A Novel Quantitative Behavioral Framework for Financial Markets Prediction

Capital Markets: Asset Pricing & Valuation, eJournal, Vol. 3, Issue 152, September 28, 2011

61st Midwest Finance Association Conference, February, 2012

11 Pages Posted: 17 Sep 2011 Last revised: 21 May 2012

See all articles by Ramesh Thimmaraya

Ramesh Thimmaraya

Centre for Quantitative Finance and Risk Analytics

Venkateshwarlu Masuna

National Institute of Industrial Engineering NITIE

Date Written: September 16, 2011

Abstract

Effective prediction of financial asset prices has become a challenge in the present day volatile world. The use of mathematics have become very extensive in the financial world, most of the mathematical models concentrates on the market data rather than the behavior of the market from which the data has been generated. An attempt has been made for the first time to model the prediction of asset prices based on both the market data and the behavior of the market participants. The participants in the financial markets behave differently from each other, these behavioral differences can be attributed to the participants understating or/and his perception about the market. Each investor has his own perception about the market and he feel it is close to reality, but truly speaking it is not so. Each participant has his own impact on the market and the reality is the aggregation of each participant’s perception. The impact of the investor’s behavior has been modeled in the present quantitative behavioral approach by dividing the participants into broad categories based on their trading behavior. To model the participant’s impact first one should predict the proportion of participants in each category. Most of the times, finding the exact number of participants in each category is not easily available from the market data, so an evolutionary based swarm intelligence model has been adopted in the present framework to find the proportion of the participants in each category. Finally the whole methodology has been applied to gold asset class (because gold is an international asset with increasing volatility these days) to validate the present method. The model is tested rigorously using different time varying samples to validate the present methodology; some interesting results have been obtained from the present study. The back testing results prove that the model presented in this paper is very effective in predicting the prices close to reality. The present frame work is very generic and can be applied to any financial asset class to estimate the returns close to reality.

Keywords: Quantitative Behavioral Finance, Financial asset prediction, Gold prices prediction, Swam intelligence, Support vector regression, Trading behavior

JEL Classification: G12, F47, C61, C53

Suggested Citation

Thimmaraya, Ramesh and Masuna, Venkateshwarlu, A Novel Quantitative Behavioral Framework for Financial Markets Prediction (September 16, 2011). Capital Markets: Asset Pricing & Valuation, eJournal, Vol. 3, Issue 152, September 28, 2011 , 61st Midwest Finance Association Conference, February, 2012, Available at SSRN: https://ssrn.com/abstract=1928727 or http://dx.doi.org/10.2139/ssrn.1928727

Ramesh Thimmaraya (Contact Author)

Centre for Quantitative Finance and Risk Analytics ( email )

Vihar Lake Road
Mumbai
India

Venkateshwarlu Masuna

National Institute of Industrial Engineering NITIE ( email )

Vihar Lake Road
Mumbai, Mahrashtra 400087
India

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
569
Abstract Views
2,192
rank
56,962
PlumX Metrics