Application of Discrete-time semi-Markov Model to the Stochastic forecasting of Capital assests as stock.

Abstract

In this paper, we developed and applied a stochastic model based on Discrete-time Semi Markov chain 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 the Markov renewal processes. it is well known that the performances of the stock market or factors that move stock prices are technical factors, fundamental factors and market sentiments.

Description

Keywords

Discrete-time Semi Markov Model, Stock prices, bull market, bear market, stagnant market

Citation