Financial Econometrics

International Library of Financial Econometrics, Forthcoming

31 Pages Posted: 14 Jun 2007

See all articles by Andrew W. Lo

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER); Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Abstract

This is an introduction to a five-volume collection of papers on financial econometrics to be published by Edward Elgar Publishers in 2007. Financial econometrics is one of the fastest growing branches of economics today, both in academia and in industry. The increasing sophistication of financial models requires equally sophisticated methods for their empirical implementation, and in recent years financial econometricians have stepped up to the challenge. The toolkit of financial econometrics has grown in size and depth, including techniques such as nonparametric estimation, functional central limit theory, nonlinear time-series models, artificial neural networks, and Markov Chain Monte Carlo methods. In these five volumes, the most influential papers of financial econometrics have been collected, spanning four decades and five distinct subfields: statistical models of asset returns (Volume I), static asset-pricing models (Volume II), dynamic asset-pricing models (Volume III), continuous-time methods and market microstructure (Volume IV), and statistical methods and non-standard finance (Volume V). Within each volume, different strands of the literature are weaved together to form a rich and coherent historical perspective on empirical and methodological breakthroughs in financial markets, while covering the major themes of financial econometrics.

Keywords: Financial Econometrics, Asset Pricing, Portfolio Theory, Market Microstructure, Empirical Finance

JEL Classification: G00, G10, G11, G12, G13, G14, C40, C50

Suggested Citation

Lo, Andrew W., Financial Econometrics. International Library of Financial Econometrics, Forthcoming. Available at SSRN: https://ssrn.com/abstract=991805

Andrew W. Lo (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

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National Bureau of Economic Research (NBER) ( email )

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Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

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