Stochastic resonance of drawdown risk in energy market prices

Yang Dong, Shu-hui Wen, Xiao-bing Hu and Jiang-Cheng Li

Physica A: Statistical Mechanics and its Applications, 2020, vol. 540, issue C

Abstract: We investigate the stochastic resonance dynamic behavior characteristics of price drawdown time series driven by internal and external periodic information and discuss the influence of information resonance on price drawdown risk, based on price drawdown, periodic Heston model and signal power amplification. A theoretical model of the periodic price drawdown time series is proposed to describe the energy price drawdown time series with the periodic Heston model. Then the signal power amplification (SPA) is employed to measure the stochastic resonance phenomenon in the internal and external periodic information environment of complex energy dynamics system. Combined with the real data of WTI spot price of NYMEX, the least square method of drawdown time series distribution is used to estimate the parameters of the model. The probability density functions of drawdown between the theoretical model and the real data are compared, and a good agreement can be found between both the simulated data from the proposed model and the real data. After the stochastic simulation of signal power amplification under internal and external periodic information respectively, the results show that: (i) In the functions of SPA versus price volatility parameters (noise correlation strength or periodic information strength), inverse resonance phenomenon can be observed, that is to say, there is the best system price volatility parameter, noise correlation strength and information strength corresponding to the least risk of the price drawdown; (ii) In the SPA versus amplitude of volatility fluctuations, the correlation induce multiple inverse stochastic resonance phenomenon can be observed; (iii) The increase of growth rate strengthens SPA and weakens drawdown risk of energy market prices.

Keywords: Econophysics; Financial market; Maximum drawdown; Signal power amplification; Stochastic resonance (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437119317479
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:540:y:2020:i:c:s0378437119317479

DOI: 10.1016/j.physa.2019.123098

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().