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FORECASTING THE PERFORMANCE OF EFFICIENT INDIAN EQUITY MUTUAL FUNDS PORTFOLIO USING AUTO-REGRESSIVE INTEGRATED MOVING AVERAGE MODEL

SOUMYA BANERJEE 1, BANHI GUHA 2, AMLAN GHOSH 3, and GAUTAM BANDYOPADHYAY 4.

Vol 17, No 09 ( 2022 )   |  DOI: 10.5281/zenodo.7059561   |   Author Affiliation: Research Scholar, Department of Management Studies, NIT Durgapur, West Bengal 1; Assistant Professor, Xavier’s Business School, St. Xavier’s University, West Bengal 2; Associate Professor, Department of Management Studies, NIT Durgapur, West Bengal 3; Professor, Department of Management Studies, NIT Durgapur, West Bengal 4.   |   Licensing: CC 4.0   |   Pg no: 161–179   |   To cite: SOUMYA BANERJEE, BANHI GUHA, AMLAN GHOSH, & GAUTAM BANDYOPADHYAY. (2022). FORECASTING THE PERFORMANCE OF EFFICIENT INDIAN EQUITY MUTUAL FUNDS PORTFOLIO USING AUTO-REGRESSIVE INTEGRATED MOVING AVERAGE MODEL. 17(09), 161–179. https://doi.org/10.5281/zenodo.7059561   |   Published on: 06-09-2022

Abstract

Mutual funds are one of the safest options to invest money in the stock market or to buy assets. Past and present analysis of the mutual fund investing scenario is very crucial to gain an insight about the future performance. This paper aims to forecast the Net Asset Values of an efficient Indian Equity Mutual Funds portfolio using the Auto-Regressive Integrated Moving Average model. The Equity Mutual funds which are operational on or before January 2015 are considered and their monthly Net Asset Values are collected from January 2015 – December 2019. The portfolio is constructed by allocating weightage to the funds ensuring minimum risk. The stationarity of the Net Asset Value for each fund constituting the portfolio is tested using the Augmented Dickey-Fuller test. An appropriate Auto-Regressive Integrated Moving Average model is fitted to each of these funds and the models are validated using the Ljung Box test. The models with the lowest Akaike's Information Criteria value and significant coefficients are selected as the appropriate model. The Net Asset Values for the first six months of the year 2020 are forecasted for each fund using the selected model and the forecasts are found to be quite appropriate. Thus, this study will help investors in their future investments.


Keywords

Equity Mutual Fund, Auto-Regressive Integrated Moving Average model, Augmented Dickey-Fuller test, Ljung Box test, Akaike’s Information Criteria.