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VOL. 10, ISSUE 1 (2024)
Predictive analysis of FDI inflow in India: A neural network approach
Authors
K Y Ingale, S V Bharati, P V Karale
Abstract
India is a promptly developing country which is often seen as an
investment basement by the industry giants of foreign countries. The recent
trends show an exponential increase in the net foreign direct investment in India
from the year 2010-2023. Thus, prediction of the future inflows of Foreign
Direct Investment (FDI) for the policy makers and the economist to design
effective policies and take better decisions. The result of the better policies
would help to deal the unbalanced market viability. NNAR modelling is a technique
used in statistics and machine learning which harness the advantages of both
Auto Regression (AR) and Neural Network (NN) models by integrating them
together to form Neural Network Autoregressive model. The present study based
on data regarding FDI inflow from 2001-2023 which aims to generate a customised
said model for forecasting and analysing the trend of FDI in India. It proposes
NNAR (2,2) model for optimal forecasting of net FDI inflow in India.
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Pages:1-3
How to cite this article:
K Y Ingale, S V Bharati, P V Karale "Predictive analysis of FDI inflow in India: A neural network approach". International Journal of Commerce and Management Research, Vol 10, Issue 1, 2024, Pages 1-3
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