This collection of original articles-8 years in the making-shines a bright light on recent advances in financial econometrics. From a survey of mathematical and statistical tools for understanding nonlinear Markov processes to an exploration of the time-series evolution of the risk-return tradeoff for stock market investment, noted scholars Yacine Aït-Sahalia and Lars Peter Hansen benchmark the current state of knowledge while contributors build a framework for its growth. Whether in the presence of statistical uncertainty or the proven advantages and limitations of value at risk models, readers will discover that they can set few constraints on the value of this long-awaited volume.
Fundamental econometric techniques and tools form the basis of this first volume on recent advances in financial econometrics. Parametric and nonparametric, in continuous time and discrete time, among these techniques and tools are Markov processes, a system for categorizing volatility concepts, a simulated method of moments indicator, and models for the timing of events. Together they reveal the ways that local characterizations can lead to long-run implications and how relationships between observed and unobserved values can be inferred. Broad and eclectic, the subjects covered by Volume 1 benchmark the current state of econometric research.