Safe marginal time of crude oil price via escape problem of econophysics

Jiang-Cheng Li, Na Leng, Guang-Yan Zhong, Yu Wei and Jia-Sheng Peng

Chaos, Solitons & Fractals, 2020, vol. 133, issue C

Abstract: Market timing for determining the trading time point and the measurement and prediction of safe holding time is of great theoretical significance and practical value in risk management. Based on statistical physics and escape problems, we put forward the safe marginal time to depict the trading safe area and holding time size, and the theoretical method for risk management is given. Combining with the NYMEX crude oil price index, we make a comparative study between the theoretical and real results of the safe marginal time series. Then we further discuss the predictability of the safe marginal time series through the method of information entropy. The results indicate: (1) the characteristics of safe marginal time is an exponential distribution; (2) the marginal time of safety is positively correlated with price return and negatively correlated with risk; (3) there is an optimal critical initial return that maximizes the expectation and variance of the safe marginal time. In addition, the predictability of safe marginal time has a nonlinear relationship with transaction conditions, and there are some optimal trading conditions that greatly enhances the predictability of safe marginal time. This study provides a method to deal with time series and measure risks from the perspective of safe marginal time. It can provide a reference for investors to measure and predict risks and provide early warning from the perspective of safe marginal time for risk management.

Keywords: Safe marginal time; Econophysics; Crude oil price; Entropy and predictability; Escape theory (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S096007792030059X
Full text for ScienceDirect subscribers only

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:chsofr:v:133:y:2020:i:c:s096007792030059x

DOI: 10.1016/j.chaos.2020.109660

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().