Most operations models assume individuals make decisions based on a perfect understanding of random variables or stochastic processes. In reality, however, individuals are subject to cognitive limitations and make systematic errors. We leverage established psychology on sample naivete to model...

A time series investigation of how the historic rates of default for corporate and retail credit exposures in three small Bulgarian banks is linked to the evolution of basic macroeconomic parameters. The result is a model which produces forecasts for probability of default based on economic outlook

This study tries to predict as accurately as possible CDS risk premia for BRICS countries by utilizing state-of-the-art recurrent neural network architectures. These are ELMAN, NARX, GRU, and LSTM RNNs in the time series setting, taking into account both local and global features. The predictive...

In this paper, we empirically assess the predictive accuracy of a large group of models based on the use of principle components and other shrinkage methods, including Bayesian model averaging and various bagging, boosting, LASSO and related methods. Our results suggest that model averaging does...

In this paper, we empirically assess the predictive accuracy of a large group of models based on the use of principle components and other shrinkage methods, including Bayesian model averaging and various bagging, boosting, LASSO and related methods Our results suggest that model averaging does...

Why should we be interested in macroeconomic survey expectations? This important book offers an in-depth treatment of this question from a point of view not covered in existing works on time-series econometrics and forecasting. Clements presents the nature of survey data, addresses some of the...

This paper documents a new stylized fact of the greater macroeconomic stability of the U.S. economy over the last two decades. Using 131 monthly time series, three popular statistical methods and the forecasts of the Federal Reserve's Greenbook and the Survey of Professional Forecasters, we show...