Microstructure models with short-term inertia and stochastic volatility
type: Item
instance of: scholarly article
title: Microstructure models with short-term inertia and stochastic volatility
zbMATH Open document ID: 1394.91311
DOI: 10.1155/2015/323475
author: Michael A. Kouritzin
published in: Mathematical Problems in Engineering
publication date: 2018-08-27T00:00:00Z
review text: Summary: Partially observed microstructure models, containing stochastic volatility, dynamic trading noise, and short-term inertia, are introduced to address the following questions: (1) Do the observed prices exhibit statistically significant inertia? (2) Is stochastic volatility (SV) still evident in the presence of dynamical trading noise? (3) If stochastic volatility and trading noise are present, which SV model matches the observed price data best? Bayes factor methods are used to answer these questions with real data and this allows us to consider volatility models with very different structures. Nonlinear filtering techniques are utilized to compute the Bayes factor on tick-by-tick data and to estimate the unknown parameters. It is shown that our price data sets all exhibit strong evidence of both inertia and Heston-type stochastic volatility.
Mathematics Subject Classification ID: 91B70
zbMATH DE Number: 6926066
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2015/323475
OpenAlex ID: W2160178006
Wikidata QID: Q59118017
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description: scientific article; zbMATH DE number 6926066