Published and Accepted Papers

[5] "A Tale of Two Market Returns: The Broad Market Factor and the Idiosyncratic Financial Factor" (with Sung Je Byun and Lawrence Schmidt)

We construct a Broad Market Factor (BMF), which is a proxy for the value-weighted equity return on all firms in the US economy (public and private). The BMF differs from the standard Value-weighted Market Factor (VMF), which reflects the valueweighted equity return on public firms. We define the difference between the VMF and the BMF to be the Idiosyncratic Financial Factor (IFF).  The IFF carries no risk premium and is uncorrelated with all macroeconomic proxies for investor marginal utility we consider. CAPM betas and, consequently, discount rates are underestimated when measured with respect to the VMF compared to the BMF for most portfolios. Size factors become redundant and the size anomaly is resolved when the VMF is replaced by the BMF in standard factor models. The intertemporal risk-return relation is substantially stronger when one replaces the VMF with the BMF. The unifying explanation for these results is that the IFF adds unpriced risk to the VMF, distorting both cross-sectional and time-series estimates of exposure to priced market risk.

[4] "An Intertemporal Risk Factor Model" (with Andrei Goncalves and Fousseni Chabi-Yo)

Prominent factor models are based on tradable factors that do not represent theoretically relevant risks. To address this issue, we develop a factor model that captures the risks to long-term investors present in the Intertemporal CAPM (ICAPM). Empirically, we construct intertemporal risk factors as long-short portfolios based on stock exposures to dividend yield and realized variance. These tradable factors mimic news to long-term expected returns and volatility, and they offset part of the marginal utility increase in recessions induced by wealth declines. Our intertemporal factor model estimation implies significant risk prices that are consistent with the ICAPM restrictions under moderate risk aversion. Moreover, our model performs well relative to previous factor models in terms of its tangency Sharpe ratio and its pricing of key test assets, including single stocks, industry portfolios, and portfolios sorted on risk exposures and lagged anomalies.

[3] "Stock Price Reactions to the Information and Bias in Analyst-Expected Returns"

I use a novel decomposition to estimate information and bias components from the returns implied by analyst price targets and provide evidence that prices simultaneously under-react to information and over-react to bias. Price reactions to information are permanent, and prices drift in the direction of their initial reaction for up to 12 months. Price reactions to bias are transitory, and prices reverse their initial reaction after about three months. Price reactions are relatively efficient. Approximately 85 percent of the total price reaction to information occurs during price target announcement months. Market participants are able to mostly (but not fully) debias analyst-expected returns before incorporating them into prices, with the announcement-month reaction to bias being relatively weak at about 15 percent of its reaction to information. A trading strategy analysis implies that mispricing induced by bias is only about one-third of that implied by prior research. 

[2] "A Decomposition of Conditional Risk Premia and Implications for Representative Agent Models" (with Fousseni Chabi-Yo)

We develop a methodology to decompose the conditional market risk premium and risk premia on higher-order moments of excess market returns into risk premia related to contingent claims on down, up, and moderate market returns. The decomposition exploits information about the risk-neutral market return distribution embedded in option prices but does not depend on assumptions about the functional form of investor preferences or about the market return distribution. The total market risk premium is highly time-varying, as are the contributions from downside, upside, and central risk. Time series variation in risk premia associated with each region is primarily driven by variation in risk prices associated with the probability of entering each region at short horizons, but it is primarily driven by variation in risk quantities at longer horizons. Analogous decompositions implied by prominent representative agent models generally fail to match the dynamic risk premium behavior implied by the data. Our results provide a set of new empirical facts regarding the drivers of conditional risk premia and identify new challenges for representative agent models.

[1] "The Conditional Expected Market Return" (with Fousseni Chabi-Yo)

We derive lower and upper bounds on the conditional expected excess market return that are related to risk-neutral volatility, skewness, and kurtosis indexes. The bounds can be calculated in real time using a cross section of option prices. The bounds require a no-arbitrage assumption, but do not depend on distributional assumptions about market returns or past observations. The bounds are highly volatile, positively skewed, and fat tailed. They imply that the term structure of expected excess holding period returns is decreasing during turbulent times and increasing during normal times, and that the expected excess market return is on average 5.2%.

We also derive closed-form expressions for any physical moment of the excess market return (e.g., mean, variance, skewness, kurtosis, etc.) when the functional form of the utility is specified. We provide closed-form expressions for the SDF obtained when a representative agent has CARA, CRRA, and HARA utilities. In these cases, we also derive closed-form expressions for physical moments of the excess market return. Bounds are not needed. Although we derive these closed-form expressions, our bounds are for the general case when the utility function and SDF are not known.