Forecast density combinations of dynamic models and data driven portfolio strategies

DOI10.1016/J.JECONOM.2018.11.011zbMath1452.62742OpenAlexW2901112082WikidataQ128959850 ScholiaQ128959850MaRDI QIDQ1740348

Xianqiang Yang

Publication date: 30 April 2019

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://research.vu.nl/ws/files/120540230/Forecast_density_combinations_of_dynamic_models_and_data_driven_portfolio_strategies.pdf

zbMATH Keywords

forecast combinationfiltering methodsBayes estimatesmomentum strategy

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20) Applications of statistics to actuarial sciences and financial mathematics (62P05) Bayesian inference (62F15)

Related Items (4)

Partially censored posterior for robust and efficient risk evaluation ⋮ A flexible predictive density combination for large financial data sets in regular and crisis periods ⋮ Editorial introduction on complexity and big data in economics and finance: recent developments from a Bayesian perspective ⋮ Sparse Bayesian time-varying covariance estimation in many dimensions

Cites Work

• Unnamed Item
• Unnamed Item
• Dynamic prediction pools: an investigation of financial frictions and forecasting performance
• Efficient high-dimensional importance sampling
• A class of adaptive importance sampling weighted EM algorithms for efficient and robust posterior and predictive simulation
• Confronting model misspecification in macroeconomics
• Optimal prediction pools
• Recursive Monte Carlo filters: algorithms and theoretical analysis
• Time-varying combinations of predictive densities using nonlinear filtering
• Finite mixture and Markov switching models.
• Sequential Monte Carlo Methods in Practice
• Bayesian Inference in Mixtures-of-Experts and Hierarchical Mixtures-of-Experts Models With an Application to Speech Recognition
• Filtering via Simulation: Auxiliary Particle Filters
• Particle Markov Chain Monte Carlo Methods
• Invariant Inference and Efficient Computation in the Static Factor Model
• A Survey of Sequential Monte Carlo Methods for Economics and Finance
• Structural Learning with Time-Varying Components: Tracking the Cross-Section of Financial Time Series
• Common risk factors in the returns on stocks and bonds
• Monte Carlo strategies in scientific computing

This page was built for publication: Forecast density combinations of dynamic models and data driven portfolio strategies