Knowledge Discovery to Support WTI Crude Oil Price Risk Management

被引:1
|
作者
Puka, Radoslaw [1 ]
Lamasz, Bartosz [1 ]
Skalna, Iwona [1 ]
Basiura, Beata [1 ]
Duda, Jerzy [1 ]
机构
[1] AGH Univ Krakow, Fac Management, PL-30059 Krakow, Poland
关键词
knowledge discovery; decision rules; crude oil price risk; commodity options; implied volatility; Greeks; decision making; HEDGING DERIVATIVE SECURITIES; IMPLIED VOLATILITY; NEURAL-NETWORKS; OPTION PRICES; MARKET; INDEX;
D O I
10.3390/en16083486
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The high volatility of commodity prices and various problems that the energy sector has to deal with in the era of COVID-19 have significantly increased the risk of oil price changes. These changes are of the main concern of companies for which oil is the main input in the production process, and therefore oil price determines the production costs. The main goal of this paper is to discover decision rules for a buyer of American WTI (West Texas Intermediate) crude oil call options. The presented research uses factors characterizing the option price, such as implied volatility and option sensitivity factors (delta, gamma, vega, and theta, known as "Greeks"). The performed analysis covers the years 2008-2022 and options with an exercise period up to three months. The decision rules are discovered using association analysis and are evaluated in terms of the three investment efficiency indicators: total payoff, average payoff, and return on investment. The results show the existence of certain ranges of the analyzed parameters for which the mentioned efficiency indicators reached particularly high values. The relationships discovered and recorded in the form of decision rules can be effectively used or adapted by practitioners to support their decisions in oil price risk management.
引用
收藏
页数:14
相关论文
共 50 条
  • [41] Are crude oil markets globalized or regionalized? Evidence from WTI and Brent
    Liao, Huei-Chu
    Lin, Shu-Chuan
    Huang, Ho-Chuan
    APPLIED ECONOMICS LETTERS, 2014, 21 (04) : 235 - 241
  • [42] WTI crude oil option implied VaR and CVaR: An empirical application
    Barone-Adesi, Giovanni
    Finta, Marinela Adriana
    Legnazzi, Chiara
    Sala, Carlo
    JOURNAL OF FORECASTING, 2019, 38 (06) : 552 - 563
  • [43] A new method for crude oil price forecasting based on support vector machines
    Xie, Wen
    Yu, Lean
    Xu, Shanying
    Wang, Shouyang
    COMPUTATIONAL SCIENCE - ICCS 2006, PT 4, PROCEEDINGS, 2006, 3994 : 444 - 451
  • [44] Assessing Potentiality of Support Vector Machine Method in Crude Oil Price Forecasting
    Yu, Lean
    Zhang, Xun
    Wang, Shouyang
    EURASIA JOURNAL OF MATHEMATICS SCIENCE AND TECHNOLOGY EDUCATION, 2017, 13 (12) : 7893 - 7904
  • [45] Managing crude oil price risk using artificial neural networks
    Najafi, H
    Rahgozar, R
    Champlin, B
    Proceedings of the IASTED International Conference on Applied Simulation and Modelling, 2004, : 83 - 90
  • [46] Extreme risk spillover between crude oil price and financial factors
    Zhao, Wan-Li
    Fan, Ying
    Ji, Qiang
    FINANCE RESEARCH LETTERS, 2022, 46
  • [47] Extreme risk spillover between crude oil price and financial factors
    Zhao, Wan-Li
    Ying, Fan
    Qiang, Ji
    FINANCE RESEARCH LETTERS, 2022, 46
  • [48] Knowledge Management in Support of Enterprise Risk Management
    Rodriguez, Eduardo
    Edwards, John S.
    INTERNATIONAL JOURNAL OF KNOWLEDGE MANAGEMENT, 2014, 10 (02) : 43 - 61
  • [49] Crude oil price dynamics with crash risk under fundamental shocks
    Hui, Cho-Hoi
    Lo, Chi-Fai
    Cheung, Chi-Hin
    Wong, Andrew
    NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE, 2020, 54
  • [50] Price volatility, hedging and variable risk premium in the crude oil market
    Jalali-Naini, Ahmad R.
    Manesh, Maryam Kazemi
    OPEC ENERGY REVIEW, 2006, 30 (02) : 55 - 70