This paper introduces a new class of parameter estimators for dynamic models, called Simulated Nonparametric Estimators (SNE). The SNE minimizes appropriate distances between nonparametric joint (or conditional) densities estimated from sample data and nonparametric joint (or conditional)...

This paper introduces a new parameter estimator of dynamic models in which the state is a multidimensional, continuous-time, partially observed Markov process. The estimator minimizes appropriate distances between nonparametric joint (and/or conditional) densities of sample data and...

Which pricing kernel restrictions are needed to make low dimensional Markov models consistent with given sets of predictions on aggregate stock-market fluctuations ? This paper develops theoretical test conditions addressing this and related reverse engineering issues arising within a fairly...

We provide a historical perspective focusing on Ziemba's experiences and research on the bond-stock earnings yield differential model (BSEYD) starting from when he first used it in Japan in 1988 through to the present in 2014. The model has called many but not all crashes. Those called have high...

This paper presents estimates of key preference parameters of the Epstein and Zin (1989, 1991) and Weil (1989) recursive utility model, evaluates the model's ability to fit asset return data relative to other asset pricing models, and investigates the implications of such estimates for the...