Testing conditional asset pricing models: An emerging market perspective

The CAPM as the benchmark asset pricing model generally performs poorly in both developed and emerging markets. We investigate whether allowing the model parameters to vary improves the performance of the CAPM and the Fama–French model. Conditional asset pricing models scaled by conditioning variables such as Trading Volume and Dividend Yield generally result in small pricing errors. However, a graphical analysis reveals that the predictions of conditional models are generally upward biased. We demonstrate that the bias in prediction may be the consequence of ignoring frequent large variation in asset returns caused by volatile institutional, political and macroeconomic conditions. This is characterised by excess kurtosis. An unconditional Fama–French model augmented with a cubic market factor performs the best among some competing models when local risk factors are employed. Moreover, the conditional models with global risk factors scaled by global conditioning variables perform better than the unconditional models with global risk factors.     

Testing asset pricing models with changing expectations and an unobservable market portfolio

When the assumption of constant risk premiums is relaxed, financial valuation models may be tested, and risk measures estimated without specifying a market index or state variables. This is accomplished by examining the behavior of conditional expected returns. The approach is developed using a single risk premium asset pricing model as an example and then extended to models with multiple risk premiums. The methodology is illustrated using daily return data on the common stocks of the Dow Jones 30. The tests indicate that these returns are consistent with a single, time-varying risk premium.     

Econometric evaluation of asset pricing models

In this article we provide econometric tools for the evaluationof intertemporal asset pricing models using specification-errorand volatility bounds. We formulate analog estimators of thesebounds, give conditions for consistency, and derive the limitingdistribution of these estimators. The analysis incorporatesmarket frictions such as short-sale constraints and proportionaltransactions costs. Among several applications we show how touse the methods to assess specific asset pricing models andto provide non-parametric characterizations of asset pricinganomalies.     

Time preference and capital asset pricing models

Results of the theory of individual optimal consumption-investment choice under uncertainty are extended to a class of intertemporally dependent preferences for consumption streams. These results are then used to show that with intertemporally dependent preferences, which are more realistic than the separable time-additive preference structure, Merton's (1973) multi-beta intertemporal capital asset pricing model is still valid, but it can no longer be collapsed to Breeden's (1979) single consumption-beta model.     

Inference in asset pricing models with a low-variance factor

This paper concerns with the effects of including a low-variance factor in an asset pricing model. When a low-variance factor is present, the commonly applied Fama–MacBeth two-pass regression procedure is very likely to yield misleading results. Local asymptotic analysis and simulation evidence indicate that the risk premiums corresponding to all factors are very likely to be unreliably estimated. Moreover, t- and F-statistics are less likely to detect whether the risk premiums are significantly different from zero. We recommend Kleibergen’s (2009)FAR statistic when there is a low-variance factor included in an asset pricing model.     

Specification tests of asset pricing models using excess returns

In this paper, we discuss the impact of different formulations of asset pricing models on the outcome of specification tests that are performed using excess returns. We point out that the popular way of specifying the stochastic discount factor (SDF) as a linear function of the factors is problematic because (1) the specification test statistic is not invariant to an affine transformation of the factors, and (2) the SDFs of competing models can have very different means. In contrast, an alternative specification that defines the SDF as a linear function of the de-meaned factors is free from these two problems and is more appropriate for model comparison. In addition, we suggest that a modification of the traditional Hansen–Jagannathan distance (HJ-distance) is needed when we use the de-meaned factors. The modified HJ-distance uses the inverse of the covariance matrix (instead of the second moment matrix) of excess returns as the weighting matrix to aggregate pricing errors. Asymptotic distributions of the modified HJ-distance and of the traditional HJ-distance based on the de-meaned SDF under correctly specified and misspecified models are provided. Finally, we propose a simple methodology for computing the standard errors of the estimated SDF parameters that are robust to model misspecification. We show that failure to take model misspecification into account is likely to understate the standard errors of the estimates of the SDF parameters and lead us to erroneously conclude that certain factors are priced.     

Consumption-based capital asset pricing models: issues and controversies

This paper discusses the issues and controversies surrounding consumption-based capital asset pricing models (CCAPMs). While CCAPMs provide a chance to explain the phenomena observed in stock markets, their viability is jeopardized owing to the weak predictability of the equity premium and risk-free rate puzzles. Even given market frictions and market incompleteness, CCAPMs must test their validity constantly in the face of the formidable challenges of rival models. Measurement error with respect to time aggregation is also regarded as a major threat, causing the low volatility of consumption and eventually resulting in chaining itself to weak return predictability. In addition, the dual choice problem of portfolio and consumption rooted in CCAPMs guides us into how investors accumulate wealth through the financial market to reach the zenith of expected utility. This paper offers insights as well as understanding into the behavior of an agent and market phenomena in the context of a consumption-based economy.     

The restrictions on predictability implied by rational asset pricing models

This article shows how rational asset pricing models restrictthe regression-based criteria commonly used to measure returnpredictability. Specifically it invokes no-arbitrage argumentsto show that the intercept, slope coefficients, and R² in predictiveregressions must take specific values. These restrictions providea way to directly assess whether the predictability uncoveredusing regression analysis is consistent with rational pricing.Empirical tests reveal that the returns on the CRSP size decilesare too predictable to be compatible with a number of well-knownpricing models. However, the overall pattern of predictabilityacross these portfolios is reasonably consistent with what wewould expect under circumstances where predictability is rational.     

Evaluation of linear asset pricing models by implied portfolio performance

We present a theoretical perspective that motivates the use of the Generalized Least Squares R-Square, prominently advocated by Lewellen et al. [Lewellen, J., Nagel, S., Shanken, J., forthcoming. A skeptical appraisal of asset-pricing tests. Journal of Financial Economics], as an evaluation measure for multivariate linear asset pricing models. Adapting results from Shanken [Shanken, J., 1985. Multivariate tests of the zero-beta CAPM. Journal of Financial Economics 14, 327–348] and Kandel and Stambaugh [Kandel, S., Stambaugh, R.F., 1995. Portfolio inefficiency and the cross-section of expected returns. Journal of Finance 50, 157–184], we provide various interpretations and a graphical account in mean-variance space of this measure, facilitating a better understanding of its properties. We furthermore relate it to another leading evaluation metric, the HJ-distance of Hansen and Jagannathan [Hansen, L.P., Jagannathan, R., 1997. Assessing specification errors in stochastic discount factor models. Journal of Finance 52, 557–590]. Additionally, we present a comparison between these evaluation measures using mean-variance mathematics in risk-return space, and we provide a simple formula for calculating both model evaluation measures that involves only the parameters of the mean-variance asset and factor frontiers.     

Measuring portfolio performance and the empirical content of asset pricing models

Recent work by Richard Roll has challenged the worth of portfolio performance measures based on the capital asset pricing model. This paper demonstrates that Roll's conclusions are due to his focusing on a ‘truly’ ex-ante efficient index. Using a choice and information theoretic framework, we show that an appropriate index is efficient relative to the probabilities assessed by the ‘market’. Residual analyses and portfolio performance tests, using such an index, yield meaningful results for a wide class of information structures. Roll's primary criticisms, however, relate to tests of the asset pricing model itself. We argue that these criticisms are vastly overstated.     

The unintended consequences of grouping in tests of asset pricing models

We identify a number of unintended consequences of grouping when the capital asset pricing model is true and when it is false. When the model is true, grouping may cause fundamental problems with the most basic capital asset pricing and cross-sectional regression relationships. For example, with traditional grouping, the market portfolio is super-efficient––unless securities in each group are value weighted. Yet, when the model is grossly false, grouping may cause the model to appear to be absolutely correct. Ironically, the only way this can occur is when securities in each group are value weighted. To make matters worse, when the model is false, the slope of a cross-sectional regression of expected returns on betas fitted to grouped data may be either steeper or flatter than when the regression is fitted to ungrouped data. In other words, grouping may exacerbate the very problem it was meant to alleviate.     

Corporate sustainability in asset pricing models and mutual funds performance measurement

This study explores whether corporate sustainability is a relevant factor in multifactor asset pricing models. It contributes to the literature on asset pricing, as well as to the literature that examines how sustainability impacts capital markets, by constructing a new factor that captures differences in the returns of sustainable and non-sustainable firms. Specifically, it examines whether an additional sustainability factor has explanatory power in asset pricing models that include size, book-to-market equity, and momentum factors. This research has practical implications for the performance measurement of portfolios and mutual funds that are managed in accordance with sustainability criteria in that it disentangles general stock-picking skills from the differences in returns between sustainable and non-sustainable stocks.     

Conditional coskewness and asset pricing

We explore the empirical usefulness of conditional coskewness to explain the cross-section of equity returns. We find that coskewness is an important determinant of the returns to equity, and that the pricing relationship varies through time. In particular we find that when the conditional market skewness is positive investors are willing to sacrifice 7.87% annually per unit of gamma (a standardized measure of coskewness risk) while they only demand a premium of 1.80% when the market is negatively skewed. A similar picture emerges from the coskewness factor of Harvey and Siddique (Harvey, C., Siddique, A., 2000a. Conditional skewness in asset pricing models tests. Journal of Finance 65, 1263–1295.) (a portfolio that is long stocks with small coskewness with the market and short high coskewness stocks) which earns 5.00% annually when the market is positively skewed but only 2.81% when the market is negatively skewed. The conditional two-moment CAPM and a conditional Fama and French (Fama, E., French, K., 1992. The cross-section of expected returns. Journal of Finance 47,427465.) three-factor model are rejected, but a model which includes coskewness is not rejected by the data. The model also passes a structural break test which many existing asset pricing models fail.     

Information and capital asset pricing

Investors in a market frequently update their diverse perceptions of the values of risky assets, thus invalidating the classic capital asset pricing model's (CAPM) assumption of complete agreement among investors. To accommodate information asymmetry and belief updating, we have developed an empirically testable information-adjusted CAPM, which states that the expected excess return of a risky asset/portfolio is solely determined by the information-adjusted beta rather than the market beta. The model is then used to analyze empirical anomalies of the classic CAPM, including a flatter relation between average return and the market beta than the CAPM predicts, a non-zero Jensen's alpha, insignificant explanatory power of the market beta, and size effect.     

Intertemporal asset pricing with bitcoin

Review of Quantitative Finance and Accounting - This paper develops and tests an intertemporal regime-switching asset pricing model characterized by heterogeneous agents that have different...     

An empirical investigation of asset pricing models under divergent lending and borrowing rates

Asset pricing theory implies that the estimate of the zero-beta rate should fall between divergent lending and borrowing rates. This paper proposes a formal test of this restriction using the difference between the prime loan rate and the 1-month Treasury bill rate as a proxy for the difference between borrowing and lending rates. Based on simulations, this paper shows that in the ordinary least squares case, the Fama and MacBeth (J Pol Econ 81:607–636, 1973) t-statistic has high power against a general alternative, which is not true of the Shanken (Rev Financ Stud 5:1–33, 1992) and Kan et al. (J Financ doi:10.1111/jofi.12035, 2013) t-statistics. In the generalized least squares case, all three t-statistics have high power. The empirical investigation highlights that only the intertemporal capital asset pricing model reasonably prices the zero-beta portfolio. Other models, such as the Fama and French (J Financ Econ 33:3–56, 1993) model, do not assign the correct value to the zero-beta rate.     

The role of data limitations,seasonality and frequency in asset pricing models

We demonstrate that the estimates of the Capital Asset Pricing Model (CAPM) parameters significantly differ across samples, which are based on different days of the week (representing different seasons). Our evidence suggests that the “noise” in the data is not an issue. We also show that parameter differences for mixed samples, which contain information on different seasons, are too small to distort statistical analysis. This is so because parameter estimates converge to some values (but not necessarily to the true values) for high frequencies or as the sample size becomes large. Our evidence suggests a possibility that the CAPM may hold empirically if seasonality in the parameters of the population model are taken into consideration.     

Housing,consumption and asset pricing

This paper considers a consumption-based asset pricing model where housing is explicitly modeled both as an asset and as a consumption good. Nonseparable preferences describe households’ concern with composition risk, that is, fluctuations in the relative share of housing in their consumption basket. Since the housing share moves slowly, a concern with composition risk induces low frequency movements in stock prices that are not driven by news about cash flow. Moreover, the model predicts that the housing share can be used to forecast excess returns on stocks. We document that this indeed true in the data. The presence of composition risk also implies that the riskless rate is low which further helps the model improve on the standard CCAPM.