Point and density prediction of intra-day volume using Bayesian linear ACV models: evidence from the Polish stock market

DOI10.1080/14697688.2017.1414491zbMath1400.91548OpenAlexW2794279843MaRDI QIDQ4554455

Roman Huptas

Publication date: 14 November 2018

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/14697688.2017.1414491

zbMATH Keywords

Bayesian analysisforecastingmarket microstructurehigh frequencyACV modeltraded volume

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Portfolio theory (91G10)

Cites Work

• Unnamed Item
• Bayesian estimation and inference for log-ACD models
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• The stochastic conditional duration model: a latent variable model for the analysis of financial durations
• Sampling-Based Approaches to Calculating Marginal Densities
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
• The Price Variability-Volume Relationship on Speculative Markets
• Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data
• Probabilistic Forecasts, Calibration and Sharpness
• Monte Carlo sampling methods using Markov chains and their applications
• A Bayesian approach for capturing daily heterogeneity in intra-daily durations time series

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