Bayesian Model Averaging and exchange rate forecasts

By Jonathan H. Wright. 2003

290 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/1274dd9c645140169a5b326205ad8eea86309f49

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In Economics and Econometrics

In Management Science and Operations Research

Citations in the corpus

On the sources of uncertainty in exchange rate predictability (2018, unknown): “16Our results on the performance of BMA excluding TVar-Coeffs are coherent with those from Wright (2008).”
How Useful is Bagging in Forecasting Economic Time Series? A Case Study of US CPI Inflation (2005, unknown): “This empirical example is in the spirit of recent work by Stock andWatson (1999), Bernanke and Boivin (2003), Forni et al. (2003), and Wright (2003b), among others.”
Model Averaging and Its Use in Economics (2017, methodology): “ by many panel data applications: high model uncertainty, presence of slope heterogeneity, and potential divergence in short-run and long-run effects”. The use of BMA in forecasting exchange rates by Wright (2008) leads to the conclusion that BMA provides slightly better out-of-sample forecasts (mea”
Forecasting the realized range-based volatility using dynamic model averaging approach (2017, methodology): “This problem can be overcome by Bayesian model averaging (BMA) and Bayesian model selection (BMS) procedures (Cremers, 2002; Koop and Potter, 2004; Wright, 2008).”
Dynamic Prediction Pools: An Investigation of Financial Frictions and Forecasting Performance (2016, unknown): “Forecasting applications in the econometrics literature include, among others, Min and Zellner (1993) and Wright (2008).”
Exchange Rate Predictability (2013, unknown): “…contemporaneous fundamental model is estimated with OLS whereas the cointegrating vector in the ECM model is estimated via the Johansen procedure; Wright (2008) also includes the ratio of the current account to output among the regressors; in Adrian et al. (2011), the repo- and commercial paper…”
Advances in Forecasting Under Instability (2012, unknown): “Wright (2008) nds that BMA is quite useful for predicting exchange rates out-of-sample.”
Forecasting with Many Predictors (2006, methodology): “Wright (2003) focuses on the problem of forecasting four exchange rates using n = 10 predictors, for a variety of values of g.”
Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version (2013, unknown): “The BMA has been widely used in econometric applications, including Sala-iMartin, Doppelhofer, and Miller (2004), Brock and Durlauf (2001), Brock, Durlauf, and West (2003), Avramov (2002), Fernandez, Lay, and Steel (2001a,b), Garratt, Lee, Pesaran, and Shin (2003), and Wright (2008, 2009).”
A Comprehensive Look at Financial Volatility Prediction by Economic Variables (2011, unknown): “Wright (2008) studies the predictability of exchange rates in a data-rich forecasting environment.”
Forecast Combination and Bayesian Model Averaging - A Prior Sensitivity Analysis (2012, unknown): “Wright (2003) relied in a classical setting on the BMA paradigm forecasting foreign exchange rates.”
Forecast combinations: An over 50-year review (2022, methodology): “The BMA procedure is consistent in the sense that the posterior probability in Equation (17) indicates the probability that model Mi is the best under the KLIC measure distance and shows how well the model fits the observations (Fernández-Villaverde and Rubio-Ramırez, 2004; Raftery et al., 2005; Wri”