Macroeconomic Forecasting Performance under Alternative Specifications of Time-Varying Volatility
By Todd E. Clark, Francesco Ravazzolo. 2015
296 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/b91d760ec5bdecabf31beeac58bc6a805bc3f7ec
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Joshua C. C. Chan
- Francesco Ravazzolo
- Fabian Krüger
- Florian Huber
- Martin Feldkircher
- Todd E. Clark
- Mark F. J. Steel
- Barbara Rossi
In Finance
- Joshua C. C. Chan
- Fabian Krüger
- Francesco Ravazzolo
- Todd E. Clark
- Florian Huber
- Martin Feldkircher
- Gregor Kastner
- Mark F. J. Steel
Citations in the corpus
- A MIDAS Approach to Modeling First and Second Moment Dynamics (2016, unknown): “We use the simpler SV volatility specification in our benchmark to reflect the popularity of this approach in empirical work; see Cogley et al. (2005), D'Agostino et al. (2013), Stock and Watson (2007), as well as the empirical evidence reported in Clark and Ravazzolo (2014).”
- Bayesian Model Comparison for Time-Varying Parameter VARs with Stochastic Volatility (2018, unknown): “…variables.1 In addition, models with time-varying parameters and stochastic volatility are often found to forecast better than their constant-coefficient counterparts, as demonstrated in papers such as Clark (2011), D'Agostino, Gambetti, and Giannone (2013), and Clark and Ravazzolo (2015).”
- The Stochastic Volatility in Mean Model With Time-Varying Parameters: An Application to Inflation Modeling (2017, background): “Recent articles include Canova (2007), Koop and Potter (2007), Stock and Watson (2007, 2010), Clark and Doh (2014), Chan et al. (2012), Koop and Korobilis (2012), Koop and Korobilis (2013), Chan (2013), D’Agostino, Gambetti, and Giannone (2013), and Clark and Ravazzolo (2015).”
- Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts (2014, methodology): “We focus on forecasts from a BVAR with random walk stochastic volatility, the specification that Clark and Ravazzolo (2015) found to perform relatively well in a comparison of the forecasting performance (both point and density—stochastic volatility is particularly important for density accuracy)…”
- Adaptive Shrinkage in Bayesian Vector Autoregressive Models (2019, background): “A plethora of recent studies (see, among others, Giordani and Villani 2010; Clark 2011; Groen, Paap, and Ravazzolo 2013; Clark and Ravazzolo 2015; Carriero, Clark, and Marcellino 2016) emphasize the importance of allowing for heteroscedasticity in a VAR framework to improve inference and obtain…”