Commodity derivatives pricing with cointegration and stochastic covariances

被引:17
|
作者
Chiu, Mei Choi [1 ]
Wong, Hoi Ying [2 ]
Zhao, Jing [3 ]
机构
[1] Hong Kong Inst Educ, Dept Math & Informat Technol, Tai Po, Hong Kong, Peoples R China
[2] Chinese Univ Hong Kong, Dept Stat, Shatin, Hong Kong, Peoples R China
[3] La Trobe Univ, Dept Finance, Bundoora, Vic 3086, Australia
关键词
Option pricing; Cointegration; Stochastic covariance; Stochastic convenience yield; VARIANCE PORTFOLIO SELECTION; OPTION VALUATION; ERROR CORRECTION; MEAN REVERSION; VOLATILITY; FUTURES; PRICES; EQUILIBRIUM; PREMIUMS; BEHAVIOR;
D O I
10.1016/j.ejor.2015.05.012
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Empirically, cointegration and stochastic covariances, including stochastic volatilities, are statistically significant for commodity prices and energy products. To capture such market phenomena, we develop a continuous-time dynamics of cointegrated assets with a stochastic covariance matrix and derive the joint characteristic function of asset returns in closed-form. The proposed model offers an endogenous explanation for the stochastic mean-reverting convenience yield. The time series of spot and futures prices of WTI crude oil and gasoline shows cointegration relationship under both physical and risk-neutral measures. The proposed model also allows us to fit the observed term structure of futures prices and calibrate the marketimplied cointegration relationship. We apply it to value options on a single commodity and on multiple commodities. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
引用
收藏
页码:476 / 486
页数:11
相关论文
共 50 条
  • [41] Pricing commodity futures options in the Schwartz multi factor model with stochastic volatility: An asymptotic method
    Chen, Jilong
    Ewald, Christian-Oliver
    INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS, 2017, 52 : 144 - 151
  • [42] Commodity market flexibility and financial derivatives
    Tvedt, Jostein
    JOURNAL OF COMMODITY MARKETS, 2020, 18
  • [43] Financialization, common stochastic trends, and commodity prices
    Kupabado, Moses M.
    Kaehler, Juergen
    JOURNAL OF FUTURES MARKETS, 2021, 41 (12) : 1988 - 2008
  • [44] A comparison of pricing and hedging performances of equity derivatives models
    Lassance, Nathan
    Vrins, Frederic
    APPLIED ECONOMICS, 2018, 50 (10) : 1122 - 1137
  • [45] Pricing temperature derivatives with a filtered historical simulation approach
    Zhou, Rui
    Li, Johnny Siu-Hang
    Pai, Jeffrey
    EUROPEAN JOURNAL OF FINANCE, 2019, 25 (15) : 1462 - 1484
  • [46] Analytical Formulas Using Affine Transformation for Pricing Generalized Swaps in Commodity Markets with Stochastic Convenience Yields
    Duangpan, Ampol
    Boonklurb, Ratinan
    Rakwongwan, Udomsak
    Sutthimat, Phiraphat
    SYMMETRY-BASEL, 2022, 14 (11):
  • [47] MODELLING THE RAND AND COMMODITY PRICES: A GRANGER CAUSALITY AND COINTEGRATION ANALYSIS
    Schaling, Eric
    Ndlovu, Xolani
    Alagidede, Paul
    SOUTH AFRICAN JOURNAL OF ECONOMIC AND MANAGEMENT SCIENCES, 2014, 17 (05): : 673 - 690
  • [48] The Classical and Stochastic Approach to Option Pricing
    Benada, Ludek
    Cupal, Martin
    EUROPEAN FINANCIAL SYSTEMS 2014, 2014, : 49 - 55
  • [49] Valuation of commodity derivatives with an unobservable convenience yield
    Anh Ngoc Lai
    Mellios, Constantin
    COMPUTERS & OPERATIONS RESEARCH, 2016, 66 : 402 - 414
  • [50] Stochastic model genetic programming: Deriving pricing equations for rainfall weather derivatives
    Cramer, Sam
    Kampouridis, Michael
    Freitas, Alex A.
    Alexandridis, Antonis
    SWARM AND EVOLUTIONARY COMPUTATION, 2019, 46 : 184 - 200