A New Approach to Infer Changes in the Synchronization of Business Cycle Phases Staff Working Paper 2014-38 Danilo Leiva-Leon This paper proposes a Markov-switching framework to endogenously identify the following: (1) regimes where economies synchronously enter recessionary and expansionary phases; and (2) regimes where economies are unsynchronized, essentially following independent business cycles. Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Regional economic developments JEL Code(s): C, C3, C32, C4, C45, E, E3, E32
The Application of Artificial Neural Networks to Exchange Rate Forecasting: The Role of Market Microstructure Variables Staff Working Paper 2000-23 Nikola Gradojevic, Jing Yang Artificial neural networks (ANN) are employed for high-frequency Canada/U.S. dollar exchange rate forecasting. ANN outperform random walk and linear models in a number of recursive out-of- sample forecasts. Content Type(s): Staff research, Staff working papers Topic(s): Exchange rates JEL Code(s): C, C4, C45, F, F3, F31
Forecasting GDP Growth Using Artificial Neural Networks Staff Working Paper 1999-3 Greg Tkacz, Sarah Hu Financial and monetary variables have long been known to contain useful leading information regarding economic activity. In this paper, the authors wish to determine whether the forecasting performance of such variables can be improved using neural network models. The main findings are that, at the 1-quarter forecasting horizon, neural networks yield no significant forecast improvements. […] Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Monetary and financial indicators JEL Code(s): C, C4, C45, E, E3, E37, E4, E44