Showing 1 - 10 of 1,052
This paper applies Markov-switching multifractal (MSM) processes to model and forecast carbon dioxide (CO2) emission price volatility, and compares their forecasting performance to the standard GARCH, fractionally integrated GARCH (FIGARCH) and the two-state Markov-switching GARCH (MS-GARCH)...
Persistent link: https://www.econbiz.de/10011296114
Evidence in favor of the monetary model of exchange rate determination for the South African Rand is, at best, mixed. A co-integrating relationship between the nominal exchange rate and monetary fundamentals forms the basis of the monetary model. With the econometric literature suggesting that...
Persistent link: https://www.econbiz.de/10009770376
generalized tempering for "online" estimation, and provide examples of multimodal posteriors that are well captured by SMC methods …. We then use the online estimation of the DSGE model to compute pseudo-out-of-sample density forecasts of DSGE models with …
Persistent link: https://www.econbiz.de/10012038824
This paper develops and illustrates a simple method to generate a DSGE model-based forecast for variables that do not explicitly appear in the model (non-core variables). We use auxiliary regressions that resemble measurement equations in a dynamic factor model to link the non-core variables to...
Persistent link: https://www.econbiz.de/10014214672
Persistent link: https://www.econbiz.de/10014529004
Yes, they do. Utilizing a machine-learning technique known as random forests to compute forecasts of realized (good and bad) stock market volatility, we show that incorporating the information in lagged industry returns can help improve out-of sample forecasts of aggregate stock market...
Persistent link: https://www.econbiz.de/10013249490
This paper uses the Markov-switching multifractal (MSM) model and generalized autoregressive conditional heteroscedasticity (GARCH)-type models to forecast oil price volatility over the time periods from January 02, 1875 to December 31, 1895 and from January 03, 1977 to March 24, 2014. Based on...
Persistent link: https://www.econbiz.de/10010488966
We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call dynamic pools, and use it to investigate the relative forecasting performance of dynamic stochastic general equilibrium (DSGE) models, with and without financial frictions, for output...
Persistent link: https://www.econbiz.de/10010414783
This paper develops and applies tools to assess multivariate aspects of Bayesian Dynamic Stochastic General Equilibrium (DSGE) model forecasts and their ability to predict comovements among key macroeconomic variables. The authors construct posterior predictive checks to evaluate the calibration...
Persistent link: https://www.econbiz.de/10013131251
This paper develops and applies tools to assess multivariate aspects of Bayesian Dynamic Stochastic General Equilibrium (DSGE) model forecasts and their ability to predict comovements among key macroeconomic variables. We construct posterior predictive checks to evaluate conditional and...
Persistent link: https://www.econbiz.de/10013106990