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Several features of financial research make it particularly prone to the occurrence of false discoveries. First, the probability of finding a positive (profitable investment strategy) is very low, due to intense competition. Second, true findings are mostly short-lived, as a result of the non-stationary nature of financial systems. Third, unlike in the natural sciences, it is rarely possible to verify statistical findings through controlled experiments. Finance’s inability to conduct controlled experiments makes it virtually impossible to debunk a false claim. One would hope that, in such a field, researchers would be particularly careful when conducting statistical inference. Sadly, the opposite is true.Tenure-seeking researchers publish thousands of academic articles that promote dubious investment strategies, without controlling for multiple testing. Some of those articles are written for, funded, or promoted by investment firms with a commercial interest. As a consequence, today’s academic finance exhibits some resemblance with medicine’s predicament during the 1950-2000 period, when Big Tobacco paid for thousands of studies in support of their bottom line. Unlike finance, medical journals today impose strict controls for multiple testing. Academic finance’s denial of its replication crisis risks its branding as a pseudoscience.

Have you ever felt miserable because of a sudden whipsaw in the price that triggered an unfortunate trade? In an attempt to remove this noise, technical analysts have used various types of moving averages (simple, exponential, adaptive one or using Nyquist criterion). These tools may have performed decently but we show in this paper that this can be improved dramatically thanks to the optimal filtering theory of Kalman filters (KF). We explain the basic concepts of KF and its optimum criterion. We provide a pseudo code for this new technical indicator that demystifies its complexity. We show that this new smoothing device can be used to better forecast price moves as lag is reduced. We provide 4 Kalman filter models and their performance on the SP500 mini-future contract. Results are quite illustrative of the efficiency of KF models with better net performance achieved by the KF model combining smoothing and extremum position.

This is an introduction to a five-volume collection of papers on financial econometrics to be published by Edward Elgar Publishers in 2007. Financial econometrics is one of the fastest growing branches of economics today, both in academia and in industry. The increasing sophistication of financial models requires equally sophisticated methods for their empirical implementation, and in recent years financial econometricians have stepped up to the challenge. The toolkit of financial econometrics has grown in size and depth, including techniques such as nonparametric estimation, functional central limit theory, nonlinear time-series models, artificial neural networks, and Markov Chain Monte Carlo methods. In these five volumes, the most influential papers of financial econometrics have been collected, spanning four decades and five distinct subfields: statistical models of asset returns (Volume I), static asset-pricing models (Volume II), dynamic asset-pricing models (Volume III), continuous-time methods and market microstructure (Volume IV), and statistical methods and non-standard finance (Volume V). Within each volume, different strands of the literature are weaved together to form a rich and coherent historical perspective on empirical and methodological breakthroughs in financial markets, while covering the major themes of financial econometrics.

Two random variables are associated when knowing the value of one helps us determine the value of the other. This should not me confounded with the notion of causality.Correlation is the best known measure of association in econometric studies. Despite its popularity among economists, correlation has many known limitations in the context of financial studies.In this seminar we will explore more modern measures of association, based on information theory, which overcome some of the limitations of correlations.

Using hundreds of significant anomalies as testing portfolios, this paper compares the performance of major empirical asset pricing models. The q-factor model and a closely related five-factor model are the two best performing models among a long array of models. The q-factor model outperforms the five-factor model in factor spanning tests and in explaining momentum and profitability anomalies, but the five-factor model has an edge in explaining value-versus-growth anomalies. Investment and profitability, not liquidity, are the key driving forces in the broad cross section of expected stock returns.

The Lightning Network (LN) is a means of netting Bitcoin payments outside the blockchain. We find a significant association between LN adoption and reduced blockchain congestion, suggesting that the LN has helped improve the efficiency of Bitcoin as a means of payment. This improvement cannot be explained by other factors, such as changes in demand or the adoption of SegWit. We find mixed evidence on whether increased centralization in the Lightning Network has improved its efficiency. Our findings have implications for the future of cryptocurrencies as a means of payment and their environmental footprint.

After reviewing the parametric and scenario-based approaches to risk management, we discuss a methodology to enhance the flexibility of the scenario-based approach. We change the probability of each scenario, and then we compute the ensuing p&l distribution and all relevant statistics such as VaR and volatility. The probabilities can be changed to reflect specific market conditions, advanced estimation techniques, or partial information, using the entropy-based Fully Flexible Views technique. The implementation of this approach is trivial, as no costly repricing is needed. Commented code is available at symmys.com.

Financial and investment professionals along with their clients reveal a wide array of psychological biases that can result in flawed judgments and decisions. Understanding these biases is important for these professionals to ensure their clients are receiving the best advice and information. The authors describe some common behavioral biases among financial planners, financial advisors, portfolio managers, financial analysts, and institutional investors. The article draws on some themes from the authors’ book Financial Behavior – Players, Services, Products, and Markets published by Oxford University Press in 2017.

This is a case study of the Bank of America and Merrill Lynch merger. It is based on the article, Fiduciary Exemption for Public Necessity: Shareholder Profit, Public Good, and the Hobson’s Choice during a National Crisis, 17 Geo. Mason L. Rev. 661 (2010). The case study analyzes the controversial events occurring between the merger signing and closing. It reviews in depth the circumstances under the federal government threatened to fire the board and management of Bank of America unless it consummated the Merrill Lynch acquisition. Among other issues, this case study raises the questions: (1) what is the role of a private firm during a public crisis? (2) what are the responsibilities of the board? (3) what is the role of government and how should it treat private firms? This case study can be used in corporate ethics classes in business schools, or business associations classes in law schools.

This paper reviews research regarding the role of financial analysts in capital markets. The paper builds on the perspectives provided by Schipper (1991) and Brown (1993). We categorize papers published mainly since 1992 and selectively discuss aspects of these papers that address or suggest key research topics of ongoing interest in seven broad areas: analysts' decision processes, the determinants of analyst expertise and distributions of individual analysts' forecasts, the informativeness of analysts' research outputs, analyst and market efficiency with respect to information, effects of analysts' economic incentives on their research outputs, effects of the institutional and regulatory environment (including cross-country comparisons), and the limitations of databases and various research paradigms.

We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns and study the realized moments' time-series and cross-sectional properties. We investigate if this week's realized moments are informative for the cross-section of next week's stock returns. We find a very strong negative relationship between realized skewness and next week's stock returns. A trading strategy that buys stocks in the lowest realized skewness decile and sells stocks in the highest realized skewness decile generates an average weekly return of 19 basis points with a t-statistic of 3.70. Our results on realized skewness are robust across a wide variety of implementations, sample periods, portfolio weightings, and firm characteristics, and are not captured by the Fama-French and Carhart factors. We find some evidence that the relationship between realized kurtosis and next week's stock returns is positive, but the evidence is not always robust and statistically significant. We do not find a strong relationship between realized volatility and next week's stock returns.

Horizontal shareholdings exist when a common set of investors own significant shares in corporations that are horizontal competitors in a product market. Economic models show that substantial horizontal shareholdings are likely to anticompetitively raise prices when the owned businesses compete in a concentrated market. Recent empirical work not only confirms this prediction, but also reveals that such horizontal shareholdings are omnipresent in our economy. I show that such horizontal shareholdings can help explain fundamental economic puzzles, including why corporate executives are rewarded for industry performance rather than individual corporate performance alone, why corporations have not used recent high profits to expand output and employment, and why economic inequality has risen in recent decades. I also show that stock acquisitions that create anticompetitive horizontal shareholdings are illegal under current antitrust law, and I recommend antitrust enforcement actions to undo them and their adverse economic effects.

We report strong evidence that changes of momentum, i.e. "acceleration", defined as the first difference of successive returns, provide better performance and higher explanatory power than momentum. The corresponding Γ-factor explains the momentum-sorted portfolios entirely but not the reverse. Thus, momentum can be considered an imperfect proxy for acceleration, and its success can be attributed to its correlation to the predominant Γ-factor. Γ-strategies based on the "acceleration" effect are on average profitable and beat momentum-based strategies in two out of three cases, for a large panel of parameterizations. The "acceleration" effect and the Γ-factor profit from transient non-sustainable accelerating (upward or downward) log-prices associated with positive feedback mechanisms.

The DRSK public model estimates forward-looking real-world default probabilities for publicly traded firms. The model also assigns credit grades based on the estimated default probabilities. The product covers firms in all regions and sectors of operation for which the necessary data is available.The DRSK public model was last updated in 2015. This year we are releasing an updated model which improves on the previous model's performance in a variety of ways. The new model's accuracy ratio is above 92%, adjusted pseudo R-squareds have improved, and performance is more in line with observed historical default rates. We describe the new model, analyze its performance in various ways and compare it to the previous model.

Due diligence is an important source of alpha in a well designed hedge fund portfolio strategy. It is generally understood that the high returns possible in investing in hedge funds are somewhat offset by the relative lack of transparency on operational issues. The performance of a diversified hedge fund portfolio can be enhanced by excluding those funds likely to do poorly - or fail - due to operational risk concerns. However, effective due diligence is an expensive concern. This implies that there is a strong competitive advantage to those funds of funds sufficiently large to absorb this fixed and necessary cost. The consequent economies of scale that we document in funds of funds are quite substantial and support the proposition that due diligence is a source of alpha in hedge fund investment.

We study how firm-level carbon emissions affect bank lending and, through this channel, real outcomes in a sample of global firms with syndicated loans. We use bank-level commitments to decarbonization to proxy for changes in banks’ green preferences and, via these commitments, shocks to firms with previous credit from these banks. Firms with higher carbon footprint previously borrowing from committed banks subsequently receive less bank credit. Affected firms also lower their total debt, leverage, size, and real investments, and increase their liquid assets. We find no improvement in environmental performance of brown firms, but only evidence consistent with firms’ greenwashing.

We establish that the risk-return tradeoff of cryptocurrencies (Bitcoin, Ripple, and Ethereum) is distinct from those of stocks, currencies, and precious metals. Cryptocurrencies have no exposure to most common stock market and macroeconomic factors or to the returns of currencies and commodities. In contrast, we show that the cryptocurrency returns can be predicted by factors which are specific to cryptocurrency markets – there is a strong time-series momentum effect and proxies for investor attention strongly forecast cryptocurrency returns. Finally, we create an index of exposures to cryptocurrencies of 354 industries in the US and 137 industries in China.

This article is a comprehensive exploration of why financial and nonfinancial firms engage in short-termism with particular attention given to the financial crisis of 2007-2009. Short-termism, which is also referred to as earnings management (or, alternatively, managerial myopia), consists of the excessive focus of corporate managers, asset managers, investors and analysts on short-term results, whether quarterly earnings or short-term portfolio returns, and a repudiation of concern for long-term value creation and the fundamental value of firms. This article examines market and internal firm dynamics that contribute to short-termism, which requires an examination of various structural, informational, behavioral and incentive problems operating within firms and markets. This article also discusses various regulatory responses to mitigate short-termism, including provisions of the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010. It is the objective of this article to seek changes that would improve our financial system and prevent a financial meltdown in the future, such as the financial crisis of 2007-2009 that has had such a devastating impact on the U.S. and global economies.

Computing incremental contribution of performance ratios like Sharpe, Treynor, Calmar or Sterling ratios is of paramount importance for asset managers. Leveraging Euler's homogeneous function theorem, we are able to prove that these performance ratios are indeed a linear combination of individual modified performance ratios. This allows not only deriving a condition for a new asset to provide incremental performance for the portfolio but also to identify the key drivers of these performance ratios. We provide various numerical examples of this performance ratio decomposition.

Although various income statement–based measures predict the cross section of stock returns, direct method cash flow measures have even stronger predictive power. We transform indirect method cash flow statements into disaggregated and more direct estimates of cash flows from operations and other sources and form portfolios on the basis of these measures. Stocks in the highest-cash-flow decile outperform those in the lowest by over 10% annually (risk adjusted). Our results are robust to investment horizons and across risk factors and sector controls. We also show that, in addition to operating cash flow information, cash taxes and capital expenditures provide incremental predictive power.

(Revised 4/29/15, with minor edits by Craig William French) Abstract by Craig William French This paper reprints a slightly edited version of Jack L. Treynor's 1961 CAPM manuscript, which has previously been unavailable to the public. The author's facsimile of the original was obtained thanks to the kind generosity of Mr. and Mrs. Treynor. Edits in the present version, which differ from the original, include minor typographical corrections and minor notation differences for some variables in the formulae. Pagination is as in the original. In 1958, Jack Treynor was employed by Arthur D. Little. That summer he took a three-week vacation to Evergreen, Colorado, during which he produced forty-four pages of mathematical notes on capital asset pricing and capital budgeting. Over the next two years, Treynor refined his notes into what is in all likelihood the first CAPM. Treynor gave a copy of this early model to John Lintner at Harvard in 1960. While in business school at Harvard from 1953 through 1955, Mr. Treynor had taken nearly every finance course offered, and though he signed up for Lintner’s economics course he was forced to cancel due to a schedule conflict. In 1960, John Lintner was the only economist he knew even slightly. Treynor refined his 1960 model into the 45-page “Market Value, Time, and Risk” [the present paper]. This paper, Treynor (1961), develops the CAPM using the concept of experiment space to quantify risk and risk relations. Without his knowledge or encouragement, one of Mr. Treynor’s colleagues sent the draft to Merton Miller in 1961, after Miller had moved to the University of Chicago from Carnegie Institute of Technology. Miller sent the paper to Franco Modigliani at MIT in the spring of 1962, and Modigliani invited Treynor to embark on a program of graduate work at MIT under his supervision. Treynor did so during the 1962-1963 academic year; in addition to Modigliani’s course, he took Bob Bishop’s price theory and Ed Kuh’s econometrics courses, among others. By the fall of 1962, Treynor had consolidated the first part of Treynor (1961), on the single-period model, into “Toward a Theory of Market Value of Risky Assets,” and presented it to the MIT finance faculty. A more complete description of the development of the Treynor CAPM may be found in French, Craig W., The Treynor Capital Asset Pricing Model. Journal of Investment Management, Vol. 1, No. 2, pp. 60-72, 2003. Available at SSRN: http://ssrn.com/abstract=447580. A reprint of Treynor's 1962 paper, “Toward a Theory of Market Value of Risky Assets,” may be found in French, Craig W., Jack Treynor's 'Toward a Theory of Market Value of Risky Assets' (December 28, 2002). Available at SSRN: http://ssrn.com/abstract=628187.

The current financial crisis that threatens the entire world has created an ideal opportunity for educators. A number of important lessons can be learned from this financial meltdown. Some are technical and deal with the value of mathematical models and measuring risk. The most important lesson, however, is that unethical behavior has many consequences. This debacle could not have occurred if the parties involved had been socially responsible and not motivated by greed. Conflicts of interest and the way CEOs are compensated are at the heart of this financial catastrophe that has wiped out trillions in assets and millions of jobs. The authors present a set of lessons as teaching opportunities for today's students and tomorrow's decision makers. [A modified version of this paper appeared as H.H. Friedman, L.W. Friedman, "Lessons from the Global Financial Meltdown of 2008," Journal of Financial Transformation, vol 28, 2010, pp.45-54.]

We model financial innovations such as Exchange-Traded Funds, smart beta products, and many index-based vehicles as composite securities that facilitate trading common factors in assets' liquidation values. Through accessing a larger basket of assets in endogenously-chosen proportions, composite securities can benefit both informed and liquidity traders and attract all factor investors with optimal designs that feature selecting liquid and representative assets. Consistent with empirical findings, introducing composite securities leads to higher price variability and co-movements, larger trading costs and synchronicity, and lower asset-specific but higher factor information in prices, especially for illiquid assets. Trading transparency, distinction between bundles and derivatives, and endogenous information acquisition also significantly affect prices and security design.

This paper uses recent experimental studies of financial accounting to illustrate our view of how such experiments can be conducted successfully. Rather than provide an exhaustive review of the literature, we focus on how particular examples illustrate successful use of experiments to determine how, when and (ultimately) why important features of financial accounting settings influence behavior. We first describe how changes in views of market efficiency, reliance on the experimentalist?s comparative advantage, new theories, and a focus on key institutional features have allowed researchers to overcome the criticisms of earlier financial accounting experiments. We then describe how specific streams of experimental financial accounting research have addressed questions about financial communication between managers, auditors, information intermediaries, and investors, and indicate how future research can extend those streams. We focus particularly on (1) how managers and auditors report information, (2) how users of financial information interpret those reports, (3) how individual decisions affect market behavior, and (4) how strategic interactions between information reporters and users can affect market outcomes. Our examples include and integrate experiments that fall into both the "behavioral" and "experimental economics" literatures in accounting. Finally, we discuss how experiments can be designed to be both effective and efficient.

The intuitive meaning of "beta" is well known to all risk and portfolio managers: the beta is the sensitivity of the return on a given asset to a given risk factor. The applications of the "beta" are manifold, from risk computation and analysis to hedging. However, the precise definition and computation of the beta is far from trivial.