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Stochastic Forecasting of Stock Prices of Capital Assets Using Semi-Markov Model
Abstract
In this paper, we developed a stochastic model based on a semi-Markov chains approach and its generalizations to study the high-frequency price dynamics of traded stocks. Semi-Markov is a stochastic process that generalizes both the Markov chain and Markov renewal process. It is well known that the performance of the stock market or factors that move stock prices are technical factors, fundamental factors, and market sentiment. We used Poisson distribution to give the probability of several events in an interval that is generated by a
Poisson process and to predict the long-term behavior of the stock value price movement. This semi-Markov model can be applied to stock values of capital assets for both opening and closing prices for a specific period to predict stock price movements for the three states
(bull market state, bear market state and stagnant market state) for the process.
Keywords
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