Combinations of a six-Currency portfolio are studied for a two-year period to access the reliability of “value at risk” approach to measuring the transaction exposure. The values at risk for each currency and for every additional currency portfolio are estimated for each year. The outcomes...

Traditional Monte Carlo simulation using linear correlations induces estimation bias in measuring portfolio value-at-risk (VaR) due to the well-documented existence of fat-tail, skewness, truncations, and non-linear relations of return distributions. In this paper, we evaluate the effectiveness...

The tail of financial returns is typically governed by a power law (i.e. “fat tails”). However, the constancy of the so-called tail index α which dictates the tail decay has been hardly investigated. We study the finite sample properties of some recently proposed endogenous tests for...

This article presents an overview of widely practiced short-term multi-currency investment strategies such as carry trade, momentum and term spread strategies. We provide evidence on their downside risk properties and illustrate their performance over historical episodes of financial market...

Blejer and Schumacher (1999) were the first to suggest that Central Bank's Value at Risk (VaR), a widely used composite measure of potential portfolio losses in the corporate sector, could be used as an early warning indicator of financial crises. We extend their research in two aspects. First,...

Corporate FX risk management has gained complexity with increased number of currencies involved and varying correlations among them. Existing literature has highlighted the need to account for cross-currency correlations when optimizing hedge ratios for portfolio management (Dowd, 1999). In this...

A plethora of academic papers on generalized autoregressive conditional heteroscedasticity (GARCH) models for bitcoin and other cryptocurrencies have been published in academic journals. Yet few, if indeed any, of these are employed by practitioners. Previous academic studies produce results...

Regular or automated processes require reliable software applications that provide accurate volatility and Value-at-Risk forecasts. The univariate and multivariate GARCH models proposed in the literature are reviewed and the suitability of selected R functions for automated forecasting systems...