I use a real-time quantile-regression approach to analyze whether commodity prices have predictive value for movements of the Australian real effective exchange rate. To do so, I use a modified version of Frankel's (1986, 2008, 2014) and Frankel and Rose's (2010) model of commodity price...

Weekends and holidays lead to gaps in daily financial data. Standard models ignore these irregularities. Because this issue is particularly important for persistent time series, we focus on volatility modelling, specifically modelling of realized volatility. We suggest a simple way of adjusting...

We forecast the realized and median realized volatility of agricultural commodities using variants of the Heterogeneous AutoRegressive (HAR) model. We obtain tick-by-tick data for five widely traded agricultural commodities (Corn, Rough Rice, Soybeans, Sugar, and Wheat) from the CME/ICE. Real...

We investigate the directional accuracy of exchange rate forecasts by corporate executives. We find that a forecast with a 1-year horizon is valuable for the profitability and unprofitability predictions of manufacturers, although previous studies provide considerable evidence that forecasts...

This paper builds two factor discrete time models in order to investigate the effect of sovereign risk on the nominal exchange rates in a Markov switching framework. The empirical section of the paper uses seven currencies from Chile, the Czech Republic, Hungary, Iceland, Japan, Korea, and...

The main goal of this research is to construct and assess forecast intervals for monthly US/EURO foreign exchange rate. The point forecasts used to build the intervals are based on a vector autoregression (VAR model) and on a Bayesian VAR model for data starting with the first month of 1999. The...

In recent years support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a moving...

This paper provides empirical evidence that combinations of option implied and time series volatility forecasts that are conditional on current information are statistically superior to individual models, unconditional combinations, and hybrid forecasts. Superior forecasting performance is...

In this paper we undertake an out-of-sample evaluation of the ability of a model to forecast the Swedish Krona’s real and nominal effective exchange rate, using a cointegrating relation between the real exchange rate, relative output, terms of trade and net foreign assets (or alternatively the...

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...