Volatility aggregation intensity energy futures series on stochastic finite-range exclusion dynamics
Authored by Jun Wang, Linlu Jia, Jinchuan Ke
Date Published: 2019
DOI: 10.1016/j.physa.2018.09.083
Sponsors:
Chinese National Natural Science Foundation
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
The stochastic finite-range exclusion process, one of statistical
physics systems, is introduced to construct a new agent-based financial
price model to study the mechanism of market dynamics. A novel
volatility aggregation intensity (VAI) time series, describing the
fluctuation aggregation intensity of the volatility series, is developed
for further investigating the nonlinear volatility behaviors in energy
markets. For studying the proposed VAI series and the proposed price
model, the New York Mercantile Exchange energy futures data is selected
and analyzed. Further, cross-correlation analysis, auto-correlation
analysis with multiscale, and multifractal detrended fluctuation
analysis are applied to analyze the correlation, volatility-clustering
and multifractal natures of the VAI time series. The empirical results
show that the proposed model has the parallel behaviors with the
authentic markets, indicating that it is rational and available. The new
concept of VAI series is of great value and can enrich the study of
volatility behaviors in energy markets to some extent. (C) 2018 Elsevier
B.V. All rights reserved.
Tags
Long memory
Agent-based
models
Stock-market
Percolation system
Volatility aggregation intensity
Statistical physics system
Finite-range exclusion process
Financial price model
Cross-correlation
Volatility-clustering
Mfdfa
Detrended cross-correlation
Nonstationary time-series
Financial dynamics
Nonlinear complexity
Fluctuation analysis
Return intervals