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Revealing the arcane: an introduction to the art of stochastic volatility models

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  • Tsyplakov, Alexander

Abstract

This essay is aimed to provide a straightforward and sufficiently accessible demonstration of some known procedures for stochastic volatility model. It reviews the important related concepts, gives informal derivations of the methods and can be useful as a cookbook for a novice. The exposition is confined to classical (non-Bayesian) framework and discrete-time formulations.

Suggested Citation

  • Tsyplakov, Alexander, 2010. "Revealing the arcane: an introduction to the art of stochastic volatility models," MPRA Paper 25511, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:25511
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    File URL: https://mpra.ub.uni-muenchen.de/25511/1/MPRA_paper_25511.pdf
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    Cited by:

    1. Laurini Márcio Poletti, 2013. "A Hybrid Data Cloning Maximum Likelihood Estimator for Stochastic Volatility Models," Journal of Time Series Econometrics, De Gruyter, vol. 5(2), pages 193-229, May.
    2. Valeriya V. Lakshina & Andrey M. Silaev, 2016. "Fluke of stochastic volatility versus GARCH inevitability or which model creates better forecasts?," Economics Bulletin, AccessEcon, vol. 36(4), pages 2368-2380.
    3. Valeria V. Lakshina, 2014. "The Fluke Of Stochastic Volatility Versus Garch Inevitability : Which Model Creates Better Forecasts?," HSE Working papers WP BRP 37/FE/2014, National Research University Higher School of Economics.

    More about this item

    Keywords

    stochastic volatility;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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