Manuscript Number : GISRRJ19263

Comparative Autocorrelation Study for Foreign Exchange Reserve and Merchandise Export in India : Development of Prediction Model

Authors(1) :-Avik Ghosh

The research is having an objective to analyse the monthly data of Foreign Exchange Reserve of India and merchandise export from India since 1990-91. The analysis was aimed at finding an autocorrelation of the said variables. Both the variables are considerably significant in the broader domain of macroeconomic framework. Foreign exchange reserve classifies the strength of government reserve in other currencies to mitigate unforeseen circumstances whereas higher export value signifies better current account and trade position. These parameters have strong correlation with the exchange rate of home currency and on the balance of payment. The degree of autocorrelation exemplifies the dependence of these variables on their past outcome. This study tested the autocorrelation of the variables successfully and through the detailed statistical methodology of unit root testing, ARMA modelling and GARCH modelling, it established a statistical model that emanates the possibility to forecast the variables. This outcome may have significant impact in policy making and predicting future trade trend.

Authors and Affiliations

Avik Ghosh
CMA, B.E. (Electrical), JAIIB, CAIIB, Diploma in Investment Law, India

Foreign Exchange Reserve in India, Export from India, Autocorrelation, Unit Root Test, ARMA model, GARCH model, EGARCH model

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Publication Details

Published in : Volume 2 | Issue 6 | November-December 2019
Date of Publication : 2019-12-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 28-33
Manuscript Number : GISRRJ19263
Publisher : Technoscience Academy

ISSN : 2582-0095

Cite This Article :

Avik Ghosh, "Comparative Autocorrelation Study for Foreign Exchange Reserve and Merchandise Export in India : Development of Prediction Model", Gyanshauryam, International Scientific Refereed Research Journal (GISRRJ), ISSN : 2582-0095, Volume 2, Issue 6, pp.28-33, November-December.2019
URL : https://gisrrj.com/GISRRJ19263

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