimum when inside blockholders hold excess voting control rights in comparison to their cash flow rights. For instance, the cost of debt is significantly higher for firms with a wider wedge between the largest ultimate owner’s control rights and cash flow rights due to potential tunneling and self-dealing behaviors and other moral hazard activities by inside blockholders (Lin, Ma, Malatesta, and Xuan, 2011). Also, the shadow price of external finance is significantly higher for firms that experience a wider control-ownership wedge among corporate insiders, thus corporations whose incumbents have large excess control rights tend to face more severe financial constraints (Lin, Ma, and Xuan, 2011). These negative outcomes tend to arise from high incumbent stock ownership concentration. The above equilibrium interplay between inside blockholders and small minority shareholders suggests corporate rent protection in favor of incumbents who hold large blocks of stock in the firm.

Is international divergence from Berle-Means stock ownership dispersion an optimal corporate outcome?

Adolf Berle and Gardiner Means’s (1932) seminal work serves as the canonical qualitative basis for the separation of corporate ownership and control. Their primary thesis has set the mainstream foundation of corporate governance research for legal scholars, practitioners, and economists over 90 years. In line with this Berle-Means thesis, corporate control over physical assets responds to a centripetal force and concentrates in the hands of only a few incumbents, whereas, corporate ownership is centrifugal, splits into small units, and passes from one person to another (Berle and Means, 1932: 9). In the Berle-Means image of the modern corporation, executives and directors gain their income primarily from the effort that these incumbents put into business decisions, but not from the return on their stock investment in the enterprise. To the extent that corporate structures evolve in response to competitive pressures in the capital markets, the Berle-Means thesis predicts gradual convergence toward diffuse equity ownership as the most efficient form.

In this paper, we design and develop a model of corporate ownership and control to assess the theoretical plausibility of Berle-Means convergence toward dispersed incumbent stock ownership. To the best of our knowledge, this study is the first mathematical analysis of whether Berle-Means convergence is optimal. Further, this analysis delves into whether Berle-Means convergence is desirable from the social planner’s perspective. A subsequent analysis explores the equilibrium interplay between inside blockholders and minority shareholders.

The core analytical results suggest that Berle-Means convergence occurs when legal institutions for investor protection outweigh in relative importance firm-specific asset protection of investor rights. While legal and firm-specific asset arrangements are complementary sources of investor protection, Berle-Means convergence toward dispersed incumbent stock ownership draws the corporate outcome to the socially optimal quality of corporate governance. High incumbent stock ownership creates perverse incentives for inside blockholders to steer corporate decisions to the detriment of minority shareholders.

In the current study, we extend and generalize Yeh, Lim, and Vos’s (2007) baseline model of Berle-Means convergence with the constant elasticity of substitution (CES) production function in comparison to the Cobb-Douglas special case. While the first proposition remains the same in this more general CES production function, several new analytical results include institutional complementarities, socially optimal incumbent equity ownership stakes, and persistent deviations from Berle-Means stock ownership dispersion in equilibrium. The latter result is an equilibrium subpar outcome in the corporate game with information asymmetries between inside blockholders and minority shareholders. These novel propositions serve as the theoretical basis for subsequent empirical analysis. The appendices provide the complete mathematical derivation.

Our analysis rests on the fundamental concept that corporate insiders can often steer key business decisions at the detriment of minority shareholders. The corporate governance literature is replete with examples of deliberate use of managerial power that leads to a deterioration in firm value. For instance, incumbents may engage in earnings management prior to major corporate events such as initial public offerings (Teoh, Welch, and Wong, 1998a), seasoned equity offerings (Teoh, Welch, and Wong, 1998b), stock-for-stock mergers (Erickson and Wang, 1999; Louis, 2004), and open-market repurchases (Gong, Louis, and Sun, 2008). Also, corporate managers tend to opportunistically time the stock market through equity issuance when the firm’s market value is high relative to its book value or past market values (e.g. Jung, Kim, and Stulz, 1996; Pagano, Panetta, and Zingales, 1998; Baker and Wurgler, 2002; Huang and Ritter, 2009). In addition, abnormal stock returns tend to arise as a result of corporate events that are associated with asset expansion or contraction (e.g. Loughran and Ritter (1995), Ikenberry, Lakonishok, and Vermaelen (1995), Loughran and Vijh (1997), Titman, Wei, and Xie (2004), Anderson and Garcia-Feijoo (2006), Fama and French (2006), and Cooper, Gulen, and Schill (2008)). Incumbent blocks of stock further facilitate this managerial rent-protection mechanism that drives business decisions to benefit inside blockholders (e.g. Bebchuk, 1999; Bebchuk and Roe; 1999; Dyck and Zingales, 2004). In this context, the desire for retaining private benefits of control may induce incumbents to introduce corporate arrangements such as poison pills and board classifications to insulate directors and executives from the influence of outside blockholders (Shleifer and Vishny, 1986; Bebchuk, Coates, and Subramanian, 2002; Bebchuk and Cohen, 2005; Bebchuk and Kamar, 2010; Bebchuk and Jackson, 2012; Bebchuk, 2013; Bebchuk, Brav, and Jiang, 2015). In summary, both managerial power and entrenchment are essential ingredients in our analysis of the equilibrium interplay between inside blockholders and minority shareholders. This interplay can shed light on whether the Berle-Means image of the modern corporation is sustainable near the social optimum.

This study provides a theoretical model of the dynamic evolution of corporate ownership and governance structures over time. This model is general enough to encapsulate both arguments for and against Berle-Means convergence as special cases. In the context of equilibrium interplay between inside blockholders and minority shareholders, the model predicts that the former obtain a positive rent from their large blocks of stock by having both corporate power and influence to steer business decisions while the latter maintain a neutral utility threshold. Insofar as incumbents seek and secure economic rent in the corporate game, this equilibrium interplay persists as a non-trivial deviation from the social optimum. Berle-Means convergence toward diffuse incumbent stock ownership hence may or may not materialize due to the unilateral tilt of both legal and firm-specific asset arrangements for investor protection. In summary, our mathematical analysis sheds skeptical light on high insider stock ownership with managerial entrenchment and rent protection.

With U.S. fintech patent approval, accreditation, and protection for 20 years, our AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors worldwide.

We build, design, and delve into our new and non-obvious proprietary algorithmic system for smart asset return prediction and fintech network platform automation. Unlike our fintech rivals and competitors who chose to keep their proprietary algorithms in a black box, we open the black box by providing the free and complete disclosure of our U.S. fintech patent publication. In this rare unique fashion, we help stock market investors ferret out informative alpha stock signals in order to enrich their own stock market investment portfolios. With no need to crunch data over an extensive period of time, our freemium members pick and choose their own alpha stock signals for profitable investment opportunities in the U.S. stock market.

Smart investors can consult our proprietary alpha stock signals to ferret out rare opportunities for transient stock market undervaluation. Our analytic reports help many stock market investors better understand global macro trends in trade, finance, technology, and so forth. Most investors can combine our proprietary alpha stock signals with broader and deeper macrofinancial knowledge to win in the stock market.

Through our proprietary alpha stock signals and personal finance tools, we can help stock market investors achieve their near-term and longer-term financial goals. High-quality stock market investment decisions can help investors attain the near-term goals of buying a smartphone, a car, a house, good health care, and many more. Also, these high-quality stock market investment decisions can further help investors attain the longer-term goals of saving for travel, passive income, retirement, self-employment, and college education for children. Our AYA fintech network platform empowers stock market investors through better social integration, education, and technology.

Corporate ownership governance theory and practice - Blog - AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors.

Corporate ownership governance theory and practice

https://ayafintech.network/blog/corporate-ownership-governance-theory-and-practice/

Olivia London

2025-02-26 00:00:12

Bullish

Quantitative fundamental analysis

Our latest podcast deep-dives into the recent empirical evidence in relation to corporate investment management (mergers and acquisitions (M&A), capital expenditures (CAPEX), and research and development (R&D) projects).

$RDDT $NVDA $AMC $TTD $IONQ $NFLX $USNA $SBUX $MTCH $TSLA $LLYVA $INTU $MSFT $AMGN 

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The original blog article is available on our AYA fintech network platform. https://ayafintech.network/blog/corporate-investment-management/

This fun podcast is about 10 minutes long (with smart AI podcast generation from Google NotebookLM). https://bit.ly/4aEKfaB

This review of corporate investment literature focuses on some recent empirical studies of M&A, capital investment, and R&D innovation. This focus spans the empirical evidence in support of the misvaluation and q-theories of takeovers (Dong, Hirshleifer, Richardson, and Teoh, 2006), the effect of anti-takeover provisions on bidder returns around major acquisition announcements (Masulis, Wang, and Xie, 2007), the managerial entrenchment theory for M&A value destruction (Harford, Humphery-Jenner, and Powell, 2012), the complex nexus between CEO overconfidence and corporate investment (Malmendier and Tate, 2005, 2008; Hirshleifer, Low, and Teoh, 2012), and the relation between acquirer-target connections and merger outcomes (Cai and Sevilir, 2012; Ishii and Xuan, 2014). Some subsequent discussion touches on the central theme of stock-market-driven acquisitions in behavioral finance (Shleifer and Vishny, 2003; Baker, Pan, and Wurgler, 2012). The literature review paints several coherent tiles in the complete mosaic of corporate investment management.

Dong, Hirshleifer, Richardson, and Teoh (2006) document evidence in support of the misvaluation and q-theories of takeovers. The misvaluation theory holds that market inefficiency has important effects on takeover activity. These effects stem from the bidder’s efforts to profit by buying undervalued targets for cash at market prices below their fundamental values, or by paying equity for targets that are less over-valued than the bidder (Shleifer and Vishny, 2003). Moreover, the q-theory of takeovers focuses on how acquisitions deploy target assets. High market valuation reflects that a firm is well run with good growth opportunities. Therefore, relative market values are proxies for growth opportunities for both the bidder and the target. Takeovers may be designed to take advantage of better acquirer investment opportunities with minimal wasteful target engagement. Alternatively, takeovers may be viewed by the incumbents of an inefficient bidder as an opportunity to expand their domains of control. Dong, Hirshleifer, Richardson, and Teoh (2006) establish several empirical regularities that bolster both the misvaluation and q-theories of takeovers:

1. Acquirers are highly valued relative to their targets, especially among equity offers and merger bids.

2. More highly valued bidders are more likely to use stock and less likely to use cash as consideration, are willing to pay more relative to target market values, are more inclined to use merger bids in lieu of tender offers, and earn lower returns around merger announcements.

3. Targets with lower market valuation receive higher premia relative to their market prices, are more likely to be hostile to the takeover, are more likely to receive tender offers in lieu of merger bids, are less likely to be successfully acquired, and earn higher returns around acquisition announcements.

Dong, Hirshleifer, Richardson, and Teoh (2006) and Masulis, Wang, and Xie (2007) confirm Loughran and Vijh’s (1997) study of acquirer returns around takeover announcements that stock acquisitions attract negative abnormal bidder returns around merger announcements while cash acquisitions attract positive abnormal bidder returns around merger announcements. Bidder and target market values (price-to-book or price-to-residual-income) significantly correlate with means of payment, mode of acquisition, target premium, target hostility, offer success, and bidder and target returns around takeover announcements.

Masulis, Wang, and Xie (2007) find that excessive managerial entrenchment with takeover defenses has a first-order negative impact on bidder value. Harford, Humphery-Jenner, and Powell (2012) extend this logic and empirically demonstrate that a significant portion of merger value destruction arises from the avoidance of private targets with better ex post managerial entrenchment. When incumbents that receive better insulation from anti-takeover provisions target private firms, these incumbents primarily use cash. This cash payment effectively helps avoid both the potential creation and scrutiny of future blockholders. This rationale also applies to the acquisition of public firms. Incumbents that benefit from more takeover defenses prefer not to use stock when their companies acquire public companies with large blockholders. Nonetheless, target form is not the whole explanation for merger value destruction because on average incumbents that benefit from more takeover defenses make unprofitable acquisitions.

Harford, Humphery-Jenner, and Powell (2012) use the Heckman (1979) sample selection model to affirm that the binary flag for anti-takeover dictatorship has a significantly negative impact on the likelihood of acquiring private targets, acquiring private targets entirely with stock, or acquiring targets with at least 5% blockholder ownership. Harford, Humphery-Jenner, and Powell (2012) apply Officer’s (2007) proxy premium regressions of 5-day cumulative abnormal returns on the binary flag for anti-takeover dictator-ship, the dummy variable for all-stock takeover, the interaction between the dictatorship dummy variable and the proxy premium, and an array of control variables. Ceteris paribus, the dummy variables and the interaction term all carry significantly negative coefficients. This evidence suggests both overpayment and poor target selection as plausible explanations for merger value destruction.

All merger value destruction involves overpayment. Greater managerial entrenchment usually results in worse post-merger operating performance in the Healy-Palepu-Ruback (1992) regressions of industry-adjusted ROAs on the governance or entrenchment index and a set of control variables for the complete sample and different anti-takeover subsamples. This evidence suggests that substandard target selection, rather than only overpayment, explains most merger value destruction. In sum, incumbents that are secure with more takeover defenses often seek to preserve their entrenchment through deliberate target selection.

A body of corporate governance literature suggests a negative nexus between anti-takeover provisions (ATPs) and both firm values and long-term stock returns (Gompers, Ishii, and Metrick, 2003; Bebchuk, Cohen, and Ferrell, 2009). ATPs give rise to higher agency costs through some combination of inefficient investment, lower operational efficiency, and managerial self-dealing behavior. Masulis, Wang, and Xie (2007) directly investigate the impact of a firm’s ATPs on its investment efficiency, or specifically, the shareholder wealth effect of its corporate acquisitions. Acquisition announcements made by firms with more ATPs in place yield significantly lower abnormal bidder returns than acquisition announcements made by firms with fewer ATPs.

Moreover, Masulis, Wang, and Xie (2007) examine the separate impact of external or internal corporate governance mechanisms such as product market competition, board composition such as board size and independence and CEO-chairman duality, as well as operating performance (as a proxy for management quality). Firms that operate in more competitive industries make better acquisitions with larger abnormal bidder returns, as do firms that separate the positions of CEO and chairman of the board.

Masulis, Wang, and Xie (2007) can identify an important channel through which takeover defenses erode shareholder value. ATPs allow corporate incumbents to make unprofitable acquisitions without facing a serious threat of losing corporate control. Masulis, Wang, and Xie (2007) also contribute to the literature on corporate governance by highlighting the importance of the market for corporate control in providing managerial incentives to increase shareholder wealth. This contribution expands the array of corporate governance mechanisms and so pertains to the empirical studies of Bebchuk and Cohen (2005), Cremers and Nair (2005), and Bebchuk, Cohen, and Ferrell (2009).

As the largest and most readily observable form of corporate investment, acquisitions tend to intensify the conflict of interest between corporate incumbents and shareholders in large public corporations (Berle and Means, 1932; Jensen and Meckling, 1976). Incumbents may not always make profitable acquisitions. Often incumbents reap private benefits of control at the detriment of minority shareholders. Incumbents extract large benefits from their empire-building attempts, thus firms with abundant free cash flows but few profitable investment opportunities are more likely to engage in M&A and capital over-investments (Jensen, 1986; Lang, Stulz, and Walking, 1991).

By substantially delaying the takeover process and thereby raising the costs of a hostile acquisition, ATPs reduce the likelihood of a successful takeover and hence the incentives of potential acquirers to launch a bid (e.g. Bebchuk, Coates, and Subramanian (SLR 2002)). ATPs undermine the ability of the market for corporate control to perform its ex post settling-up function. The conflict of interest between incumbents and investors is more severe at firms with more ATPs or firms that are less vulnerable to hostile takeovers.

The IRRC publications cover 24 anti-takeover provisions from which Gompers, Ishii, and Metrick (2003) construct the governance index by adding one point for each provision that enhances managerial power. High G-index firms with more ATPs yield lower long-run stock returns and firm values (Gompers, Ishii, and Metrick, 2003). Bebchuk, Cohen, and Ferrell (2009) extend these results by creating a more parsimo-nious entrenchment index based on the 6 major provisions that are most important from a legal standpoint: staggered boards, poison pills, golden parachutes, supermajority requirements for mergers, and limits to shareholder bylaw amendments and charter amendments.

In the above context, Masulis, Wang, and Xie (2007) deduce the hypothesis of ATP value destruction: incumbents with more ATP insulation are more likely to engage in acquisitions that do not contribute to shareholder wealth maximization. Acquisition announcements made by firms with more ATPs in place produce significantly lower abnormal bidder returns than acquisition announcements made by firms with fewer ATPs. Each additional anti-takeover provision reduces bidder shareholder value by about 0.1%. As a typical dictatorship firm has 10 more ATPs than a typical democracy firm, the former underperforms the latter by about 1%, which is non-trivial relative to the mean cumulative abnormal return around the acquisition announcement of 0.215% (e.g. board classifications correspond to a mean shareholder value loss of $30 million).

Product market competition has a positive disciplinary effect on managerial behavior (Leibenstein, 1966; Hart, 1983; Shleifer and Vishny, 1997). Incumbents of firms that operate in competitive industries are unlikely to divert valuable corporate resources into inefficient uses. In more competitive industries, the margin for error is thin and any missteps can be quickly exploited by competitors. In turn, these missteps jeopardize firms’ prospects for survival. Masulis, Wang, and Xie (2007) use the Herfindahl-Hirschman index as a proxy for industry competition and the industry’s median ratio of selling expenses to sales as a proxy for product uniqueness (Titman and Wessels, 1988). Masulis, Wang, and Xie (2007) document a positive relation between product market competition and bidder return performance.

The board of directors serves as an important internal control mechanism. CEO-chairman duality, board size, and board independence are key characteristics that affect how effectively the board functions (Core, Holthausen, and Larcker, 1999; Hermalin and Weisbach, 2003). Masulis, Wang, and Xie (2007) find a negative nexus between CEO-chairman duality and bidder stock return performance. Separating the CEO and chairman positions helps rein in empire-building attempts by CEOs. As a consequence, these CEOs become more selective in their acquisition decisions that lead to greater shareholder wealth.

Less able CEOs make poor acquisitions and adopt ATPs to entrench themselves. A common practice is to measure bidder CEO quality by industry-adjusted operating income growth over the 3 years prior to the acquisition announcement (Morck, Shleifer, and Vishny, 1990). Masulis, Wang, and Xie (2007) find a positive relationship between bidder management quality and short-run stock return performance. Thus, CEOs of better management quality make better acquisitions in the best interests of shareholders.

Masulis, Wang, and Xie’s (2007) study of short-run abnormal bidder returns reinforces the prior evidence that firms with fewer ATPs generate better long-run shareholder value in comparison to firms with more ATPs (Cremers and Nair, 2005; Core, Guay, and Rusticus, 2005). Overall, Masulis, Wang, and Xie (2007) find empirical support for the hypothesis of ATP value destruction: incumbents with more ATP insulation are more likely to engage in acquisitions that do not contribute to shareholder wealth maximization. In essence, acquisition announcements made by firms with more ATPs in place produce significantly lower abnormal bidder returns than acquisition announcements made by firms with fewer ATPs.

With U.S. fintech patent approval, accreditation, and protection for 20 years, our AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors worldwide.

We build, design, and delve into our new and non-obvious proprietary algorithmic system for smart asset return prediction and fintech network platform automation. Unlike our fintech rivals and competitors who chose to keep their proprietary algorithms in a black box, we open the black box by providing the free and complete disclosure of our U.S. fintech patent publication. In this rare unique fashion, we help stock market investors ferret out informative alpha stock signals in order to enrich their own stock market investment portfolios. With no need to crunch data over an extensive period of time, our freemium members pick and choose their own alpha stock signals for profitable investment opportunities in the U.S. stock market.

Smart investors can consult our proprietary alpha stock signals to ferret out rare opportunities for transient stock market undervaluation. Our analytic reports help many stock market investors better understand global macro trends in trade, finance, technology, and so forth. Most investors can combine our proprietary alpha stock signals with broader and deeper macrofinancial knowledge to win in the stock market.

Through our proprietary alpha stock signals and personal finance tools, we can help stock market investors achieve their near-term and longer-term financial goals. High-quality stock market investment decisions can help investors attain the near-term goals of buying a smartphone, a car, a house, good health care, and many more. Also, these high-quality stock market investment decisions can further help investors attain the longer-term goals of saving for travel, passive income, retirement, self-employment, and college education for children. Our AYA fintech network platform empowers stock market investors through better social integration, education, and technology.

Corporate investment management - Blog - AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors.

Corporate investment management

https://ayafintech.network/blog/corporate-investment-management/

Apple Boston

2025-02-24 02:16:02

Bullish

Quantitative fundamental analysis

Our latest podcast deep-dives into the recent empirical results in relation to corporate diversification, with a special emphasis on both the bright and dark sides of internal capital markets. The bright-side view posits that internal capital markets benefit from stronger control rights and fewer information asymmetries across intra-firm divisions while this benefit in turn enables the CEO to make better fund allocation decisions. In contrast, the dark-side view suggests that internal capital markets suffer from the agency motives of both divisional managers and the CEO who might prefer to pursue their private interests. Several recent empirical studies delve into the delicate balance between the bright and dark sides of internal capital markets.

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The original blog article is available on our AYA fintech network platform. https://ayafintech.network/blog/corporate-diversification-theory-and-evidence/

This fun podcast is about 10 minutes long (with smart AI podcast generation from Google NotebookLM). https://bit.ly/4hhxUMf

A recent strand of corporate diversification literature spans at least three generations. The first generation suggests that corporate diversification typically erodes firm value. The entire firm value is less than the sum of the imputed values of different segments. The diversification discount is 12%-15% of Tobin’s q (e.g. Lang and Stulz (1994) and Berger and Ofek (1995)). Also, the second generation suggests that the diversification discount is at least partly attributable to the use of anti-takeover provisions, which insulate incumbents from the direct influence of hostile takeovers and hence result in poor corporate governance (Hoechle, Schmid, Walter, and Yermack, 2012). Finally, the third generation sheds fresh light on the role of internal capital markets that help transfer valuable capital from one division to another division within the same enterprise (e.g. Duchin (2010) and Duchin and Sosyura (2013)). Both the bright and dark sides of internal capital markets warrant attention from corporate decision-makers.

Lang and Stulz (1994) empirically find that corporate diversification erodes firm value. The typical firm decides to diversify into some other industry segments when there are few internal investment growth opportunities. On average, the firm diversification discount is about 12%-15% of Tobin’s q. Furthermore, Berger and Ofek (1995) report that the diversification discount is much smaller when this diversification occurs in somewhat related industry segments at the 2-digit SIC codes. Also, overinvestment and cross-subsidization contribute to the loss of firm value that arises from corporate diversification.

More recent empirical studies suggest that firm diversification occurs endogenously in response to both corporate value and governance (Campa and Kedia, 2002; Graham, Lemmon, and Wolf, 2002; Villalonga, 2004). Valid instruments are the lags of firm performance, corporate governance, and several other firm attributes (Wintoki, Linck, and Netter, 2012). In the special case of both international and U.S. financial conglomerates, Laeven and Levine (2007) and Schmid and Walter (2009) empirically find an increase in the diversification discount when the econometrician uses the Heckman (1979) sample selection model to account for any self-selection bias that may arise from corporate diversification.

Hoechle, Schmid, Walter, and Yermack (2012) investigate whether the diversification discount occurs as an artifact of poor corporate governance. A number of dynamic panel regressions adequately control for potential endogeneity of the typical firm’s diversification decision. The diversification discount shrinks by a full order of magnitude with the addition of governance variables such as anti-takeover provisions to the dynamic panel regressions. Differences in the quality of corporate governance across conglomerate firms can help explain at least part of the negative nexus between firm value and corporate diversification. Specifically, Hoechle, Schmid, Walter, and Yermack’s (2012) baseline panel regression model suggests that the diversification discount decreases from 15%-17% to about 13% when the econometrician adds a plethora of corporate governance variables such as institutional ownership, CEO stock ownership and its square, CEO power, and G-index of anti-takeover provisions to the panel regressions of excess value multiples to total sales or total assets with firm-specific fixed effects. If poorly governed firms often tend to diversify, perhaps through mergers, acquisitions, and overinvestments in somewhat unrelated industry segments, then the diversification discount could be the symptom of a larger problem in the fundamental context of corporate governance.

Hoechle, Schmid, Walter, and Yermack (2012) follow Campa and Kedia’s (2002) treatment of potential endogeneity by implementing the Heckman (1979) sample selection model to reassess the diversification discount. The Heckman method involves a two-step procedure that uses a probit model for the subsequent analysis of discount determinants. The econometrician first estimates the firm’s propensity to diversify with a probit model via quasi-maximum likelihood estimation. The inverse Mills ratio can be computed as the hazard rate of the probability density function (pdf) to the cumulative density function (cdf) from the first-step probit estimation. In turn, this ratio serves as an auxiliary explanatory variable in the second-step regression of excess firm value on a unique set of firm attributes. The resultant parameters would be consistent with the true counterparts (Heckman, 1979).

A firm’s current actions affect its future corporate governance and firm performance, the latter of which then affects the firm’s future actions (e.g. Hermalin and Weisbach (2004) and Wintoki, Linck, and Netter (2012)). In order to address the dynamic endogeneity issue, Hoechle, Schmid, Walter, and Yermack (2012) run the GMM panel regression model that corresponds to a dynamic system of simultaneous equations. The first step involves the inclusion of performance lags as explanatory variables in the dynamic model. The econometrician first-differences each factor to remove any unobservable heterogeneity and omitted-variables bias. Then the econometrician estimates the GMM panel regression model with the use of lags of the diversification, governance, and performance variables as well as some other firm characteristics as exogenous instruments.

While the Heckman (1979) sample selection model suggests that the diversification discount vanishes as a result of adding corporate governance variables to the set of explanatory variables, the dynamic GMM panel regressions produce a smaller but still significant diversification discount. Specifically, the GMM estimate of diversification discount decreases from 12% (t-ratio>2) to 7.6% (t-ratio<2) with the addition of corporate governance variables. Overall, poor corporate governance helps explain at least part of the corporate diversification discount.

Masulis, Wang, and Xie’s (2007) event study suggests that merger announcement returns are significantly lower for acquirers with poor corporate governance structures (e.g. more anti-takeover provisions in the market for corporate control). Specifically, acquirers with more anti-takeover provisions or joint CEO-chairman positions experience significantly lower merger-announcement cumulative abnormal returns. In order to evaluate whether the diversification discount decreases with better corporate governance in merger and acquisition announcements, Hoechle, Schmid, Walter, and Yermack (2012) add the same set of governance variables plus the diversification dummy variable to the panel regressions of post-merger announcement cumulative abnormal returns within short time windows. The main evidence suggests that the negative cumulative abnormal return for corporate diversification decreases from nearly 1.2%-1.6% (t-ratio>2) to 0.3%-0.6% (t-ratio<2). This event study echoes the overarching thesis of the dynamic panel regression results that poor corporate governance helps explain at least part of the diversification discount.

A major implication of corporate diversification pertains to the precautionary demand for cash retention. According to the precautionary cash demand story (Keynes, 1936), firms hold cash to protect themselves against adverse cash flow shocks that might force these firms to forego valuable investment opportunities due to costly external finance. Some recent empirical studies of structural shifts in corporate cash reserves lend credence to the central thesis that firms increasingly hold cash for a precautionary motive while the median firm’s net debt (i.e. total debt minus cash) is below zero (Opler, Pinkowitz, Stulz, and Williamson, 1999; Almeida, Campello, and Weisbach, 2004; Bates, Kahle, and Stulz, 2009).

Well-diversified firms exhibit lower cross-divisional correlations in investment opportunities and smaller financing deficits (Duchin, 2010). These well-diversified firms enjoy the benefit of coinsurance, which reduces their exposure to risk and allows them to hold lower amounts of precautionary cash in contrast to their standalone counterparts. Multi-divisional firms hold approximately half as much cash as highly specialized firms do. The difference is largely due to corporate diversification in investment opportunities and cash flows. Well-diversified firms hold low precautionary cash balances, which in turn reflect sound governance and efficient fund transfer within these firms.

Duchin and Sosyura (2013) draw a clear distinction between the bright and dark sides of internal capital markets. The bright-side view posits that internal capital markets benefit from stronger control rights and fewer information asymmetries across intra-firm divisions while this benefit in turn enables the CEO to make better fund allocation decisions (e.g. Naveen and Tice (2001) and Maksimovic and Phillips (2002)). In contrast, the dark-side view suggests that internal capital markets suffer from the agency motives of both divisional managers and the CEO who might prefer to pursue their private interests (Scharfstein and Stein, 2000; Rajan, Servaes, and Zingales, 2000; Ozbas and Scharfstein, 2009). The relative importance of divisional managers garners practical support from the survey evidence of Graham, Harvey, and Puri (2015) who report that the CEO’s opinion of a divisional manager is the second most important factor in internal capital allocation after the net present value rule.

Duchin and Sosyura (2013) offer evidence on the watershed between the bright and dark sides of internal capital markets by constructing a hand-collected dataset of divisional managers at S&P 500 firms with managerial attributes and connections to the CEO on capital allocation decisions. In particular, Duchin and Sosyura (2013) evaluate the involvement of divisional managers in the firm via various channels, ranging from formal board membership and seniority to informal social connections to the CEO via prior employment, educational institutions, and non-profit organizations. The evidence suggests that divisional managers with social connections to the CEO receive more capital after the econometrician controls for divisional size, performance, proxies for investment opportunities, and other characteristics. One social connection between a divisional manager and the CEO correlates with 7.2% greater capital allocation to his or her division or about $4.2 million in annual expenditure in a division with median characteristics.

At well-governed firms with high information asymmetries, where divisional managers are likely to have valuable information about investment opportunities, social connections between the CEO and divisional managers significantly correlate with better investment efficiency and firm valuation. In contrast, at firms with poor governance, which are more prone to agency-driven favoritism, managerial connections to the CEO are negatively related to investment efficiency and firm value. Duchin and Sosyura’s (2013) study draws a clear empirical distinction between the bright and dark sides of internal capital markets. In this light, corporate diversification results in some costs and benefits that must be weighed against managerial connections to the CEO in different contexts.

With U.S. fintech patent approval, accreditation, and protection for 20 years, our AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors worldwide.

We build, design, and delve into our new and non-obvious proprietary algorithmic system for smart asset return prediction and fintech network platform automation. Unlike our fintech rivals and competitors who chose to keep their proprietary algorithms in a black box, we open the black box by providing the free and complete disclosure of our U.S. fintech patent publication. In this rare unique fashion, we help stock market investors ferret out informative alpha stock signals in order to enrich their own stock market investment portfolios. With no need to crunch data over an extensive period of time, our freemium members pick and choose their own alpha stock signals for profitable investment opportunities in the U.S. stock market.

Smart investors can consult our proprietary alpha stock signals to ferret out rare opportunities for transient stock market undervaluation. Our analytic reports help many stock market investors better understand global macro trends in trade, finance, technology, and so forth. Most investors can combine our proprietary alpha stock signals with broader and deeper macrofinancial knowledge to win in the stock market.

Through our proprietary alpha stock signals and personal finance tools, we can help stock market investors achieve their near-term and longer-term financial goals. High-quality stock market investment decisions can help investors attain the near-term goals of buying a smartphone, a car, a house, good health care, and many more. Also, these high-quality stock market investment decisions can further help investors attain the longer-term goals of saving for travel, passive income, retirement, self-employment, and college education for children. Our AYA fintech network platform empowers stock market investors through better social integration, education, and technology.

Corporate diversification theory and evidence - Blog - AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors.

Corporate diversification theory and evidence

https://ayafintech.network/blog/corporate-diversification-theory-and-evidence/

James Campbell

2025-02-20 02:16:52

Bullish

Quantitative fundamental analysis

Our latest podcast deep-dives into why President Trump continues to blame China for the long prevalent U.S. trade deficits and several other social and economic deficiencies as he moves into his second term.

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This fun podcast is about 10 minutes long (with smart AI podcast generation from Google NotebookLM). https://bit.ly/42ucDKt

In recent years, President Donald Trump blames China for the long prevalent high U.S. trade deficits against the middle kingdom. Now China seems to hollow out the American industrial homeland from smartphones and semiconductor microchips to electric vehicles (EV), drones, high-speed broadband networks, cloud services, and even large language models (LLM) for generative artificial intelligence. President Trump further blames China for causing the Covid pandemic crisis worldwide. Also, President Trump accuses China of attacking the U.S. and its western allies with fentanyl in the current opioid crisis. Given his U.S. domestic economic protectionism, President Trump seeks to double down on the hardline trade war with China. Specifically, President Trump seeks to impose hefty tariffs, export restrictions, and indefinite bans on many foreign investment categories against China. As President Trump moves into his second term, he continues to view China as a geopolitical adversary in a zero-sum game. In order to make America great again, many supporters seem to think only President Trump and his hardcore cabinet members can come up with hardline economic policies, sanctions, and regulations to tame the respective foes and rivals in Beijing. Political tensions between the U.S. and China continue to persist and even exacerbate in recent years. As a result, the bilateral relations between the U.S. and China seem to rest on flimsy foundations. Nowadays, geopolitical alignment often reshapes and reinforces asset market fragmentation in the wider context of financial deglobalization. Around the world, several western governments seek to incorporate new elements of global resilience into economic statecraft.

In China, President Xi Jinping and his cabinet members may not view the new Trump second term with fear and trepidation. These Chinese leaders, technocrats, and diplomats already learned much from the Trump first term, the Biden administration, and the populist return of Donald Trump to the White House in recent years. President Trump tends to apply economic protectionism across many industrial sectors and categories with fresh geopolitical tensions and frictions on the global stage. Early in his second term, President Trump declares retreats from the international Paris climate agreement, Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP), and even the World Health Organization (WHO). In effect, these complete withdrawals highlight the fact that the new Trump administration tends to undertake unilateral measures in support of greater economic protectionism in America. Despite the growing trade tensions, disputes, and frictions between Beijing and Washington, the Xi administration still seeks to navigate new confrontations in global trade, finance, and technology. Also, the new Trump administration may impose new tariffs and other economic sanctions on Canada, Mexico, and some other western allies. This hardline approach would encourage many countries, such as France, Germany, Japan, and Australia, to hedge their foreign investment bets outside North America. Specifically, these countries may choose to build better ties with Beijing, partly through its Belt-and-Road Initiative, in response to greater economic policy uncertainty in Washington. Although the U.S. and China may inadvertently stumble into the proverbial Thucydides trap, we believe the best likelihood of military threats between these dual superpowers remains quite low. Over the past decade, President Trump has not shown any deep and extreme ideological inclinations. It does not seem likely for the current competition between the U.S. and China to further escalate into a more destructive New Cold War. Although President Trump sees more realism in the current balance of power between the U.S. and China, he strives to stop-and-prevent wars in the hot and lofty pursuit of world peace. In recent years, President Trump has reiterated his intentions to coordinate truces, ceasefires, and peaceful resolutions of the relentless Russia-Ukraine war in Eastern Europe, as well as the current conflicts between Israel and Iran, Lebanon, Hamas, and the Palestinians in the Middle East. The new Trump administration seeks to better contain China, its recent rise on the global stage of economic growth, and endless interference over Taiwan along the Pacific first island chain.

Beijing believes Trump’s presidential election victory has little or minimal influence over the near-term trajectory of U.S. foreign policies toward China. In U.S. Congress, the bipartisan consensus perceives China as a unique series of new economic, technological, military, and diplomatic threats to the U.S. and its western allies, regardless of who wins the presidential bid to enter the White House. To the extent that the U.S. seeks to further contain-and-derisk from China, Russia, Iran, and North Korea, geopolitical alignment reshapes and reinforces asset market fragmentation in the broader context of financial deglobalization. Through U.S. political history, not everything remains the same from one administration to another. During his second term, President Trump is likely to maintain the hardline approach to foreign affairs with China not only from his own first term, but also from the Biden administration. President Trump seems to have learned from his first term that the current hardline approach to China would need to refresh with new and much younger cabinet members, such as Secretary of State Marco Rubio and Secretary of Defense Peter Hegseth, both of whom serve as China hawks with strong anti-communist beliefs. The devil is in the details. President Trump needs more nuance in the new bilateral relations between the U.S. and China. This nuance directs President Trump’s nominations for foreign policy and national security positions away from right-wing extremists (who served in their rightful capacity in the first Trump administration). In support of calm and stable asset markets, President Trump picks new cabinet members as strategic partners who can help advise on a wide range of global economic, technological, military, and diplomatic themes and issues during the recent rise of China, Russia, Iran, and North Korea on the global stage. Many of the new cabinet members continue to view China as the primary threat to the U.S. with substantial economic and technological advancements. For this reason, these cabinet members tend to favor new hardline and coercive measures for the new Trump administration to constrain China’s sphere of influence. Unlike the former Soviet Union in the Cold War era, China retains virtually no or few global ambitions to expand its communist propaganda. Nonetheless, the Trump administration needs to remain careful and cautious toward China’s increasingly aggressive policy stances toward Taiwan, Japan, Hong Kong, South Korea, and other strategic partners in East Asia.

In the wider geopolitical context, the same hardline approach may not work well because so much has changed significantly since the first Trump administration. When President Trump entered the White House for the first time in early-2017, many governments thought Trump would serve like a conventional American leader, an ideologically neutral businessman, and an economically rational decision-maker. Indeed, many major western allies thought Trump would commit to their common prosperity and regional security worldwide. President Trump visited China, Vietnam, South Korea, and the Philippines in November 2017. Despite U.S. opposition to Russia’s annexation of Crimea from Ukraine back in 2014, the Kremlin invited President Trump to Moscow for Russia’s annual celebration of the victory in World War II in late-2017. Subsequently, President Trump met with Russian President Vladimir Putin in a summit in Helsinki, Finland, as part of a weeklong trip to Europe in July 2018.

This time may be a bit different. Many leaders and governments are now proactive to protect their own countries from substantial economic policy uncertainty in Washington as President Trump moves into his second term. French President Emmanuel Macron invited President Trump to visit Paris as Macron would like to indicate that Europeans are their own decision-makers with respect to their own common prosperity, security, and climate risk management. Also, Japan and Germany reiterate their current concern that President Trump may require bigger fractions of their respective fiscal budgets to guarantee American military protection in their countries. In South Korea, the interim government worries that President Trump may take advantage of its current lack of authority over domestic affairs to the detriment of many special interest groups. In Taiwan, the extant government further fears that President Trump may tap into more than 5% of its annual economic output in return for U.S. military presence in response to China’s constant aggression.

In Eastern Europe, President Trump needs to grapple with the fact that Russia continues to attack Ukraine even though the U.S. and its western allies provide military support to Kiev. In the Middle East, Washington continues to provide military aid and geopolitical support for Israel’s brutal and bloody operations in Gaza, where many mainstream pundits believe there is an ongoing humanitarian crisis. Specifically, this crisis has further exposed the hypocrisy of U.S. claims to champion international law, world peace, and human rights. In his second term, President Trump has to better coordinate truces, ceasefires, and peaceful resolutions of these regional wars and conflicts in the lofty pursuit of world peace. Indeed, these peaceful resolutions can be a good legacy for President Trump to leave behind in his second term.

Since the first Trump administration, Beijing has become more adept at managing its current competition with Washington. We can trace this competition to the Obama administration in 2010 when President Obama embarked on a strategic pivot to Asia. In the subsequent years, Beijing has successfully navigated the different foreign-policy strategies and paradigms of the Obama, Trump, and Biden administrations. Both Biden and Obama attempted to contain China through multilateral negotiations, engagements, and approaches, while Trump took a more unilateral foreign policy stance toward China. With a decade-long experience, Chinese leaders remain calm, careful, and cautious toward the same well-known prospect of a Trump second term. On some of its official government agency websites, Beijing has even released strategic guidelines on how their leaders, technocrats, and diplomats can handle President Trump’s harsh foreign-policy measures against China. The Xi administration adheres to the current commitment to mutual respect, peaceful co-existence, and win-win cooperation as the mainstream principles for China-U.S. relations in trade, finance, and technology. Mutual respect refers to the worst-case scenario where China may retaliate by offloading more than $750 billion massive stockpiles of U.S. government bonds against any provocative foreign-policy measures, export restrictions, tariffs, quotas, embargoes, and several other economic sanctions that the new Trump administration chooses to undertake against China. Peaceful co-existence reflects the fact that China seeks to engage President Trump and his reps in new mutual dialogues to better manage expectations, differences, and even conflicts. In this fashion, the ultimate peaceful resolutions would help stabilize China-U.S. relations. Win-win cooperation refers to joint collaboration on global themes and issues in which China and the U.S. share common interests. In the meantime, these global themes and issues include the peaceful resolutions of wars and conflicts in Eastern Europe and the Middle East, as well as bilateral rules and regulations for artificial intelligence infrastructure, semiconductor micro-chip design, and the worldwide flow of illicit drugs (specifically, fentanyl and ketamine).

President Trump seems intent on further entrenching U.S. domestic economic protectionism in his second term, especially when this hardline foreign policy stance involves bilateral trade with China. President Trump has indicated that he might levy higher tariffs on Chinese goods. Also, the Trump administration seeks to impose more draconian restrictions on U.S. foreign direct investments (FDI) in China as well as on Chinese capital in the U.S. stock market. In addition, the Trump administration plans to place more constraints on China-U.S. high-tech collaboration with substantially fewer Chinese students and H1-B workers in the U.S. across STEM subjects. These decisions may inadvertently result in greater frictions between Beijing and Washington. Although the Biden administration extended the tariffs that Trump imposed on Chinese goods in his first term, this extension focused on excluding China from the global supply chains for intermediate technological goods, such as semiconductor microchips and high-speed broadband networks etc. Specifically, the Biden administration sought to de-risk from China, but did not seek to completely decouple from China. Throughout Biden’s tenure, key traditional trade sectors between China and America continued business-as-usual even though their technological collaboration came to a halt. In his second term, President Trump is likely to push harder for further decoupling from China. His new industrial homeland policy stance toward China may dramatically reduce the total market share of Chinese products in America. This reduction spans intermediate goods made and built outside China; however, their lean production still relies heavily on Chinese investments, factories, components, and other industrial resources. At the same time, Beijing may retaliate by offloading at least some of the $750 billion massive stockpiles of U.S. government bonds, as well as $2 trillion dollar assets, against any provocative foreign-policy measures, export restrictions, tariffs, quotas, embargoes, and some other economic sanctions that the new Trump administration deploys against China. This tit-for-tac dynamism may drive the China-U.S. trade war to a new peak. As a consequence, the global economy would suffer with new scars and damages as many other countries scramble to implement their own protectionist policies in global trade, finance, and technology.

We build, design, and delve into our new and non-obvious proprietary algorithmic system for smart asset return prediction and fintech network platform automation. Unlike our fintech rivals and competitors who chose to keep their proprietary algorithms in a black box, we open the black box by providing the free and complete disclosure of our U.S. fintech patent publication. In this rare unique fashion, we help stock market investors ferret out informative alpha stock signals in order to enrich their own stock market investment portfolios. With no need to crunch data over an extensive period of time, our freemium members pick and choose their own alpha stock signals for profitable investment opportunities in the U.S. stock market.

With U.S. patent accreditation and protection for 20 years, our AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors.

Smart investors can consult our proprietary alpha stock signals to ferret out rare opportunities for transient stock market undervaluation. Our analytic reports help many stock market investors better understand global macro trends in trade, finance, technology, and so forth. Most investors can combine our proprietary alpha stock signals with broader and deeper macrofinancial knowledge to win in the stock market.

Through our proprietary alpha stock signals and personal finance tools, we can help stock market investors achieve their near-term and longer-term financial goals. High-quality stock market investment decisions can help investors attain the near-term goals of buying a smartphone, a car, a house, good health care, and many more. Also, these high-quality stock market investment decisions can further help investors attain the longer-term goals of saving for travel, passive income, retirement, self-employment, and college education for children. Our AYA fintech network platform empowers stock market investors through better social integration, education, and technology.

President Donald Trump blames China for the long prevalent U.S. trade deficits and several other social and economic deficiencies. - Blog - AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors.

President Donald Trump blames China for the long prevalent U.S. trade deficits and several other soc...

https://ayafintech.network/blog/president-trump-blames-china-for-the-long-prevalent-us-trade-deficits-and-other-social-and-economic-woes/

Monica McNeil

2025-02-18 02:21:31

Bullish

Hybrid analysis

Our latest podcast deep-dives into the recent empirical results in support of the mainstream corporate capital structure theories.


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The original blog article is available on our AYA fintech network platform. https://ayafintech.network/blog/capital-structure-theory-and-practice/

This fun podcast is about 10 minutes long (with smart AI podcast generation from Google NotebookLM). https://bit.ly/40w5wP2

The genesis of modern capital structure theory traces back to the seminal work of Modigliani and Miller (1958, 1963). This work not only leads to the core testable propositions but also sets the research agenda for the subsequent decades. These propositions shine light on the nexus between a corporation’s market value and the choice of debt versus equity in the absence of taxes, agency costs, financial distress costs, information asymmetries, and other market frictions.

A corporation’s market value is independent of its capital structure or relative mix of debt and equity.
The relative riskiness of a corporation’s equity increases with the degree of financial leverage.

Modigliani and Miller’s propositions suggest that the costs of different forms of capital do not change independently, so there is no gain from opportunistically switching between debt and equity. The above Modigliani-Miller propositions can be synthesized with the CAPM to yield a formula for the required rate of return on a corporation’s equity.

By adding a few market frictions to the baseline Modigliani-Miller model, the trade-off theory determines an optimal capital structure. These frictions include taxes, distress costs, and agency costs. Higher taxes on dividends indicate more debt (Modigliani and Miller, 1963; Miller and Scholes, 1978). Higher non-debt tax shields indicate less debt (DeAngelo and Masulis, 1980). Higher distress or business disruption costs suggest that equity is more important than debt for a firm to survive. Agency problems also call for more or less debt. Too much equity can result in free cash flows and potential conflicts of interest between corporate managers and shareholders (Jensen, 1986). Too much debt can lead to asset substitution and conflicts of interest between managers and bondholders (Fama and Miller, 1972; Jensen and Meckling, 1976). Leland (1994) and Leland and Toft (1996) derive an equilibrium model of optimal capital structure that weighs a reasonable trade-off between interest tax shields and business disruption costs. To the extent that the costs and benefits of debt usage offset one another, the corporation faces an optimal mix of debt and equity in accordance with shareholder wealth maximization.

The key testable prediction of the trade-off theory is that capital structure fully or partially adjusts toward some target leverage ratio. The empirical evidence thus far offers polemic views of this capital structure puzzle with large heterogeneity in the speed of partial adjustment toward an unobservable target mix of debt and equity (e.g. Fama and French (2002, 2005), Flannery and Rangan (2006), Antoniou, Guney, and Paudyal (2008), Lemmon, Roberts, and Zender (2008), and Huang and Ritter (2009)). The crux of this issue is that the estimates of target leverage convergence speed are quite sensitive to the variation in the econometric methodology. As a result, this issue remains a major puzzle in the capital structure literature.

In the pecking order theory of Myers (1984) and Myers and Majluf (1984), there is no optimal capital structure. If there is an optimum, the cost of deviating from this optimum is insignificant in comparison to the cost of raising external finance. Raising external finance is costly because corporate managers have better information about the firm’s recent prospects. Due to this information asymmetry, outside investors rationally discount the firm’s stock price when the firm issues equity in lieu of debt. To avoid this discount, corporate managers view equity as the last resort. This rationale suggests that each firm follows a pecking order of capital structure. The Myers-Majluf firm uses up internal funds first, then uses up debt, and finally resorts to equity. In the absence of profitable investment opportunities, the firm retains profits and builds up financial slack to avoid having to raise external finance in the future. A firm raises debt to finance its investment opportunities if there are insufficient internal funds to support these opportunities. Following the pecking order, a firm adjusts the debt ratio due to the need for external funds, but not because of an attempt to reach an optimal mix of debt and equity (Myers, 1984; Myers and Majluf, 1984; Shyam-Sunder and Myers, 1999).

Shyam-Sunder and Myers (1999) conduct the first empirical test of the pecking order theory against the static trade-off theory. The econometrician regresses the variation in the debt-to-assets ratio on the funds-flow deficit and the deviation of debt-to-assets from the target capital structure, which can be quantified as the firm’s moving average debt ratio or the industry average debt ratio. The pecking order coefficient turns out to be higher than the target adjustment coefficient by an order of magnitude (i.e. β=0.73>γ=0.15). This model captures most of the variation in the debt-to-assets ratio (R2=0.76). Shyam-Sunder and Myers (1999) interpret this evidence as empirical support for the pecking order theory of capital structure.

Frank and Goyal (2003) offer an alternative view of the horse race between the trade-off theory and the pecking order theory. Contrary to the pecking order theory, net equity issuance tracks the financing deficit more closely than does net debt issuance. While large corporations exhibit some aspects of pecking order behavior, the evidence is not robust to the inclusion of conventional explanatory factors such as changes in asset tangibility, market-to-book, sales as a proxy for firm size, and profitability (Rajan and Zingales, 1995). Specifically, Frank and Goyal (2003) report that Shyam-Sunder and Myers’s (1999) evidence is quite sensitive to changes in both sample selection and factor design. When the panel regression model includes the above explanatory factors (Rajan and Zingales, 1995), the pecking order coefficient sharply declines to β<0.25 for large firms and β<0.05 for small firms. Therefore, the pecking order phenomenon exists primarily among large firms and is not as robust as Shyam-Sunder and Myers (1999) suggest. The contradictory evidence points to an empirical void that both the static trade-off and pecking order theories cannot fill in practice.

Fama and French (2002) establish some empirical regularities with respect to the trade-off and pecking order theories of capital structure. While the joint predictions of these theories attract supportive evidence, the Fama-MacBeth cross-sectional regression tests shed skeptical light on the issues that reflect disagree-ment between these theories. For better exposition, the bullet points below sum up the joint predictions:

Firms with more investment opportunities have lower book or market leverage.
There is a positive relationship between firm size and financial leverage.
There is a negative relationship between target dividend payout and financial leverage.

Fama and French (2002) design a set of Fama-MacBeth leverage regressions to distinguish the trade-off and pecking order models. The framework is a standard partial adjustment model in which the change in book or market leverage partially absorbs the difference between target leverage and past leverage.

The leverage gap moves in response to the target leverage gap at the speed of adjustment per year with firm characteristics such as current and past corporate income and investment. The initial target leverage regression takes into account the joint effect of fundamental firm attributes such as firm size, stock market valuation, investment, profitability, and dividend payout. The econometrician then uses the fitted values of target leverage from this first-stage cross-sectional regression as a useful proxy for target leverage in the second-stage cross-sectional regression.

Controlling for investment opportunities, the trade-off model predicts that profitable firms can afford to have higher book or market leverage. Fama and French (2002) find a significantly negative relationship between profitability and leverage. This evidence contradicts the trade-off model but supports the pecking order theory. On the other hand, Fama and French (2002) report a significantly positive link between the target and future leverage gaps. This evidence suggests the existence of an optimal debt ratio in stark contrast to the pecking order theory. However, the mean reversion of leverage is 7%-10% per year for dividend payers and 15%-18% per year for dividend non-payers. This slow speed of partial adjustment toward target leverage bolsters the trade-off model or the dynamic pecking order model with a soft target leverage ratio.

Contradicting the central predictions of the pecking order model, Fama and French (2005) find that net equity issues are commonplace (i.e. equity is not a last resort). From 1973 to 1982, 54% of the U.S. firms make net equity issues each year, and this proportion rises to 62% for 1983 to 1992 and 72% for 1993 to 2002. Because equity issues are so pervasive, most firms that issue equity are not under financial duress. On average, equity issues are material. Among small firms with high growth potential, net equity issues are on average larger than net debt issues. However, the equity issuance process is lumpy and therefore results in a right-skewed distribution of stock issues. One story for the above results is that the pecking order model breaks down at least in part because there are many ways for firms to issue equity with low transaction costs and modest information asymmetries (Fama and French, 2005). In fact, any forces that lead to equity issuance not as a last resort invalidate the pecking order model.

Overall, Fama and French (2002, 2005) empirically find that both the trade-off and pecking order models have serious problems. It is probably time to stop running horse races between these competing models as standalone stories of capital structure. Perhaps it would be better to view these models as stable mates, and each has some elements of truth that help explain some aspects of corporate financing decisions.

In the dynamic version of the pecking order theory, high-growth firms reduce leverage in order to avoid raising equity as investment opportunities arise in the future (Myers, 1984). Baker and Wurgler (2002) report empirical results that are difficult to reconcile with this interpretation. Past values of market-to-book serve as important determinants of financial leverage. On this basis, Baker and Wurgler (2002: 27) assert that capital structure evolves as the cumulative outcome of past attempts to time the stock market. Corporate managers tend to recommend stock issuance when they believe the cost of equity is irrationally low. Conversely, corporate managers tend to recommend stock repurchase when they believe the cost of equity is irrationally high. This market timing theory of capital structure rests upon the behavioral basis of extreme or irrational investor expectations (La Porta, 1996; La Porta, Lakonishok, Shleifer, and Vishny, 1997; Frankel and Lee, 1998; Shleifer, 2000). If corporate managers attempt to exploit extreme investor expectations, net equity issuance should be positively related to the market-to-book ratio. In the absence of an optimal capital structure, corporate managers need not reverse their leverage decisions when the firm seems to be correctly valued and the cost of equity appears to be normal. The persistence of cumulative capital structure decisions leaves transient fluctuations in the market-to-book ratio with permanent effects on financial leverage. The market timing theory accords with Graham and Harvey’s (2001) anonymous survey that many CFOs admit to trying to time the stock market through net equity or debt issuance.

Baker and Wurgler (2002) find that the market timing coefficient is significantly negative up to 10 years after the IPO. An alternative measure of market-to-book, the external-finance-weighted-average market-to-book ratio, can be incorporated as an explanatory factor that increases for corporations whose recent past equity issuance tends to be high at the time of high stock market-to-book and vice versa. The evidence suggests that the market timing coefficient is significantly negative in almost all of the above Fama-MacBeth regressions. Baker and Wurgler (2002) estimate that the half-life of convergence toward target capital structure is well over 10 years. This persistence lends credence to the market timing theory that may serve as a plausible substitute for the trade-off and pecking order theories.

We build, design, and delve into our new and non-obvious proprietary algorithmic system for smart asset return prediction and fintech network platform automation. Unlike our fintech rivals and competitors who chose to keep their proprietary algorithms in a black box, we open the black box by providing the free and complete disclosure of our U.S. fintech patent publication. In this rare unique fashion, we help stock market investors ferret out informative alpha stock signals in order to enrich their own stock market investment portfolios. With no need to crunch data over an extensive period of time, our freemium members pick and choose their own alpha stock signals for profitable investment opportunities in the U.S. stock market.

With U.S. patent accreditation and protection for 20 years, our AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors.

Smart investors can consult our proprietary alpha stock signals to ferret out rare opportunities for transient stock market undervaluation. Our analytic reports help many stock market investors better understand global macro trends in trade, finance, technology, and so forth. Most investors can combine our proprietary alpha stock signals with broader and deeper macrofinancial knowledge to win in the stock market.

Through our proprietary alpha stock signals and personal finance tools, we can help stock market investors achieve their near-term and longer-term financial goals. High-quality stock market investment decisions can help investors attain the near-term goals of buying a smartphone, a car, a house, good health care, and many more. Also, these high-quality stock market investment decisions can further help investors attain the longer-term goals of saving for travel, passive income, retirement, self-employment, and college education for children. Our AYA fintech network platform empowers stock market investors through better social integration, education, and technology.

Capital structure theory and practice - Blog - AYA fintech network platform provides proprietary alpha stock signals and personal finance tools for stock market investors.

Capital structure theory and practice

https://ayafintech.network/blog/capital-structure-theory-and-practice/

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