Financial Time Series -Recent Trends in Econometrics
Keywords:
high frequency data, chaos, stochastic volatility, brownian motion, markov process, garch process
Abstract
The paper points to a coverage of the latest research techniques and findings relating to the econometric analysis of financial markets. It contains a wealth of new materials reflecting the developments during the last decade or so. Particular attention is paid to the wide range of nonlinear models that are used to analyze financial data observed at high frequencies and to the long memory characteristics found in financial time series. There is also a discussion, briefly, of the treatment of volatility, chaos, the Fed model, stochastic estimation and Bayesian estimation, the Fed model and tail dependent time series models.
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Published
2013-05-21
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