George Tauchen

TL;DR: In this article, the authors introduce reprojection as a general-purpose technique for characterizing the dynamic response of a partially observed nonlinear system to its observable history, where first data are summarized by projection onto a Hermite series representation of the unconstrained transition density for observables, then system parameters are estimated by minimum chi-squared, where the chi-square criterion is a quadratic form in the expected score of the projection.

TL;DR: In this article, the authors developed techniques for estimating the conditional distribution of the forward integrated variance given observed variables and found that standard models do not fit the data very well and a more general three-factor model does better, as it mimics the long-memory feature of financial volatility.

TL;DR: In this article, the jump detection method based on bi-power variation was extended to identify realized jumps on flnancial markets and to estimate parametrically the jump intensity, mean, and variance.

TL;DR: The authors developed an empirically highly accurate discrete-time daily stochastic volatility model that explicitly distinguishes between the jump and continuous time components of price movements using nonparametric realized variation and Bipower variation measures constructed from high-frequency intraday data.