[This article develops a Kalman filter model to track dynamic mutual fund factor loadings. It then uses the estimates to analyze whether managers with market-timing ability can be identified ex ante. The primary findings are as follows: (i) Ordinary least squares (OLS) timing models produce false positives (nonzero alphas) at too high a rate with either daily or monthly data. In contrast, the Kalman filter model produces them at approximately the correct rate with monthly data; (ii) In monthly data, though the OLS models fail to detect any timing among fund managers, the Kalman filter does; (iii) The alpha and beta forecasts from the Kalman model are more accurate than those from the OLS timing models; (iv) The Kalman filter model tracks most fund alphas and betas better than OLS models that employ macroeconomic variables in addition to fund returns.]
[Strategic alliances are long-term contracts between legally distinct organizations that provide for sharing the costs and benefits of a mutually beneficial activity. In this paper, I develop and test a model that helps explain why firms sometimes prefer alliances over internally organized projects. I introduce managerial effort into a model of internal capital markets and show how strategic alliances help overcome incentive problems that arise when headquarters cannot pre-commit to particular capital allocations. The model generates a number of implications, which I test using a large sample of alliance transactions in conjunction with Compustat data.]
[We study whether option-implied jump risk premia can explain the high observed level of credit spreads. We use a structural jump-diffusion firm value model to assess the level of credit spreads generated by option-implied jump risk premia. Prices and returns of equity index and individual options are used to estimate the jump parameters. We further calibrate the model to historical information on default risk and the equity premium. The results show that incorporating option-implied jump risk premia brings predicted credit spread levels much closer to observed levels. The introduction of jumps also helps to improve the fit of the volatility of credit spreads and equity returns.]
[We introduce a model that captures the main properties that characterize employee stock options (ESO). We discuss the likelihood of early voluntary ESO exercise, and the obligation to exercise immediately if the employee leaves the firm, except if this happens before options are vested, in which case the options are forfeited. We derive an analytic formula for the price of the ESO and in a case study compare it to alternative methods.]
[This paper examines whether investor sentiment about the stock market affects prices of the S&P 500 options. The findings reveal that the index option volatility smile is steeper (flatter) and the risk-neutral skewness of monthly index return is more (less) negative when market sentiment becomes more bearish (bullish). These significant relations are robust and become stronger when there are more impediments to arbitrage in index options. They cannot be explained by rational perfect-market-based option pricing models. Changes in investor sentiment help explain time variation in the slope of index option smile and risk-neutral skewness beyond factors suggested by the current models.]
[While recent studies document increasing idiosyncratic volatility over the past four decades, an explanation for this trend remains elusive. We establish a theoretical link between growth options available to managers and the idiosyncratic risk of equity. Empirically both the level and variance of corporate growth options are significantly related to idiosyncratic volatility. Accounting for growth options eliminates or reverses the trend in aggregate firm-specific risk. These results are robust for different measures of idiosyncratic volatility, different growth option proxies, across exchanges, and through time. Finally, our results suggest that growth options explain the trend in idiosyncratic volatility beyond alternative explanations.]
[If returns are not predictable, dividend growth must be predictable, to generate the observed variation in divided yields. I find that the absence of dividend growth predictability gives stronger evidence than does the presence of return predictability. Long-horizon return forecasts give the same strong evidence. These tests exploit the negative correlation of return forecasts with dividend-yield autocorrelation across samples, together with sensible upper bounds on dividend-yield autocorrelation, to deliver more powerful statistics. I reconcile my findings with the literature that finds poor power in long-horizon return forecasts, and with the literature that notes the poor out-of-sample R² of return-forecasting regressions.]
[We posit that screening IPOs requires specialized labor which is in fixed supply. A sudden increase in demand for IPO financing increases the compensation of IPO screening labor. This results in reduced screening, encouraging sub-marginal firms to enter the IPO market, further fueling the demand for screening labor. The model's conclusions are consistent with empirical findings of increased underpricing during hot markets, positive correlation between issue volume and underpricing, and with tipping points between hot and cold markets. Finally, the model makes sharp predictions relating the IPO market to fundamental values of firms and to investment banking returns.]
[The prevailing view in finance is that the evidence for long-horizon stock return predictability is significantly stronger than that for short horizons. We show that for persistent regressors, a characteristic of most of the predictive variables used in the literature, the estimators are almost perfectly correlated across horizons under the null hypothesis of no predictability. For the persistence levels of dividend yields, the analytical correlation is 99% between the 1- and 2-year horizon estimators and 94% between the 1- and 5-year horizons. Common sampling error across equations leads to ordinary least squares coefficient estimates and R²s that are roughly proportional to the horizon under the null hypothesis. This is the precise pattern found in the data. We perform joint tests across horizons for a variety of explanatory variables and provide an alternative view of the existing evidence.]
[This paper studies whether stock returns' sensitivities to aggregate liquidity fluctuations and the pricing of liquidity risk vary over time. We find that liquidity betas vary across two distinct states: one with high liquidity betas and the other with low betas. The high liquidity-beta state is short lived and characterized by heavy trade, high volatility, and a wide cross-sectional dispersion in liquidity betas. It also delivers a disproportionately large liquidity risk premium, amounting to more than twice the value premium. Our results are consistent with a model of liquidity risk in which investors face uncertainty about their trading counterparties' preferences.]