Forecasting of Indian Stock Market by Effective Macro- Economic Factors and Stochastic Model

Jyoti Badge

Journal of Statistical and Econometric Methods, 2012, vol. 1, issue 2, 4

Abstract: The stock market patterns are non-linear in nature therefore it is difficult to forecast the future trends of the market. In this paper we have used different macro-economic factors of Indian stock market. Macro-economic factors include technical indicators. These technical indicators help to decide the patterns of the market at a particular time. There are hundreds of technical indicators are available, but all technical indicators are not useful. So we have obtained most effective technical indicators by applying Principal Component Analysis (PCA). Selected technical indicators are taken as input variable. Future prices are found through Hidden Markov Model (HMM). Hidden Markov Model is a very powerful stochastic model. In literature survey it was found that HMM gives better accuracy than other models. On the basis of experiment it was found that HMM with PCA performed well and gives Mean Absolute Percentage Error (MAPE) 1.77%.

Date: 2012
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