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A semi-Markovian approach to model the tick-by-tick dynamics of stock price

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  • Garima Agrawal
  • Anindya Goswami

Abstract

We model the stock price dynamics through a semi-Markov process obtained using a Poisson random measure. We establish the existence and uniqueness of the classical solution of a non-homogeneous terminal value problem and we show that the expected value of stock price at horizon can be obtained as a classical solution of a linear partial differential equation that is a special case of the terminal value problem studied in this paper. We further analyze the market making problem using the point of view of an agent who posts the limit orders at the best price available. We use the dynamic programming principle to obtain a HJB equation. In no-risk aversion case, we obtain the value function as a classical solution of a linear pde and derive the expressions for optimal controls by solving the HJB equation.

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  • Garima Agrawal & Anindya Goswami, 2022. "A semi-Markovian approach to model the tick-by-tick dynamics of stock price," Papers 2209.04620, arXiv.org.
    • Handle: RePEc:arx:papers:2209.04620
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    References listed on IDEAS

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    1. Pietro Fodra & Huyên Pham, 2015. "Semi-Markov Model for Market Microstructure," Applied Mathematical Finance, Taylor & Francis Journals, vol. 22(3), pages 261-295, July.
    2. Anindya Goswami & Jeeten Patel & Poorva Shevgaonkar, 2015. "A system of non-local parabolic PDE and application to option pricing," Papers 1506.01467, arXiv.org, revised May 2016.
    3. Pietro Fodra & Huy^en Pham, 2013. "High frequency trading and asymptotics for small risk aversion in a Markov renewal model," Papers 1310.1756, arXiv.org, revised Jan 2015.
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