Asset Pricing - A Brief Review

I first introduce the early-stage and modern classical asset pricing and portfolio theories. These include: the capital asset pricing model (CAPM), the arbitrage pricing theory (APT), the consumption capital asset pricing model (CCAPM), the intertemporal capital asset pricing model (ICAPM), and some other important modern concepts and techniques. Finally, I discuss the most recent development during the last decade and the outlook in the field of asset pricing.Asset Pricing Models

A survey on risk-return analysis

This paper provides a review of the main features of asset pricing models. The review includes single-factor and multifactor models, extended forms of the Capital Asset Pricing Model with higher order co- moments, and asset pricing models conditional on time-varying volatility.Asset pricing, CAPM

Prices and Portfolio Choices in Financial Markets: Theory, Econometrics, Experiments

Many tests of asset-pricing models address only the pricing predictions, but these pricing predictions rest on portfolio choice predictions that seem obviously wrong. This paper suggests a new approach to asset pricing and portfolio choices based on unobserved heterogeneity. This approach yields the standard pricing conclusions of classical models but is consistent with very different portfolio choices. Novel econometric tests link the price and portfolio predictions and take into account the general equilibrium effects of sample-size bias. This paper works through the approach in detail for the case of the classical capital asset pricing model (CAPM), producing a model called CAPM+ε. When these econometric tests are applied to data generated by large-scale laboratory asset markets that reveal both prices and portfolio choices, CAPM+εis not rejected

Why Are Asset Returns Predictable?

Starting from an information process governed by a geometric Brownian motion we show that asset returns are predictable if the elasticity of the pricing kernel is not constant. Declining [Increasing] elasticity of the pricing kernel leads to mean reversion and negatively autocorrelated asset returns [mean aversion and positively autocorrelated asset returns]. Under nonconstant elasticity of the pricing kernel financial ratios as the price-earnings ratio have predictive power for future asset returns. In addition, it is shown that asset prices will be governed by a time-homogeneous stochastic differential equation only under the constant elasticity pricing kernel. Hence, usually asset price processes do not satisfy the assumptions needed for empirical estimation. --Pricing kernel,Diffusion processes,Stationarity,Predictability of asset returns,Autocorrelation

Incomplete Diversification and Asset Pricing

Investors in equilibrium are modeled as facing investor specific risks across the space of assets. Personalized asset pricing models reflect these risks. Averaging across the pool of investors we obtain a market asset pricing model that reflects market risk exposures. It is observed on invoking a law of large numbers applied to an infinite population of investors, that many personally relevant risk considerations can be eliminated from the market asset pricing model. Examples illustrating the effects of undiversified labor income and taste specific price indices are provided. Suggestions for future work on asset pricing include a need to focus on identifying and explaining investor specific risk exposures.Diversification, Asset Pricing, Investor specific risks

Small Firm Effect, Liquidity and Security Returns: Australian Evidence

Standard asset pricing models ignore the costs of liquidity. In this study we advance the ongoing debate on empirical asset pricing and test if liquidity costs (as proxied by turnover rate, turnover ratio and bid-ask spread) affect stock returns for Australian stocks. Our tests use the factor portfolio mimicking approach of Fama and French (1993, 1996). We find small and less liquid firms generate positive risk premia after controlling for market returns and firm size. We find no evidence of any seasonal effects that can explain our multifactor asset pricing model findings. In summary, our study provides support for a broader asset-pricing model with multiple risk factors.Liquidity, Turnover, Asset Pricing, and Closing Bid-Ask Spread

Asset Pricing Theories, Models, and Tests

An important but still partially unanswered question in the investment field is why different assets earn substantially different returns on average. Financial economists have typically addressed this question in the context of theoretically or empirically motivated asset pricing models. Since many of the proposed “risk” theories are plausible, a common practice in the literature is to take the models to the data and perform “horse races” among competing asset pricing specifications. A “good” asset pricing model should produce small pricing (expected return) errors on a set of test assets and should deliver reasonable estimates of the underlying market and economic risk premia. This chapter provides an up-to-date review of the statistical methods that are typically used to estimate, evaluate, and compare competing asset pricing models. The analysis also highlights several pitfalls in the current econometric practice and offers suggestions for improving empirical tests

Asset Pricing Under Information with Stochastic Volatility

Based on a general specification of the asset specific pricing kernel, we develop a pricing model using an information process with stochastic volatility. We derive analytical asset and option pricing formulas. The asset prices in this rational expectations model exhibit crash-like, strong downward movements. The resulting option pricing formula is consistent with the strong negative skewness and high levels of kurtosis observed in empirical studies. Furthermore, we determine credit spreads in a simple structural model.

Do Heterogeneous Beliefs Matter for Asset Pricing?

We study how heterogeneous beliefs affect returns and examine whether heterogeneous beliefs are a priced factor in traditional asset pricing models. To accomplish this task, we suggest new empirical measures based on the disagreement among analysts about expected (short-term and long-term) earnings are good proxies. Having established that heterogeneity of beliefs matters for asset pricing we turn our attention to estimating a structural model in which we use the forecasts of financial analysts to proxy for the beliefs of agents. Finally, we investigate if the amount of heterogeneity in analysts' forecasts can help explain asset pricing puzzlesHeterogeneous Beliefs, Asset pricing