Open AccessPortfolio Selection using DEA-COPRAS at Risk – Return Interface Based on NSE (India)
Author(s) -
Sayan Gupta,
Gautam Bandyopadhyay,
Malay Bhattacharjee,
Sanjib Biswas
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.j8858.0881019
Subject(s) - portfolio , market liquidity , investment performance , investment decisions , economics , actuarial science , econometrics , selection (genetic algorithm) , rate of return on a portfolio , financial economics , return on investment , portfolio optimization , computer science , finance , microeconomics , artificial intelligence , behavioral economics , production (economics)
Portfolio formation holds paramount importance in the process of the investment decision making since, a single door investment (SDI) option is much riskier than a multiple door investment (MDI) option. Among available financial instruments, the stock market (SM) has allured investors because of its liquidity and growth opportunities. However, the effectiveness of the investment decision is largely reflected in the selection of the constituent elements of the portfolio by an investor while trading off risk and return. In this paper, after an initial level selection of for formulating a possible portfolio by using Perceptual Map (PM), we have applied DEA to calculate the efficiency of the stocks at the risk-return interface based on the market performance. In order to ascertain that the stock selection is logical and worthwhile, we further probe the fundamental performances over a time period of five consecutive financial years using the method of Multi-Criteria Decision Analysis (MCDA) framework based on the Complex Proportional Assessment (COPRAS) method, where, the criteria weights are calculated by using the entropy method. A consistency is visible in the yearly fundamental performances and a significant pattern with regard to the portfolio selection.