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Performance Analysis of Hybrid Forecasting Model In Stock Market Forecasting

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  • Mahesh S. Khadka
  • K. M. George
  • N. Park
  • J. B. Kim

Abstract

This paper presents performance analysis of hybrid model comprise of concordance and Genetic Programming (GP) to forecast financial market with some existing models. This scheme can be used for in depth analysis of stock market. Different measures of concordances such as Kendalls Tau, Ginis Mean Difference, Spearmans Rho, and weak interpretation of concordance are used to search for the pattern in past that look similar to present. Genetic Programming is then used to match the past trend to present trend as close as possible. Then Genetic Program estimates what will happen next based on what had happened next. The concept is validated using financial time series data (S&P 500 and NASDAQ indices) as sample data sets. The forecasted result is then compared with standard ARIMA model and other model to analyse its performance.

Suggested Citation

  • Mahesh S. Khadka & K. M. George & N. Park & J. B. Kim, 2012. "Performance Analysis of Hybrid Forecasting Model In Stock Market Forecasting," Papers 1209.4608, arXiv.org, revised May 2013.
    • Handle: RePEc:arx:papers:1209.4608
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    1. Lan, Boon Leong & Tan, Ying Oon, 2007. "Statistical properties of stock market indices of different economies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 605-611.
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