Transition Densities for Interest Rate and Other Nonlinear Diffusions

This paper applies to interest rate models the theoretical method developed in Aït-Sahalia (1998) to generate accurate closed-form approximations to the transition function of an arbitrary diffusion. While the main focus of this paper is on the maximum-likelihood estimation of interest rate models with otherwise unknown transition functions, applications to the valuation of derivative securities are also briefly discussed.     

Out of sample forecasts of quadratic variation

We compare the forecasts of Quadratic Variation given by the Realized Volatility (RV) and the Two Scales Realized Volatility (TSRV) computed from high frequency data in the presence of market microstructure noise, under several different dynamics for the volatility process and assumptions on the noise. We show that TSRV largely outperforms RV, whether looking at bias, variance, RMSE or out-of-sample forecasting ability. An empirical application to all DJIA stocks confirms the simulation results.     

Stationarity-based specification tests for diffusions when the process is nonstationary

We analyze in this paper the asymptotic behavior of the specification test of Aït-Sahalia (1996) for the stationary density of a diffusion process, but when the diffusion is not stationary. We consider integrated and explosive processes, as well as nearly integrated ones in the spirit of the local to unity analysis in classical unit root theory. We find that the behavior of the test predicted by the asymptotic distribution under an integrated process provides a better approximation to the small sample distribution of the test than that predicted by the asymptotic distribution under strict stationarity.     

The Effect of CEO Risk Appetite on Firm Volatility: An Empirical Analysis of Financial Firms☆

This paper examines the effect of CEO risk appetite on the return volatility of a sample of large, listed financial firms over the period 2000–2008. After controlling for firm specific characteristics, the results give strong evidence that the CEO risk appetite has an important effect on firm volatility. The biographical measures for CEO risk appetite are significant explanatory variables of all measures of firm volatility employed in this study. The effect of CEO age is significant and positive for all four volatility measures, while CEO education and current job tenure are negative and significant for all four measures. Executive experience with other firm boards has a negative and significant effect on total and idiosyncratic volatility. Interestingly, CEO wealth is complementary to the other biographical variables with a positive effect on all but the default volatility measure. Our results carry implications for shareholders, financial regulators, governments, and managers.     

Nonparametric Estimation of State-Price Densities Implicit in Financial Asset Prices

Implicit in the prices of traded financial assets are Arrow–Debreu prices or, with continuous states, the state-price density (SPD). We construct a nonparametric estimator for the SPD implicit in option prices and we derive its asymptotic sampling theory. This estimator provides an arbitrage-free method of pricing new, complex, or illiquid securities while capturing those features of the data that are most relevant from an asset-pricing perspective, for example, negative skewness and excess kurtosis for asset returns, and volatility "smiles" for option prices. We perform Monte Carlo experiments and extract the SPD from actual S&P 500 option prices.