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Artificial Neural Network and Time Series Modeling Based Approach to Forecasting the Exchange Rate in a Multivariate Framework

Journal of Insurance and Financial Management

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Title Artificial Neural Network and Time Series Modeling Based Approach to Forecasting the Exchange Rate in a Multivariate Framework
 
Creator Datta Chaudhuri, Tamal
Ghosh, Indranil
 
Description Any discussion on exchange rate movements and forecasting should include explanatory variables from both the current account and the capital account of the balance of payments. In this paper, we include such factors to forecast the value of the Indian rupee vis a vis the US Dollar. Further, factors reflecting political instability and lack of mechanism for enforcement of contracts that can affect both direct foreign investment and also portfolio investment, have been incorporated. The explanatory variables chosen are the 3 month Rupee Dollar futures exchange rate (FX4), NIFTY returns (NIFTYR), Dow Jones Industrial Average returns (DJIAR), Hang Seng returns (HSR), DAX returns (DR), crude oil price (COP), CBOE VIX (CV) and India VIX  (IV). To forecast the exchange rate, we have used two different classes of frameworks namely, Artificial Neural Network (ANN) based models and Time Series Econometric models. Multilayer Feed Forward Neural Network (MLFFNN) and Nonlinear Autoregressive models with Exogenous Input (NARX) Neural Network are the approaches that we have used as ANN models. Generalized Autoregressive Conditional Heteroskedastic (GARCH) and Exponential Generalized Autoregressive Conditional Heteroskedastic (EGARCH) techniques are the ones that we have used as Time Series Econometric methods. Within our framework, our results indicate that, although the two different approaches are quite efficient in forecasting the exchange rate, MLFNN and NARX are the most efficient.
 
Publisher Journal of Insurance and Financial Management
 
Contributor —
 
Date 2016-07-02
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://journal-of-insurance-and-financial-management.com/index.php/JIFM/article/view/46
 
Source Journal of Insurance and Financial Management; Vol 1, No 5 (2016): Journal of Insurance and Financial Management
2371-2112
 
Language eng
 
Relation https://journal-of-insurance-and-financial-management.com/index.php/JIFM/article/view/46/pdf
 
Rights Copyright (c) 2016 TAMAL DATTA CHAUDHURI, INDRANIL GHOSH
http://creativecommons.org/licenses/by/4.0