In this paper, we challenge the traditional assumption of a linear relationship between exchange rate volatility and economic growth in South Africa. By using data collected from 1970 to 2016 applied to a smooth transition regression (STR) model, we are able to prove that the exchange...

Increased sovereign credit risk is often associated with sharp currency movements. Therefore, expectations of the probability of a sovereign default event can convey important information regarding future movements of exchange rates. In this paper, we investigate the possible pass-through of...

In this paper, we challenge the traditional assumption of a linear relationship between exchange rate volatility and economic growth in South Africa. By using data collected from 1970 to 2016 applied to a smooth transition regression (STR) model, we are able to prove that the exchange...

A practice that has become widespread and widely endorsed is that of evaluating forecasts of financial variability obtained from discrete time models by comparing them with high-frequency ex post estimates (e.g. realised volatility) based on continuous time theory. In explanatory financial...

In this paper, we present a novel machine learning based forecasting system of the EU/USD exchange rate directional changes. Specifically, we feed an overcomplete variable set to a Support Vector Machines (SVM) model and refine it through a Sensitivity Analysis process. The dataset spans from...

The 2008 financial crisis has rekindled interest in the issue of early warning signals (EWS) of financial distress. It has also triggered renewed interest in the literature on currency crises, with many countries, especially among emerging market economies, experiencing severe exchange market...

This paper demonstrates that "commodity currency" exchange rates have remarkably robust power in predicting future global commodity prices, both in sample and out-of-sample. A critical element of our in-sample approach is to allow for structural breaks, endemic to empirical exchange rate models,...

Many researchers use GARCH models to generate volatility forecasts. Using data on three major U.S. dollar exchange rates we show that such forecasts are too high in volatile periods. We argue that this is due to the high persistence of shocks in GARCH forecasts. To obtain more flexibility...

Long-range persistence in volatility is widely modelled and forecasted in terms of the so-called fractional integrated models. These models are mostly applied in the univariate framework, since the extension to the multivariate context of assets portfolios, while relevant, is not...

In this study, a vector autoregression (VAR) model with time-varying parameters (TVP) to predict the daily Indian rupee (INR)/US dollar (USD) exchange rates for the Indian economy is developed. The method is based on characterization of the TVP as an optimal control problem. The methodology is a...