Portfolio Performance & Predictive Relevance through Techno-Fundamental Analysis- A Hybrid ARIMA Approach
Journal: International Journal of Mechanical and Production Engineering Research and Development (IJMPERD ) (Vol.10, No. 3)Publication Date: 2020-06-30
Authors : Nitin Kulshrestha; Vinay K Srivastava;
Page : 4971-4984
Keywords : Technical Analysis; Fundamental Analysis; Hybrid ARIMA; Backtest; Nifty Index; Portfolio; Expert System; Algorithmic Trading/Investment;
Abstract
Purpose: The primary purpose of this paper is to understand the portfolio performance & predictive relevance of TechnoFundamental analysis through Hybrid ARIMA. Can we leverage the portfolio selection, investment optimisation & predictive relevance through Techno-fundamental analysis? Design /Methodologies/Approach: In this paper, we have selected the National Stock Exchange selected shares & apply fundamental analysis for selecting portfolio & technical analysis along with algorithmic trading for superior earning optimization, furthermore, Hybrid ARIMA to validate predictive relevance. The empirical analysis includes the chosen portfolio from Jan 2014 to May 2020. Originality & Value: This paper is written primarily for those financial enthusiasts who want to take leverage of synergy i.e., Technical analysis & Fundamental analysis to optimise their portfolio. Results & Practical implication: The successful application of "L- FANTAM" approach will encourage the practitioners & academicians of Financial markets to research & explore further uses & practical impact of the present stud
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