Multifactor Models Do No Explain Deviations From The Capm

A number of studies have presented evidence rejecting the validity of the Capital Asset Pricing Model (CAPM). This evidence has spawned research into possible explanations. These explanations can be divided into two main categories-- the risk-based alternatives and the nonrisk-based alternatives. The risk-based category includes multifactor asset pricing models developed under the assumptions of investor rationality and perfect capital markets. The nonrisk-based category includes biases introduced in the empirical methodology, the existence of market frictions, or explanations arising from the presence of irrational investors. The distinction between the two categories is important for asset pricing applications such as estimation of the cost of capital. This paper proposes to distinguish between the two categories using ex ante analysis. A framework is developed showing that ex ante one should expect that CAPM deviations due to missing risk factors will be very difficult to empirically detect. In contrast, deviations resulting from nonrisk-based sources will be easy to detect. Examination of empirical results leads to the conclusion that the risk-based alternatives is not the whole story for the CAPM deviations. The implication of this conclusion is that the adoption of empirically developed multifactor asset pricing models may be premature.

A number of studies have presented evidence rejecting the validity of the Capital Asset Pricing Model (CAPM). This evidence has spawned research into possible explanations. These explanations can be divided into two main categories - the risk based alternatives and the nonrisk based alternatives. The risk based category includes multifactor asset pricing models developed under the assumptions of investor rationality and perfect capital markets. The nonrisk based category includes biases introduced in the empirical methodology, the existence of market frictions, or explanations arising from the presence of irrational investors. The distinction between the two categories is important for asset pricing applications such as estimation of the cost of capital. This paper proposes to distinguish between the two categories using ex ante analysis. A framework is developed showing that ex ante one should expect that CAPM deviations due to missing risk factors will be very difficult to statistically detect. In contrast, deviations resulting from nonrisk based sources will be easy to detect. Examination of empirical results leads to the conclusion that the risk based alternatives is not the whole story for the CAPM deviations. The implication of this conclusion is that the adoption of empirically developed multifactor asset pricing models may be premature.

For over half a century, financial experts have regarded the movements of markets as a random walk--unpredictable meanderings akin to a drunkard's unsteady gait--and this hypothesis has become a cornerstone of modern financial economics and many investment strategies. Here Andrew W. Lo and A. Craig MacKinlay put the Random Walk Hypothesis to the test. In this volume, which elegantly integrates their most important articles, Lo and MacKinlay find that markets are not completely random after all, and that predictable components do exist in recent stock and bond returns. Their book provides a state-of-the-art account of the techniques for detecting predictabilities and evaluating their statistical and economic significance, and offers a tantalizing glimpse into the financial technologies of the future. The articles track the exciting course of Lo and MacKinlay's research on the predictability of stock prices from their early work on rejecting random walks in short-horizon returns to their analysis of long-term memory in stock market prices. A particular highlight is their now-famous inquiry into the pitfalls of "data-snooping biases" that have arisen from the widespread use of the same historical databases for discovering anomalies and developing seemingly profitable investment strategies. This book invites scholars to reconsider the Random Walk Hypothesis, and, by carefully documenting the presence of predictable components in the stock market, also directs investment professionals toward superior long-term investment returns through disciplined active investment management.

This book analyzes the emerging asset class of digital assets. When a new asset class originates, researchers try to understand some basic questions: Can digital assets, with the flagship asset bitcoin, really be considered a serious asset class? Since it is possible to trade digital assets, does it make sense to trade or to invest in these assets? How do digital assets compare to traditional asset classes like equities or bonds? After describing basic financial theory and breaking down the digital asset universe, this book provides fundamental knowledge with respect to this young and rising asset class. It focuses on special issues like the application of technical indicators, investment styles, asset pricing and portfolio construction. Furthermore, it offers remarks and links to other traditional asset classes and describes and warns of data issues in digital asset data.

This book relates to strategic asset allocation for institutional investors. It consists of a collection of edited papers from academics worldwide on the latest developments in asset allocation, portfolio management and international investments. These expert studies can improve the risk and return characteristics of your investment portfolio.

This book proposes a new capital asset pricing model dubbed the ZCAPM that outperforms other popular models in empirical tests using US stock returns. The ZCAPM is derived from Fischer Black’s well-known zero-beta CAPM, itself a more general form of the famous capital asset pricing model (CAPM) by 1990 Nobel Laureate William Sharpe and others. It is widely accepted that the CAPM has failed in its theoretical relation between market beta risk and average stock returns, as numerous studies have shown that it does not work in the real world with empirical stock return data. The upshot of the CAPM’s failure is that many new factors have been proposed by researchers. However, the number of factors proposed by authors has steadily increased into the hundreds over the past three decades. This new ZCAPM is a path-breaking asset pricing model that is shown to outperform popular models currently in practice in finance across different test assets and time periods. Since asset pricing is central to the field of finance, it can be broadly employed across many areas, including investment analysis, cost of equity analyses, valuation, corporate decision making, pension portfolio management, etc. The ZCAPM represents a revolution in finance that proves the CAPM as conceived by Sharpe and others is alive and well in a new form, and will certainly be of interest to academics, researchers, students, and professionals of finance, investing, and economics.