Taylor, S J (1999) Markov processes and the distribution of volatility:a comparison of discrete and continuous specifications. Philosophical Transactions A: Mathematical, Physical and Engineering Sciences, 357 (1758). pp. 2059-2070. ISSN 1364-503XFull text not available from this repository.
Two mixtures of normal distributions, created by persistent changes in volatility, are compared as models for asset returns. A Markov chain with two states for volatility is contrasted with an autoregressive Gaussian process for the logarithm of volatility. The conditional variances of asset returns are shown to have a bimodal distribution for the former process when volatility is persistent that contrasts with a unimodal distribution for the latter process. A test procedure based upon this contrast shows that a log–normal distribution for sterling/dollar volatility is far more credible than only two volatility states.
|Journal or Publication Title:||Philosophical Transactions A: Mathematical, Physical and Engineering Sciences|
|Uncontrolled Keywords:||conditional state probabilities ; foreign exchange volatility distributions stochastic volatility ; Leptokurtic return distributions ; Markov chain ; mixture distributions ; stochastic volatility|
|Departments:||Lancaster University Management School > Accounting & Finance|
|Deposited On:||11 Jul 2011 18:59|
|Last Modified:||01 May 2017 02:39|
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