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A Modified Levy Jump-Diffusion Model Based on Market Sentiment Memory for Online Jump Prediction

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  • Zheqing Zhu
  • Jian-guo Liu
  • Lei Li

Abstract

In this paper, we propose a modified Levy jump diffusion model with market sentiment memory for stock prices, where the market sentiment comes from data mining implementation using Tweets on Twitter. We take the market sentiment process, which has memory, as the signal of Levy jumps in the stock price. An online learning and optimization algorithm with the Unscented Kalman filter (UKF) is then proposed to learn the memory and to predict possible price jumps. Experiments show that the algorithm provides a relatively good performance in identifying asset return trends.

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  • Zheqing Zhu & Jian-guo Liu & Lei Li, 2017. "A Modified Levy Jump-Diffusion Model Based on Market Sentiment Memory for Online Jump Prediction," Papers 1709.03611, arXiv.org.
    • Handle: RePEc:arx:papers:1709.03611
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    References listed on IDEAS

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    4. Lisa Borland, 2002. "Option Pricing Formulas based on a non-Gaussian Stock Price Model," Papers cond-mat/0204331, arXiv.org, revised Sep 2002.
    5. Geman, Helyette, 2002. "Pure jump Levy processes for asset price modelling," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1297-1316, July.
    6. Ross,Sheldon M., 2011. "An Elementary Introduction to Mathematical Finance," Cambridge Books, Cambridge University Press, number 9780521192538.
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