We study the consumption-portfolio allocation problem in continuous time when asset prices follow Levy processes and the investor is concerned about potential model misspecification. We derive optimal consumption and portfolio policies that are robust to uncertainty about the...

We develop and implement asymptotic theory to conduct inference on continuous-time asset pricing models using individual equity returns sampled at high frequencies over an increasing time horizon. We study the identification and estimation of risk premia for the continuous and jump components of...

We consider a nonparametric time series regression model. Our framework allows precise estimation of betas without the usual assumption of betas being piecewise constant. This property makes our framework particularly suitable to study individual stocks. We provide an inference framework for all...

Different continuous-time models for interest rates coexist in the literature. We test parametric models by comparing their implied parametric density to the same density estimated nonparametrically. We do not replace the continuous-time model by discrete approximations, even though the data are...

Many models of the term structure of interest rates rely on a continuous-time specification of the short rate process as one of their factors. Different parametric specifications for this process, often arbitrary and mutually exclusive, coexist in the literature. It is important to specify this...

This paper develops and estimates a continuous-time model of a financial market where investors' trading strategies and the market maker's rule of price adjustments are best response to each other. There exists an equilibrium where the market maker finds it optimal to add volatility to the price...

This paper derives a nonparametric estimation procedure for continuous-time models and provides the asymptotic distribution of the estimator. Since the pricing of derivative securities depends crucially on the form of the instantaneous volatility of the underlying asset, the diffusion function...

We develop tests that help assess whether a high frequency data sample can be treated as reasonably free of market microstructure noise at a given sampling frequency for the purpose of implementing high frequency volatility and other estimators. The tests are based on the Hausman principle of...

We develop the necessary methodology to conduct principal component analysis at high frequency. We construct estimators of realized eigenvalues, eigenvectors, and principal components and provide the asymptotic distribution of these estimators. Empirically, we study the high frequency covariance...

We propose a model of market making where a strategic high frequency trader exploits his speed and informational advantages to place quotes that interact with the orders of low frequency traders. We characterize the optimal market making policy of the high frequency trader analytically. Our...