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Forecasting the INR/USD Exchange Rate: A BVAR Framework

In: Macroeconometric Methods

Author

Listed:
  • Pami Dua

    (University of Delhi)

  • Rajiv Ranjan

    (Reserve Bank of India)

  • Deepika Goel

    (Aryabhatta College, University of Delhi)

Abstract

This paper uses vector autoregression and Bayesian vector autoregression techniques to forecast the Indian Re/US dollar exchange rate. It extends the Dua and Ranjan (2010, 2012) model by including the domestic–foreign differential of the rate of return in stock prices as well as global oil prices as determinants of the exchange rate in addition to monetary model fundamentals (i.e. differential in money supply, interest rate and inflation), forward premium, volatility of capital flows, order flows and central bank intervention. The estimation period is July 1996–January 2017, while an analysis of the out-of-sample forecasting performance is undertaken from February 2017 to January 2019. The main findings are as follows: (i) Granger causality tests reveal that the exchange rate is granger caused by all the determinants considered, including differential of the rate of return of stock prices and global oil prices. (ii) Forecast accuracy of the extended model that includes stock market information and global oil prices is somewhat better than Dua and Ranjan (2010, 2012) model, especially at the longer end. (iii) Bayesian vector autoregressive models generally outperform their corresponding VAR variants. (iv) Turning points are difficult to predict.

Suggested Citation

  • Pami Dua & Rajiv Ranjan & Deepika Goel, 2023. "Forecasting the INR/USD Exchange Rate: A BVAR Framework," Springer Books, in: Pami Dua (ed.), Macroeconometric Methods, chapter 0, pages 183-224, Springer.
    • Handle: RePEc:spr:sprchp:978-981-19-7592-9_8
    DOI: 10.1007/978-981-19-7592-9_8
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    More about this item

    Keywords

    Exchange rate; VAR and BVAR models; Forecasting; Stock price differential; Oil prices;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

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