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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/11431

Title: Estimation of Stochastic Volatility with a Compensated Poisson Jump Using Quadratic Variation
Authors: Andam, Perpetual Saah
Ackora-Prah, Joseph
Mataramvura, Sure
Keywords: Stochastic Volatility
Compensated Poisson Jump
Quadratic Variation
Issue Date: 2017
Publisher: Applied Mathematics
Citation: Applied Mathematics, 2017, 8, 987-1000; http://www.scirp.org/journal/am
Abstract: The degree of variation of trading prices with respect to time is volatilitymeasured by the standard deviation of returns. We present the estimation of stochastic volatility from the stochastic differential equation for evenly spaced data. We indicate that, the price process is driven by a semi-martingale and the data are evenly spaced. The results of Malliavin and Mancino [1] are extended by adding a compensated poisson jump that uses a quadratic variation to calculate volatility. The volatility is computed from a daily data without assuming its functional form. Our result is well suited for financial market applications and in particular the analysis of high frequency data for the computation of volatility.
Description: An article published in Applied Mathematics, 2017, 8, 987-1000; http://www.scirp.org/journal/am; https://doi.org/10.4236/am.2017.87077
URI: http://hdl.handle.net/123456789/11431
Appears in Collections:College of Science

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