FOREIGN EXCHANGE RISK MANAGEMENT : A STUDY OF INDIAN COMPANIES

Abstract

the foreign exchange risk management, the present research study conducts a secondary data analysis. The secondary data analysis focuses on the popular derivatives instruments and currencies identified from the primary analysis and uses various hedge effectiveness models to find out the effectiveness of the hedging as per these models. This analysis is conducted on time series data for forwards and futures contracts for United States Dollar (USD), Great Britain Pound (GBP) and EURO. This data is collected for daily frequencies for a period of seven years from February 2010 to December 2017. The study uses three static models and two dynamic models for this purpose. The three static models are Ordinary Least Square (OLS), Vector Autoregression (VAR) model and Vector Error Correction model (VECM) models. These models do not consider time-varying heteroskedasticity of the residual of the time series and provide one static hedge ratio, therefore are static in nature. The two dynamic models are Constant Conditional Correlation (CCC) Multivariate GARCH model and Dynamic Conditional Correlation (DCC) Multivariate GARCH model. These two models consider time-varying heteroskedasticity of the residual of the time series and provide dynamic hedge ratio to the hedgers and are therefore, dynamic in nature. The results of the analysis reveal 1-month forward contract as the effective hedging instrument and dynamic multivariate GARCH model as better model for measuring the hedge effectiveness which the companies should use. These results are shared by the treasurers who agree with the analysis but present certain challenges in adopting these results. The study then concludes by providing implications and recommendations to the companies and treasurers as well as the policy makers to rationalize the hedging process, educate the professionals on the statistical methods and foster the use of efficient hedge effectiveness methods by sensitizing the companies on appropriateness of hedge effectiveness models.