Incorporating FX Forecast and Volatility into Bayesian Risk Management

Abstract

This paper explores the use of derivatives for managing currency risk and introduces a novel approach to enhance risk management decisions. While widely used by multinational firms to hedge financial risks, derivatives can also contribute to systemic risk, as seen in the 2008 financial crisis. The study examines the factors influencing the decision to use currency derivatives, such as managerial incentives, financial constraints, and the need to mitigate financial distress. It proposes a dynamic Bayesian model for forecasting both exchange rates and volatility, using skewed distributions instead of normal ones to better capture asymmetry in financial data. The Bayesian framework allows for real-time updates to enhance risk management accuracy. The paper also applies the model to real-world data, particularly in options pricing and currency risk management, offering insights on optimizing hedging strategies by integrating behavioral, financial, and econometric perspectives.

Keywords: Derivatives, Foreign Exchange, Risk Management, Skew-Normal Distribution, Bayesian Forecasting, Hedging Strategies JEL Classification: G15