Developing a Volume Forecasting Model

This study builds a series of models to predict trading volume in European markets using different statistical methods. The analysis considers a number of aspects, such as special events (e.g. MSCI rebalances, futures expiries, or cross-market holidays), day-of-the-week effects, and the volume-price...

Full description

Saved in:
Bibliographic Details
Published in:Journal of applied finance and banking 2017-01, Vol.7 (1), p.1
Main Authors: Batrinca, Bogdan, Hesse, Christian W, Treleaven, Philip C
Format: Article
Language:English
Subjects:
Asymmetry
Breakdowns
Business metrics
Economic models
Feature selection
Futures
Holidays & special occasions
Machine learning
Statistical analysis
Statistical methods
Stock exchanges
Studies
Time series
Trends
Volatility
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This study builds a series of models to predict trading volume in European markets using different statistical methods. The analysis considers a number of aspects, such as special events (e.g. MSCI rebalances, futures expiries, or cross-market holidays), day-of-the-week effects, and the volume-price relation asymmetry, in order to perform contextual one-step ahead prediction. We investigate the prediction error for each calendar circumstance to infer a cross-stock event-oriented switching model for volume prediction. The study concludes by proposing a stock-specific out-of-sample metamodel that is fit by selecting an initial stock-specific model yielding the best performance for the most recent observations.
ISSN:1792-6580
1792-6599