Do relative leverage and relative distress really explain size and book-to-market anomalies?

In a capital asset pricing model (CAPM) framework, Ferguson and Shockley [2003. Equilibrium “anomalies”. Journal of Finance 58, 2549–2580] propose two factors constructed on relative leverage and relative distress, and show that the two factors subsume Fama and French's [1993. Common risk factors in the returns on stocks and bonds. Journal of Financial Economics 33, 3–56] factors constructed on size and book-to-market (BM) in explaining the cross-sectional average returns of the 25 size-BM portfolios. Based on tests on individual securities, we find that all factors fail to fully explain the common asset-pricing anomalies. In the spirit of Merton's [1973. An intertemporal capital asset pricing model. Econometrica 41, 867–887] intertemporal CAPM, we propose an augmented five-factor model, which incorporates Ferguson and Shockley's [2003. Equilibrium “anomalies”. Journal of Finance 58, 2549–2580] factors into the Fama–French three-factor model. The empirical results show that a simple conditional version of the augmented model is able to explain most well-known asset-pricing anomalies.     

Modeling the cross-section of stock returns using sensible models in a model pool

An increase in the number of asset pricing models intensifies model uncertainties in asset pricing. While a pure “model selection” (singling out a best model) can result in a loss of useful information, a full “model pooling” may increase the risk of including noisy information. We make a trade-off between the two methods and develop a new two-step trimming-then-pooling method to forecast the joint distributions of asset returns using a large pool of asset pricing models. Our method allows investors to focus on certain regions of the distributions. In the first step, we trim the uninformative models from a pool of candidates, and in the second step, we pool the forecasts of the surviving models. We find that our method significantly enhances portfolio performance and predicts downside risk precisely, and the improvements are mainly due to trimming. The pool of sensible models becomes larger when focusing on extreme events, responds rapidly to rising uncertainty, and reflects the magnitude of factor premiums. These findings provide new insights into asset pricing model evaluation.     

Some Results in the Theory of Arbitrage Pricing

This paper derives a stronger version of Huberman's recent “preference free” pricing theorem. This pricing result relates the expected return on an asset to its factor responses and the covariance structure of the residuals from a linear factor model. It must characterize any infinite asset economy in which no arbitrage opportunities are present whether or not the factor model has uncorrelated residuals. This result provides the intuition for the role of residual risk in the pricing model and eliminates some classes of arbitrage opportunities still present under Huberman's bound. Some applications to empirical tests and performance measurement are also discussed.     

The Analytics of the Intervaling Effect on Skewness and Kurtosis of Stock Returns

This paper analyzes how the skewness and kurtosis of securities' returns are affected by the length of the differencing interval over which returns are measured. Hawawini's previous analysis of this “intervaling effect” on log returns is shown to be incorrect, and the correct effects are derived. While Hawawini only considered log returns, we also derived the intervaling effect on the skewness and kurtosis of “simple” returns. Our results show that the length of differencing interval has very different effects on log and simple returns, but in both cases the effects on the returns' skewness and kurtosis are substantial and also quite tractable. These results also enable us to reconcile some of the contradictory results published earlier on the intervaling effect.     

Pension benefits, wealth accumulation, and capital market equilibrium: a life cycle hypothesis-based dynamic model

This paper examines the impacts of pension benefits on capital asset pricing in conjunction with wealth accumulation and retirement, and derives and tests a dynamic capital asset pricing model (CAPM) within the framework of a life cycle hypothesis-based dynamic model. The life cycle hypothesis-based dynamic model maximizes the expected utility of the individual's lifetime wealth in a continuous time process. An optimal solution of the individual's wealth path, incorporating the ages of retirement and death, is obtained and, based on the optimal wealth path, an analysis of comparative dynamics is pursued. The dynamic CAPM is then derived from the optimal wealth path; simulation and nonparametric tests are undertaken to evaluate the performance of the dynamic CAPM as compared to the traditional model which does not consider the impacts of pension benefits and the static model that incorporates the effects of pension benefits. The test results suggest that the proposed dynamic CAPM closely states the expected rate of return for a capital asset; that the new dynamic CAPM is preferable over the static model that is preferable over the traditional model; and that the three models considered are statistically distinguishable from one another.     

Technological Growth and Asset Pricing

We study the asset‐pricing implications of technological growth in a model with “small,” disembodied productivity shocks and “large,” infrequent technological innovations, which are embodied into new capital vintages. The technological‐adoption process leads to endogenous cycles in output and asset valuations. This process can help explain stylized asset‐valuation patterns around major technological innovations. More importantly, it can help provide a unified, investment‐based theory for numerous well‐documented facts related to excess‐return predictability. To illustrate the distinguishing features of our theory, we highlight novel implications pertaining to the joint time‐series properties of consumption and excess returns.     

Changes in Expected Security Returns,Risk, and the Level of Interest Rates

Regressions of security returns on treasury bill rates provide insight about the behavior of risk in rational asset pricing models. The information in one-month bill rates implies time variation in the conditional covariances of portfolios of stocks and fixed-income securities with benchmark pricing variables, over extended samples and within five-year subperiods. There is evidence of changes in conditional “betas” associated with interest rates. Consumption and stock market data are examined as proxies for marginal utility, in a general framework for asset pricing with time-varying conditional covariances.     

Prospect theory and a manager's decision to trade a blind principal bid basket

We analyze asset managers' decisions to execute substantial baskets of stocks. Such transactions can be executed in two ways. The first method is through blind auctions with unique features known as blind principal bids (BPBs). The manager learns the trading cost once the auction process determines the commission. The second method is to use an agency trade. In this case, the asset manager faces an actual trading cost that is unknown before execution due to market impact uncertainty. Using proprietary data, we investigate the manager's choice between BPBs and agency trade in a natural experiment with large monetary stakes. The volume traded in each sample basket is significant, which can amount to over 0.5% of the NYSE daily share volume. Our findings show that managers' behavior is more consistent with prospect theory than the expected utility framework. When asset managers trade BPB baskets, they are reluctant to realize the potential higher cost of agency trade and opt for the fixed cost of BPBs instead. Thus, our results complement the literature on the disposition effect by demonstrating that managers' trading cost decisions exhibit “play it safe” behavior.     

Consumption Externality and Equilibrium Underinsurance

Relative consumption has been found to be crucial in many areas, such as asset pricing, the design of taxation, and economic growth. This article extends this line of research to the individual's insurance decision. We first define “keeping up with the Joneses” in the purchase of insurance and find that jealousy does not necessarily give rise to “keeping up with the Joneses.” We also identify several sufficient conditions that cause the optimal coverage in the private market to be less than the social optimum (equilibrium underinsurance). Jealousy is found to be neither a sufficient nor a necessary condition for equilibrium underinsurance. We further show that a social welfare maximizing government could adopt a tax system to correct for the consumption externality and make individuals better off.     

It takes a model to beat a model: Volatility bounds

Models like the CAPM and Fama–French three-factor models are commonly used as benchmarks for calculating cost of capital and evaluating portfolio performance, despite the empirical evidence to reject them. For many practical purposes, “it takes a model to beat a model.” In this paper we derive restrictions on models that could “beat” a bench-mark model but might still be misspecified. In these “takes-a-model-to-beat-a-model” (TMBM) bounds, model A beats model B if model A's quadratic form of pricing errors is smaller. The bounds generalize the Hansen–Jagannathan bound and distance measure. We use the TMBM bounds to evaluate various linear factor models and consumption-based models. The failure of the power utility model is much less extreme when it is compared with the CAPM and Fama–French model. For reasonable utility curvature, the Ferson–Constantinides model and Epstein–Zin model perform best among the consumption-based models, beating the model of Campbell and Cochrane, in which model the value of the persistence parameter that matches the time-series properties of aggregate stock market returns seems too low for cross-sectional asset pricing.     

THE NEGLECTED AND SMALL FIRM EFFECTS

This paper addresses the empirical question of whether the differential attention which companies receive affects the capital asset pricing process. The degree of attention was measured by research concentration rankings based on the number of analysts regularly following the firm's securities. The results suggest: (i) that there is a “neglected firm effect” in terms of superior performance for less researched companies and (ii) that the neglected firm effect persists over and above the small firm effect; namely, the excess returns are not fully attributable to size. The ex-post capital asset pricing model is unable to account for the differences in return across security research ranking. Several possible explanations for the results are considered but not tested.     

A Look Back at Modern Finance: Accomplishments and Limitations

In a conversation held in June 2016 between Nobel laureate Eugene Fama of the University of Chicago and Joel Stern, chairman and CEO of Stern Value Management, Professor Fama revisited some of the landmarks of “modern finance,” a movement that was launched in the early 1960s at Chicago and other leading business schools, and that gave rise to Efficient Markets Theory, the Modigliani‐Miller “irrelevance” propositions, and the Capital Asset Pricing Model. These concepts and models are still taught at prestigious business schools, whose graduates continue to make use of them in corporations and investment firms throughout the world. But while acknowledging the staying power of “modern finance,” Fama also notes that, even after a half‐century of research and refinements, most asset‐pricing models have failed empirically. Estimating something as apparently simple as the cost of capital remains fraught with difficulty. He dismisses betas for individual stocks as “garbage,” and even industry betas are said to be unstable, “too dynamic through time.” What's more, the wide range of estimates for the market risk premium—anywhere from 2% to 10%—casts doubt on their reliability and practical usefulness. And as if to reaffirm the fundamental insight of the M&M “irrelevance” propositions—namely, that what companies do with the right‐hand sides of their balance sheets “doesn't matter”—Fama observes that “we still have no real resolution on the key questions of debt and taxes, or dividends and taxes.” But if he has reservations about much of modern finance, Professor Fama is even more skeptical about subfields now in vogue such as behavioral finance, which he describes as “mostly just dredging for anomalies,” with no underlying theory and no testable predictions. Although he does not dispute that a number of well‐documented traits from cognitive psychology show up in individual behavior, Fama says that behavioral economists have thus far failed to come up with a testable theory that links cognitive psychology to market prices. And he continues to defend the concept of “efficient markets” with which his name has long been closely associated, while noting that empirically based asset pricing models such as his (with Ken French) “three‐factor” CAPM have produced much better results than the standard CAPM.     

Non-monotonic pricing kernel and an extended class of mixture of distributions for option pricing

We derive closed form European option pricing formulae under the general equilibrium framework for underlying assets that have an \(N\) -mixture of transformed normal distributions. The component distributions need not belong to the same class but must all be transformed normal. An important implication of our results is that the mixture of distributions is consistent with a “what appears to be abnormal” non-monotonic (asset specific) pricing kernel for the S&P 500 and that the representative agent has a “logical” monotonic decreasing marginal utility. We show that a mixture of two lognormal distributions is sufficient to produce this result and also implied volatility smiles of a wide variety of shapes.     

Risky asset pricing based on safety first fund management

We study a portfolio selection model based on Kataoka's safety-first criterion (KSF model in short). We assume that the market is complete but without risk-free asset, and that the returns are jointly elliptically distributed. With these assumptions, we provide an explicit analytical optimal solution for the KSF model and obtain some geometrical properties of the efficient frontier in the plane of probability risk degree z _α and target return r _α. We further prove a two-fund separation and tangency portfolio theorem in the spirit of the traditional mean-variance analysis. We also establish a risky asset pricing model based on risky funds that is similar to Black's zero-beta capital asset pricing model (CAPM, for short). Moreover, we simplify our risky asset pricing model using a derivative risky fund as a reference for market evaluation.     

CARE/CEASA Roundtable on Managing Uncertainty and Risk

Two distinguished Morgan Stanley “alumni” discuss how their management of risk and uncertainty has not only preserved but increased the profitability of their businesses. In both cases—one involving a commodities trading operation and the other a long‐short hedge fund—the key has been to find cost‐effective ways to “cut off the left tails” of the distribution by avoiding naked long or short positions and creating option‐like payoffs with limited downside. In the case of the hedge fund, the combination of longs and shorts with the use of other risk‐reducing strategies has enabled the fund's managers to produce twice the market's returns with only half the volatility (and only one losing year) during the 18‐year life of the fund. In the case of the commodities trading operation, the strategy is described as combining ownership of physical assets with the use of option pricing models to create what amount to “long gamma positions in the asset” that “produce payoffs regardless of whether the asset goes up or down in value.”     

Deposit Insurance and the Discount Window: Pricing under Asymmetric Information

The risk-sensitive pricing of deposit insurance and the discount window is determined in an environment where banks have private information concerning their financial conditions. The two facilities are managed jointly; an incentive-compatible policy is designed such that banks' choice of terms at which they can obtain insurance and access to discount window credit will reveal their asset quality. The function of the discount window is to be a risk-neutral “lender of last resort” to banks in a market dominated by risk-averse depositors.     

BORROWING RELATIONSHIPS,MONITORING, AND THE INFLUENCE ON LOAN RATES

While monitoring borrowers, a bank obtains private information about its customers, giving the bank an informational advantage in the production of subsequent services. Competing theories exist on the way banks use this advantage in the pricing of subsequent services to the customer. If moral hazard limits the transfer of private information, the borrowing relationship transforms into an informational monopoly and can be characterized as a “wasting asset.” Alternately, if the banks' competitive environment necessitates that cost economies are shared, the relationship has “value.” Ordering pairs of successive loans made to a particular borrower as prior loans and subsequent loans, and controlling for environmental, borrower, and loan characteristics, we show that the subsequent loan is priced significantly lower than the prior loan.     

Concentrated commonalities and systemic risk in China's banking system: A contagion network approach

China's banking system has seen increasing convergence in exposures to different asset types. These concentrated commonalities have far reaching implications on systemic financial risk. Based on the commonality structure of banks' balance sheets, we construct a bipartite financial network and design novel indicators to analyze the systemic risk of China's banking system and its relation to the real economy. Results show that (1) considering the interconnectivity, indirect loss arising from common exposure is much higher than direct loss; (2) concentrated common exposure to mortgage is demonstrated to be the most significant source of systemic vulnerability in China; (3) the derived contagion network shows the property of “small world”, which plays an important role in generating systemic risk, amplified non-linearly by multi-rounds of contagion; (4) a bank's systemic importance/vulnerability depends on complex interaction between asset volume, leverage rate, and its commonality of asset composition to other banks. The model proposed in this study provides a new structural perspective to investigate the systemic risk, and a macroprudential instrument to complement existing stress testing that contributes to more efficient and precise regulations. Moreover, we contribute a ranking framework to assess each bank's systemic importance as well as vulnerability corresponding to specific real sectors.     

Explaining abnormal returns in stock markets: An alpha-neutral version of the CAPM

This paper develops a behavioural asset pricing model in which traders are not fully rational as is commonly assumed in the literature. The model derived is underpinned by the notion that agents’ preferences are affected by their degree of optimism or pessimism regarding future market states. It is characterized by a representation consistent with the Capital Asset Pricing Model, augmented by a behavioural bias that yields a simple and intuitive economic explanation of the abnormal returns typically left unexplained by benchmark models. The results we provide show how the factor introduced is able to absorb the “abnormal” returns that are not captured by the traditional CAPM, thereby reducing the pricing errors in the asset pricing model to statistical insignificance.