Narrow Results

Theories deal with the world on its own terms, absolutely. Models are metaphors, relative descriptions of the object of their attention that compare it to something similar already better understood via theories. Models are reductions in dimensionality that always simplify and sweep dirt under the rug. Theories tell you what something is. Models tell you merely what something is partially like.

This paper examines the impact of status-seeking considerations on investors' portfolio choices and asset prices in a general equilibrium setting. The economy studied in this paper consists of traditional ("Markowitz") investors as well as status-seekers who are concerned about relative wealth. The model highlights the strategic and interdependent nature of portfolio selection in such a setting: Low-status investors look for portfolio choices that maximize their chances of moving up the ladder while high-status investors look to maintain the status quo and hedge against these choices of the low-status investors. In equilibrium, asset returns obey a novel two-factor model in which one factor is the traditional market factor and the other is a particular "high volatility factor" that does not appear to have been identified so far in the theoretical or empirical literature. This two-factor model found significant support when tested with stock market data. Of particular interest is that the model and the empirical results attribute the low returns on idiosyncratic volatility stocks to their covariance with the portfolio of highly volatile stocks held by investors with relatively low status.

This paper shows that the stylized fact of average mutual fund underperformance documented in the literature stems from expansion periods when funds have statistically significant negative risk-adjusted performance and not recession periods when risk-adjusted fund performance is positive. These results imply that traditional unconditional performance measures understate the value added by active mutual fund managers in recessions, when investors' marginal utility of wealth is high. The risk-adjusted performance (or alpha) difference between recession and expansion periods is statistically and economically significant at 3% to 5% per year. Our findings are based on a novel multi-variate conditional regime-switching performance methodology used to carry out one of the most comprehensive examinations of the performance of US domestic equity mutual funds in recessions and expansions from 1962 to 2005. The findings are robust to the choice of the factor model (including bond and liquidity factor extensions), the use of NBER business cycle dates, fund load, turnover, expenses and percentage of equity holdings.

This paper applies a state space approach to the analysis of stock return predictability. It acknowledges that expected returns and expected dividends are unobservable and uses the Kalman filter to extract them from the observed history of realized dividends and returns. The suggested approach explicitly takes into account the time variation in expected dividend growth rates and exploits the present value relation. The obtained predictors for future returns are robust to structural breaks in the means of expected dividends and returns and more efficient than the dividend–price ratio. The likelihood ratio test reliably rejects the hypothesis of constant expected returns.

We propose new multifactor models to explain the accruals anomaly. Our baseline model represents an application of Merton’s ICAPM in which the key factors represent (innovations on) the term and small-value spreads. The model shows large explanatory power for cross-sectional risking premia associated with three accruals portfolio groups. A scaled version of the model shows better performance, suggesting that accruals risk premia are related with the business cycle. Both models compare favorably with popular multifactor models used in the literature, and also perform well in pricing other important anomalies. The risk price estimates of the hedging factors are consistent with the ICAPM framework.

Due to the tightening of conditions required to obtain a mortgage loan following the recent financial crisis, the rent-to-own contract and contract for deed sales for residential real estate have become increasingly popular among potential home buyers and sellers. In this study, after analyzing the embedded options in the contracts, I use option-theoretic methods to develop models for valuing both contracts for deed sale and rent-to-own contracts, which can be used to determine equilibrium monthly payments and the equilibrium down payment.

This paper tests a multi-factor asset pricing model that does not assume that the return’s beta coefficients are constants. This is done by estimating the generalized arbitrage pricing theory (GAPT) using price differences. An implication of the GAPT is that when using price differences instead of returns, the beta coefficients are constant. We employ the adaptive multi-factor (AMF) model to test the GAPT utilizing a Groupwise Interpretable Basis Selection (GIBS) algorithm to identify the relevant factors from among all traded exchange-traded funds. We compare the performance of the AMF model with the Fama–French 5-factor (FF5) model. For nearly all time periods less than six years, the beta coefficients are time-invariant for the AMF model, but not for the FF5 model. This implies that the AMF model with a rolling window (such as five years) is more consistent with realized asset returns than is the FF5 model.

This paper develops an approximation to arbitrage-free bond yields in Gaussian shadow rate term structure models. In this class of models, yields are constrained to be above an effective lower bound, thus rendering standard bond pricing methods inapplicable. I propose approximating the nonlinear relationship between yields and state variables using moments of the censored normal distribution. In an empirical application, this approximation technique is accurate to within a fraction of a basis point. As I show, minimizing the yield approximation error is crucial for model estimation as even seemingly small errors can lead to economically meaningful inference biases.

This study examines whether there is a strong relationship between stock liquidity, which proxies for the implicit cost of trading shares, and future stock returns in an asset-pricing context in the UK stock market. The time period, 1994–2016, includes the most recent global financial crisis that drained liquidity from financial markets worldwide. Four different measures of stock liquidity are employed; the empirical findings indicate that liquidity is a systematic pricing factor and explains a significant portion of the variation in stock returns, even after the inclusion of the other traditional risk factors. The results are robust to both forms of liquidity, either as a residual effect or in its original form as a separate risk factor. Finally, for the first time quantile regression is applied, showing that the liquidity risk factor (LIQ) absorbs a significant portion of the information content of the size and value factors, while remaining independent of the momentum factor.