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Forecasting Foreign Institutional Investors' (FII) Investment Flows in India: An Autoregressive Model


Affiliations
1 Assistant Professor, School of Management Studies, Kongu Engineering College, Perundurai, Erode - 638 060, Tamil Nadu, India
2 Assistant Professor, Department of Management Studies, Nandha Engineering College, Erode - 638 052, Tamil Nadu, India

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India is considered as one of the fastest emerging economies in the world and a leading nation in attracting foreign investments. The country offers huge investment opportunities to reap benefits for both domestic and foreign institutional investors (FIIs) in its equity market. India's FII investments are characterized by positive net inflows in most of the years since its inception in 1992. Only during 1998-99 and 2008-09, FII outflows were higher than inflows. Many earlier studies have concluded that FII flows were largely influenced by the Indian stock market returns. Considering the volatile nature of FII investment flows, this study attempted to forecast FII flows in Indian stock market using an autoregressive model. Net FII investments and stock market returns data from July 2013 to December 2015 were used to estimate an autoregressive model. Net FII flows from January 2016 to June 2016 were forecasted based on the formulated estimation. The forecasted values were then compared with the actual values to verify the model's reliability. The autoregressive model used in the study was an acceptable model as forecast errors were minimal, and it captured the investment trends correctly. Forecasting the FII investments can help in better policy formulation and are useful for making strategic decisions in the capital market.

Keywords

FII Investments, Forecasting, Nifty Returns, Regression, ARCH Test

C150, C530, F 210

Paper Submission Date : June 28, 2018 ; Paper sent back for Revision : October 15, 2018 ; Paper Acceptance Date : October 26, 2018.

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  • Forecasting Foreign Institutional Investors' (FII) Investment Flows in India: An Autoregressive Model

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Authors

T. Mohanasundaram
Assistant Professor, School of Management Studies, Kongu Engineering College, Perundurai, Erode - 638 060, Tamil Nadu, India
P. Karthikeyan
Assistant Professor, School of Management Studies, Kongu Engineering College, Perundurai, Erode - 638 060, Tamil Nadu, India
D. Shanthi
Assistant Professor, Department of Management Studies, Nandha Engineering College, Erode - 638 052, Tamil Nadu, India

Abstract


India is considered as one of the fastest emerging economies in the world and a leading nation in attracting foreign investments. The country offers huge investment opportunities to reap benefits for both domestic and foreign institutional investors (FIIs) in its equity market. India's FII investments are characterized by positive net inflows in most of the years since its inception in 1992. Only during 1998-99 and 2008-09, FII outflows were higher than inflows. Many earlier studies have concluded that FII flows were largely influenced by the Indian stock market returns. Considering the volatile nature of FII investment flows, this study attempted to forecast FII flows in Indian stock market using an autoregressive model. Net FII investments and stock market returns data from July 2013 to December 2015 were used to estimate an autoregressive model. Net FII flows from January 2016 to June 2016 were forecasted based on the formulated estimation. The forecasted values were then compared with the actual values to verify the model's reliability. The autoregressive model used in the study was an acceptable model as forecast errors were minimal, and it captured the investment trends correctly. Forecasting the FII investments can help in better policy formulation and are useful for making strategic decisions in the capital market.

Keywords


FII Investments, Forecasting, Nifty Returns, Regression, ARCH Test

C150, C530, F 210

Paper Submission Date : June 28, 2018 ; Paper sent back for Revision : October 15, 2018 ; Paper Acceptance Date : October 26, 2018.




DOI: https://doi.org/10.17010/aijer%2F2018%2Fv7i5%2F139927