A cellular automata model for safe investment based on expert's recommendations

Tessy Mathew, L. Jeganathan and U. Srinivasa Rao

International Journal of Economics and Business Research, 2017, vol. 14, issue 3/4, 390-400

Abstract: Traditional stock trading methodologies (ARMA, ARIMA, regression, etc.) are used to analyse price behaviour and then produce signals namely BUY, SELL or HOLD. Our proposed work is to develop a one-dimensional cellular automata model that helps new investors who have zero knowledge on stock market trades. The one-dimensional cellular automata (1D CA) model processes the existing recommendations or advices from the experts who possess a very good knowledge on stock market trades. Based on different expert recommendations, the CA model will give financial alerts that will help the investor to take buy/hold/sell decision on stocks. Hence new investors can either make a profit or at least keep them in safe zone (minimum loss). The trading rules in this model give highest priority to sell the share and lowest priority to buy the share. This model gives recommendations to investors regarding the selling, buying and holding of a stock/stock segment.

Keywords: stock market; cellular automata; complexity; investment behaviour. (search for similar items in EconPapers)
Date: 2017
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