Forecasting Exchange Rates: A Robust Regression Approach

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Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction (2011, background): “There is evidence of substantial theoretical progress in NNs, in forecasting both single time series (see for example de Menezes & Nikolaev, 2006, Preminger & Franck, 2007 and Terasvirta, van Dijk, & Medeiros, 2005) and representative sets of empirical time series (see, e.g., Liao & Fildes, 2005,…”
Robust Forecasting of Dynamic Conditional Correlation GARCH Models (2013, background): “Loss function: In the presence of outliers (or jumps), Preminger and Franck (2007) recommend using forecast performance evaluation criteria that are less sensitive to extreme observations.”
Using artificial neural network models in stock market index prediction (2011, methodology): “Preminger and Franck (2007) used a robust linear autoregressive and a robust neural network model to forecast exchange rates.”