PREDICTIVE DENSITY COMBINATION USING BAYESIAN MACHINE LEARNING
International Economic Review, EarlyView.Abstract Based on agent opinion analysis theory, Bayesian predictive synthesis (BPS) is a framework for combining predictive distributions in the face of model uncertainty. In this article, we generalize existing parametric implementations of BPS by showing how to combine competing probabilistic forecasts using interpretable Bayesian tree‐based machine
Tony Chernis +4 more
wiley +1 more source
Time-series Econometrics: Cointegration and Autoregressive Conditional Heteroskedasticity [PDF]
Advanced information on the Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel, 2003. Empirical research in macroeconomics as well as in financial economics is largely based on time series. Ever since Economics Laureate Trygve Haavelmo's
Committee, Nobel Prize
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Multivariate autoregressive conditional heteroskedasticity with smooth transitions in conditional correlations [PDF]
, 2005 In this paper we propose a new multivariate GARCH model with time-varying conditional correlation structure. The approach adopted here is based on the decomposition of the covariances into correlations and standard deviations.
Silvennoinen, Annastiina +1 more
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Systematic Features of High-Frequency Volatility in Australian Electricity Markets: Intraday Patterns, Information Arrival and Calendar Effects [PDF]
, 2004 This paper investigates the intraday price volatility process in four Australian wholesale electricity markets; namely New South Wales, Queensland, South Australia and Victoria.
Higgs, Helen, Worthington, Andrew C.
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Handling Out‐of‐Sample Areas to Estimate the Unemployment Rate at Local Labour Market Areas in Italy
International Statistical Review, EarlyView.Summary Unemployment rate estimates for small areas are used to efficiently support the distribution of services and the allocation of resources, grants and funding. A Fay–Herriot type model is the most used tool to obtain these estimates. Under this approach out‐of‐sample areas require some synthetic estimates. As the geographical context is extremely
Roberto Benedetti +4 more
wiley +1 more source
Exponential conditional volatility models [PDF]
The asymptotic distribution of maximum likelihood estimators is derived for a class of exponential generalized autoregressive conditional heteroskedasticity (EGARCH) models.
Andrew Harvey
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Wild bootstrap seasonal unit root tests for time series with periodic nonstationary volatility [PDF]
, 2017 We investigate the behavior of the well-known Hylleberg, Engle, Granger and Yoo (HEGY) regression-based seasonal unit root tests in cases where the driving shocks can display periodic nonstationary volatility and conditional heteroskedasticity.
Cavaliere, Giuseppe +2 more
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Does Dividend Policy Lead the Economy?
Journal of Money, Credit and Banking, EarlyView.Abstract I investigate the predictive role of the aggregate dividend–payout ratio (de$\textit{de}$) for future economic activity. A vector‐autoregression‐based variance decomposition shows that the main driving force of de$\textit{de}$ is long‐run predictability of earnings growth, with dividend growth predictability assuming a secondary role ...
PAULO MAIO
wiley +1 more source
A new frontier for studying within-person variability: Bayesian multivariate generalized autoregressive conditional heteroskedasticity models. [PDF]
Psychol Methods, 2022 Rast P, Martin SR, Liu S, Williams DR.
europepmc +1 more source
Grain price adjustment asymmetry: the case of cowpea in Ghana [PDF]
Patterns in price adjustment in response to information are important to market practitioners. This study looks at cowpea real wholesale price adjustment patterns in Bolgatanga, Wa, Makola and Techiman markets in Ghana.
Langyintuo, Augustine S.
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