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Stochastic volatility models

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Macroeconometrics and Time Series Analysis

Part of the book series: The New Palgrave Economics Collection ((NPHE))

Abstract

Stochastic volatility (SV) is the main concept used in the fields of financial economics and mathematical finance to deal with the endemic time-varying volatility and codependence found in financial markets. Such dependence has been known for a long time; early commentators include Mandelbrot (1963) and Officer (1973). It was also clear to the founding fathers of modern continuous time finance that homogeneity was an unrealistic if convenient simplification; for example, Black and Scholes (1972, p. 416) wrote, ‘…there is evidence of non-stationarity in the variance. More work must be done to predict variances using the information available.’ Heterogeneity has deep implications for the theory and practice of financial economics and econometrics. In particular, asset pricing theory is dominated by the idea that higher rewards may be expected when we face higher risks, but these risks change through time in complicated ways. Some of the changes in the level of risk can be modelled stochastically, where the level of volatility and degree of codependence between assets is allowed to change over time. Such models allow us to explain, for example, empirically observed departures from Black-Scholes-Merton prices for options and understand why we should expect to see occasional dramatic moves in financial markets.

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Authors
  1. Neil Shephard
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Editor information

Editors and Affiliations

  1. University of Wisconsin-Madison, USA

    Steven N. Durlauf

  2. Cornell University, USA

    Lawrence E. Blume

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© 2010 Palgrave Macmillan, a division of Macmillan Publishers Limited

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Shephard, N. (2010). Stochastic volatility models. In: Durlauf, S.N., Blume, L.E. (eds) Macroeconometrics and Time Series Analysis. The New Palgrave Economics Collection. Palgrave Macmillan, London. https://doi.org/10.1057/9780230280830_31

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