The Mispricing Return Premium

The Mispricing Return Premium

I. INTRODUCTION The consumption-based capital asset pricing model (CCAPM) has become the dominant paradigm in asset pricing theory because of its intuitive characterization of asset risk. That is, unlike expectations-based asset pricing theories (e.g. the present value model of stock prices) which inherently assume risk neutrality, the CCAPM is predicated upon risk-averse agents attempting to achieve a smooth consumption profile through the trading of assets. From this perspective, the risk of an asset is captured by the covariance of the asset's return with agents' marginal utility of consumption, or, more broadly, agents' intertemporal marginal rate of substitution of wealth. With this characterization, the CCAPM extends the results of the standard CAPM, i.e. the risk of an asset is reflected in the covariance of the asset's return with the market portfolio, to a general equilibrium setting. However, this intuitively appealing theory has not found much empirical support. Perhaps the most famous demonstration of inconsistency between the theory and data was Rajnish Mehra and Edward Prescott's [1985] analysis of the equity premium, i.e. the difference between the average return on equity and that on government bonds. Using calibration methods rather than a formal statistical approach, they showed that a standard CCAPM severely underpredicts the size of the risk premium on equity. The important implication of this finding is that the basic CCAPM incorrectly models the covariance structure between the return on equity and asset holders' intertemporal marginal rate of substitution. Economists' response to this empirical rejection has been to either identify new sources of risk (e.g., that implied by a particular monetary environment as in Labadie [1989]) or define alternative preferences toward risk (e.g., the use of non-expected utility theory as presented in Weil [1989] and Epstein and Zin [1989]). The potential for this research was illustrated recently by George Constantinides's [1990] resolution of the equity premium puzzle in a model that included habit formation in consumption. By relaxing the standard CCAPM's assumption of time-separable preferences, Constantinides demonstrated that a relatively smooth consumption profile and large risk premium on equity are consistent with equilibrium in a complete markets, rational-expectations framework.(1) I use this insight to study another risk premium puzzle; specifically the behavior of the nominal term premium. The existence of a nominal term premium puzzle was demonstrated in papers by Backus, Gregory, and Zin [1989] and Salyer [1990] in which the term structure implications within a Lucas [1982] type cash-in-advance (CIA) economy were studied. While some equilibrium characteristics of this model were consistent with the data, both papers demonstrated that the model predicts the wrong sign of the term premium: the theory implies the term premium should be negative while, based on quarterly data for yields of three- and six-month U.S. Treasury Bills over the period 1959.1-1989.4, the observed term premium is positive. Similar to the equity premium puzzle as posed by Mehra and Prescott [1985], the prediction of a negative average term premium signals a critical discrepancy between the risk associated with nominal bonds as perceived by market participants and as captured by the models. Moreover, this term premium puzzle is in some sense a stronger rejection of the underlying asset pricing model than that embodied by the equity premium puzzle. To see this, recall that within the consumption-based asset pricing model, the sign of the risk premium on any asset depends on the sign of the covariance between the marginal utility of consumption and that asset's return. Applying this reasoning to the case of the equity premium suggests that, while the discrepancy in size between the observed equity premium and that generated within the model is troubling, the model's prediction of a positive equity premium implies that the basic payout structure of equity within the model is consistent with that in the data (e. …

The asset pricing model has been a core area of research in finance due to its applicability in corporate finance and security analysis. The present study attempted to evaluate the three popular asset pricing models viz., the capital asset pricing model, the Fama-French three-factor model, and the Fama-French five-factor model in the Indian equity market for the period of January 2009 to November 2018. The study also examined the role of the size, profitability, value, investment, and market factors in explaining the average equity returns in the Indian equity market. The empirical results reveal the inferior performance of a single market factor in describing the variations in average stock returns in comparison with the Fama-French three-factor model and the Fama-French five-factor model. Further, the size and value factors added to CAPM yield a vital melioration in explaining the variation in average returns of sample stocks.

We propose a dynamic equilibrium model of asset prices and trading volume with heterogeneous agents fixed transactions costs. We show that even small fixed costs can give rise to large no-trade regions for each agent's optimal trading policy and a significant illiquidity discount in asset prices. We perform a calibration exercise to illustrate the empirical relevance of our model for aggregate data. Our model also has implications for the dynamics of order flow, bid/ask spreads, market depth, the allocation of trading costs between buyers and sellers, and other aspects of market microstructure, including a square-root power law between trading volume and fixed costs which we confirm using historical US stock market data from 1993 to 1997.

Incentive compatible financial contracts, asset prices, and the value of control

Most single-factor and multifactor asset pricing models constitute special cases of the consumption-based asset pricing theory, in which investors’ marginal utility is the key determinant of asset prices. However, in recent years, production-based asset pricing models have been extraordinarily successful in correctly pricing a wide range of anomaly portfolios that are typically mispriced in previous research. In parallel, research on conditioning information has contributed to significantly improve the performance of classic consumption-based asset pricing models. On this basis, in this paper we conduct an in-depth research on the performance of consumption and production-based asset pricing models on the Tokyo Stock Exchange, for the period from 1992 to 2018, in order to test to what extent consumer confidence helps consumption models to correctly capture shifts in the investment opportunity set of investors. To overcome the constraints imposed by the periodicity of macroeconomic data, we use a factor-mimicking portfolio approach that allows us to test the performance of the models into consideration at different frequencies. Our results suggest that the consumer confidence index for Japan helps consumption-based asset pricing models outperform production-based models for different anomaly portfolios. Conversely, in those cases where consumption models perform worse, the production models also perform poorly. These results help to partially reconcile the results provided by the consumption and production models, and constitute a step forward for the purpose of identifying the fundamental risk factors that drive asset prices.

The specification of the stochastic process for stock prices is an important assumption underlying most equilibrium and option-pricing models in modern finance. This is particularly true of the continuous-time capital asset pricing models where it is assumed that asset prices follow diffusion processes with continuous sample paths (see Merton 1973a; Breeden 1979; Grossman and Shiller 1982). The extent to which the implications of these models generalize to discontinuous sample paths is an unanswered question in theoretical finance. However, the answer to this question is of more than just theoretical interest since accumulated empirical evidence appears to be inconsistent with the continuous sample path assumption (see Rosenberg 1972; Oldfield, Rogalski, and Jarrow 1977; Rosenfeld 1982). One purpose of this paper is to provide some answers to this question. We do this by extending Merton's (1973a) intertemporal asset pricing model, in the special case of a constant investment opportunity set, to include discontinuous sample paths for asset prices. The constant investment opportunity set assumption is imposed because we are interested in obtaining sufficient conditions under which an instantaneous capital asset pricing model (CAPM) results. The extension of our model to a stochastic opportunity set is discussed briefly in the text. This paper investigates an economy where stock prices follow a jump-diffusion process. The first part of the analysis derives a sufficient condition under which an instantaneous CAPM will characterize equilibrium expected returns. The sufficient condition is that the jump component of a stock's return must be unsystematic and diversifiable in the market portfolio. The second part of the paper is an empirical investigation of the satisfaction of this condition. The evidence is seen to be inconsistent with the satisfaction of this hypothesis, that is, the market portfolio appears to contain a jump component.

A Temporary Equilibrium Model of Asset Pricing

In his seminal paper Samuelson (1965) argues that in an informationally efficient market — not to be confused with an allocationally or Pareto-efficient market — price changes must be unforecastable if they are properly anticipated. Prices follow a random walk and fully incorporate the information and expectations of all market participants. Fama's (1970a) dictum that "prices fully reflect all available information" has become a holy grail among the academic community and triggered virtually hundreds of empirical investigations on market efficiency since then. However, in the late 1980s several studies reported deviations of stock returns behavior from the random walk. Poterba/Summers (1988) and Fama/French (1988a) find significant negative autocorrelation in both real and excess long-horizon returns, while Lo/MacKinlay (1988) detect positive autocorrelation for weekly holding-period returns. The empirical evidence throughout this book has shown that stock returns are predictable to some extent on the basis of global instrument variables. It has been argued in chapter 4 that expected returns vary with the business cycle, and that appropriate instrument variables should be indicators for recent and/or future real activity. Similar to the previous literature, the results in chapter 5 strongly suggested that the time variation of economic risk premiums can explain a considerable fraction of the observed stock return predictability. This chapter attempts to put many things together into a unifying framework. Throughout this book it has been argued that predictability is far from being a symptom of inefficiency or irrationality. Now the focus is explicitly on the underlying economic forces in a general equilibrium model of asset pricing, namely reversion in the stochastic discount factor and consumption smoothing. Specifically, this chapter proposes a model in the spirit of LeRoy (1973) and Lucas (1978) to explain mean reversion and, hence stock return predictability in a consumption-based framework. The goal is to demonstrate empirically that the random walk hypothesis is neither a necessary nor a sufficient condition for rationally determined asset prices. In fact, unforecastable prices do not necessarily imply a well-functioning financial market with rational investors, and forecastable prices need not imply the opposite. While the original version of the efficient market hypothesis implicitly assumes constant expected returns, this is inappropriate because it does not account for time variation in risk.KeywordsBusiness CycleStock ReturnAsset PriceExcess ReturnConsumption GrowthThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Asset Pricing with Return Extrapolation

This thesis consists of three empirical studies on what drives stock market dynamics. The first empirical study explores the effect of crude oil price changes on the stock market returns of oil-exporting countries and oil-importing countries as well as those of a number of global stock indices. Using the Ordinary Least Squares (OLS) approach as well as the more robust Quantile Regression (QR) approach to explore the relationship between crude oil and stock market dynamics. The empirical findings suggest that the QR approach provides further insights compared to the OLS approach. For instance, the QR approach is able to identify specific quantiles where a significant relation exists. In particular crude oil price increases tend to have a negative impact on the stock market returns for some oil-exporting countries (such as Mexico, Iraq, Ecuador, and Venezuela) and a positive effect for other oil-exporting countries (such as Brazil and Algeria). However, the OLS approach suggests that these relationships are insignificant at the level of the mean. Overall, the empirical findings confirm that the QR approach can reveal more information about the relationship between crude oil price changes and stock market return across different quantiles of their distribution.The second study explores the extent to which implied volatility extracted from commodity markets and developed stock markets can predict the implied volatility of stock markets in BRICS countries. Using daily data from 2011 to 2016 and employing the newly developed Bayesian Graphical Vector Autoregressive (BGVAR) model of Ahelegbey et al. (2016) which does not suffer from over-parameterization and the identification problems associated with traditional VAR frameworks, this study finds that implied volatilities extracted from global and regional stock markets have a significant predictive power over the implied volatilities in BRICS stock markets. However, the predictive power of implied volatility from commodity markets are significant only in the case of South Africa.The third empirical study analyses the relationship between illiquidity and stock market returns in the G7 and BRICS countries. More specifically, this study explore the extent to which the Amihud (2002) illiquidity measure can improve the explanatory power of three commonly used asset pricing models, namely the Capital Asset Pricing Model (CAPM), the Fama-French three-factor model and the Carhart four-factor model. The empirical analysis is based on 15 years of monthly data on the returns of seven stock portfolios: 100 largest companies (Largest100), small value (S/V), small neutral (S/N), small growth (S/G) stocks, big value (B/V) stocks, big neutral (B/N) stocks, and big growth (B/G) stocks. The findings suggest that incorporating illiquidity as an additional factor results in a significant improvement in the explanatory power of these asset pricing models across several of the sample countries (8 countries in the case of the CAPM and Carhart four-factor model, and 6 countries in the case of the Fama-French three-factor model). For example, in the US adding illiquidity to the CAPM leads to an increase of the goodness of fit by 2.6% in the B/V portfolio, and for the Fama-French three-factor model the goodness of fit increases by up to 3% in all portfolios Moreover, the goodness of fit increases in all portfolios in the US by adding illiquidity to the Carhart four-factor model, with an up to 36% increase in the B/N portfolio.

This study experimentally investigates whether shareholders correctly anticipate the incentive effects of increasingly complex compensation packages given to managers, and whether potential biases in individual shareholder beliefs carry over to price and volume effects in a stock market. In the experiment, a manager makes a decision about the stochastic dividend process generating the firm's fundamental value, and shareholders make estimations about fundamental value and trade shares in a stock market. The manager's action is either known or hidden and, nested in the hidden-action condition, compensation is either simple or complex. We hypothesise that hidden action gives rise to perceived behavioural uncertainty, and that this uncertainty has valuation relevance in that it affects both individual estimations of fundamental firm value and stock prices. Furthermore, we hypothesise that perceived behavioural uncertainty increases with the complexity of compensation, and that compensation complexity also affects trading volume. We find supporting evidence for our conjectures. Both estimations and market prices are biased when the manager's action is hidden, and biases are stronger when compensation is complex. We further find that trading volume decreases when compensation is complex, even though the heterogeneity of investors' individual beliefs increases.

Since Sharpe (1964) derived the CAPM, it has been the benchmark of asset pricing models and has been used to calculate the cost of equity capital and other asset pricing determinations for more than four decades. Many researchers have tried to relax the original assumptions and generalize the static CAPM. In addition, Merton (1973) and Black (1976) have generalized the static CAPM in terms of intertemporal CAPM. In this chapter, we survey the important alternative theoretical models of capital asset pricing and provide a complete review of the evolution of both static and intertemporal asset pricing models. We also discuss the interrelationships among these models and suggest several possible directions for future research. In addition, we review the asset pricing tests in terms of individual companies’ data instead of portfolio data. Our results might be used as a guideline for future theoretical and empirical research in capital asset pricing.

A general equilibrium asset pricing model for a monetary economy with capital accumulation, fin and endogenous financial structure is constructed in which there is a meaningful between monetary policy, inflation taxes, investment decisions and private financial arrangements. A differential stochastic liquidity premium applies in equilibrium to consumption and investment purchases. A production version of the capital asset pricing model is constructed. The presence of endogenous financial arrangements is shown to play a key role in explaining potential distortions in the equilibrium risk premia associated with technological uncertainty. Numerical work indicates (1) that return anomalies are potentially large, and (2) that the model has implications for empirical implementations for the partial equilibrium, production-based asset pricing models such as Cochrane (1991,1996) and Braun (1993). Copyright 1996 by The London School of Economics and Political Science.

HOUSING PRICES HAVE risen by about 50 percent in the past five years, and more than 100 percent in some hot markets. Many knowledgeable observers believe that the United States is in the midst of a speculative bubble in residential real estate prices that rivals the dot-com bubble of the 1990s and that will have a similarly unhappy conclusion. In December 2004 UCLA Anderson Forecast's Economic Outlook described the California housing market as a bubble, repeating their warnings made in previous years. Robert Shiller has issued similar alarms for several years and, in June 2005, warned that, [housing] market is in the throes of a bubble of unprecedented proportions that probably will end ugly. (1) Shiller suggests that real housing prices might fall by 50 percent over the next decade. In August 2005 Paul Krugman argued that there was definitely a housing bubble on the coasts and that, indeed, the air had already begun leaking out. (2) Evidence of a housing bubble has been suggestive but indirect, in that it does not address the key question of whether housing prices are justified by the value of the services provided by a home. We first show how to estimate the fundamental value of a home from rent data. We then use this procedure to estimate the fundamental value of homes in ten urban housing markets using a unique set of rent and sale price data for matched single-family homes. Our evidence indicates that, even though prices have risen rapidly and some buyers have unrealistic expectations of continuing price increases, the bubble is not, in fact, a bubble in most of these areas: under a variety of plausible assumptions about fundamentals, buying a home at current market prices still appears to be an attractive long-term investment. Our results also demonstrate that models that gauge a housing bubble by comparing movements in housing price indexes with movements in other indexes or with the values predicted by regression models are flawed, because they assume that market prices fluctuate randomly around fundamental values. Those models must assume that prices were close to fundamentals in the past in order to conclude that the 2001-05 run-up pushed prices above fundamentals. But maybe prices were below fundamentals in the past and the 2001-05 run-up pushed prices closer to fundamentals. Defining a Bubble Charles Kindleberger defined a bubble this way: a sharp rise in price of an asset or a range of assets in a continuous process, with the initial rise generating expectations of further rises and attracting new buyers--generally speculators interested in profits from trading in the asset rather than its use or earning capacity. The rise is usually followed by a reversal of expectations and a sharp decline in price often resulting in financial crisis. (3) Researchers often focus on a single specific aspect of this general concept: rapidly rising prices, (4) unrealistic expectations of future price increases, (5) the departure of prices from fundamental value, (6) or a large drop in prices after the bubble pops. (7) Shiller and Karl Case write that, A tendency to view housing as an investment is a defining characteristic of a housing bubble. (8) To the contrary, we believe that housing is an investment and that the correct way to gauge a bubble is to compare actual home prices with the value of homes as an investment calculated from fundamentals (and that one of the main sources of mispricing in the housing market is that almost none of the participants estimate the fundamental value of their home). We define a bubble as a situation in which the market prices of certain assets (such as stocks or real estate) rise far above the present value of the anticipated cash flow from the asset (what Kindleberger called the asset's use or earning capacity). This definition suggests many of the features noted above: prices rising rapidly, a speculative focus on future price increases rather than the asset's cash flow, and an eventual drop in prices. …