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Stochastic Volatility Analysis using the Generalised Kolmogorov-Feller Equation.

  • Jonathan Blackledge

Research output: Contribution to conferencePaperpeer-review

Abstract

We consider an approach to analysing the Stochastic Volatility of a financial time series using the Generalised Kolmogorov-Feller Equation (GKFE). After reviewing the computation of the Stochastic Volatility using a phase only condition, a Green’s function solution to the GKFE equation is derived which depends upon the ‘memory function’ used to construct the GKFE. Using the Mittag-Leffler memory function, we derive an expression for the Impulse Response Function associated with a short time window of data which is then used to derive an algorithm for computing a new index using a standard moving window process. It is shown that application of this index to both a financial time series and its corresponding Stochastic Volatility provides a correlation between the start, direction and end of a trend depending on the sampling rate of the time series and the look-back window that is used.
Original languageEnglish
DOIs
Publication statusPublished - 2012
Externally publishedYes
EventThe 2012 International Conference of Financial Engineering - London, United Kingdom
Duration: 1 Jan 201231 Dec 2012

Conference

ConferenceThe 2012 International Conference of Financial Engineering
Country/TerritoryUnited Kingdom
CityLondon
Period1/01/1231/12/12

Keywords

  • Stochastic Volatility
  • Generalised Kolmogorov-Feller Equation
  • Green’s function
  • memory function
  • Mittag-Leffler memory function
  • Impulse Response Function
  • financial time series
  • algorithm
  • moving window process
  • correlation
  • trend

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