A Test of Using Markov-Switching GARCH Models in Oil and Natural Gas Trading

被引:13
|
作者
De la Torre-Torres, Oscar V. [1 ]
Galeana-Figueroa, Evaristo [1 ]
Alvarez-Garcia, Jose [2 ]
机构
[1] St Nicholas & Hidalgo Michoacan State Univ UMSNH, Fac Accounting & Management, Morelia 58030, Michoacan, Mexico
[2] Univ Extremadura, Fac Business Finance & Tourism, Financial Econ & Accounting Dept, Caceres 10071, Spain
关键词
Markov-switching; Markov-switching GARCH; energy futures; commodities; portfolio management; active investment; diversification; institutional investors; energy price hedging; TIME-SERIES; CONDITIONAL HETEROSKEDASTICITY; ASSET ALLOCATION; PRICES FOLLOW; STOCK-PRICES; RANDOM-WALK; PERFORMANCE; VOLATILITY; INTEGRATION; REGRESSION;
D O I
10.3390/en13010129
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
In this paper, we test the use of Markov-switching (MS) GARCH (MSGARCH) models for trading either oil or natural gas futures. Using weekly data from 7 January 1994 to 31 May 2019, we tested the next trading rule: to invest in the simulated commodity if the investor expects to be in the low-volatility regime at t + 1 or to otherwise hold the risk-free asset. Assumptions for our simulations included the following: (1) we assumed that the investors trade in a homogeneous (Gaussian or t-Student) two regime context and (2) the investor used a time-fixed, ARCH, or GARCH variance in each regime. Our results suggest that the use of the MS Gaussian model, with time-fixed variance, leads to the best performance in the oil market. For the case of natural gas, we found no benefit of using our trading rule against a buy-and-hold strategy in the three-month U.S. Treasury bills.
引用
收藏
页数:24
相关论文
共 50 条
  • [21] The functional central limit theorem for Markov-switching GARCH model
    Kwon, Dream
    Lee, Oesook
    ECONOMICS LETTERS, 2024, 238
  • [22] Using Markov-Switching Models in US Stocks Optimal Portfolio Selection in a Black-Litterman Context (Part 1)
    De la Torre-torres, Oscar V.
    Galeana-Figueroa, Evaristo
    Del Rio-Rama, Maria de la Cruz
    Alvarez-Garcia, Jose
    MATHEMATICS, 2022, 10 (08)
  • [23] Markov-Switching MIDAS Models
    Guerin, Pierre
    Marcellino, Massimiliano
    JOURNAL OF BUSINESS & ECONOMIC STATISTICS, 2013, 31 (01) : 45 - 56
  • [24] A Markov-Switching VSTOXX Trading Algorithm for Enhancing EUR Stock Portfolio Performance
    De la Torre-torres, Oscar V.
    Galeana-Figueroa, Evaristo
    Alvarez-Garcia, Jose
    MATHEMATICS, 2021, 9 (09)
  • [25] Dynamic volatility modelling of Bitcoin using time-varying transition probability Markov-switching GARCH model
    Tan, Chia-Yen
    Koh, You-Beng
    Ng, Kok-Haur
    Ng, Kooi-Huat
    NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE, 2021, 56
  • [26] Volatility Forecasting with Double Markov Switching GARCH Models
    Chen, Cathy W. S.
    So, Mike K. P.
    Lin, Edward M. H.
    JOURNAL OF FORECASTING, 2009, 28 (08) : 681 - 697
  • [27] A nesting framework for Markov-switching GARCH modelling with an application to the German stock market
    Reher, Gerrit
    Wilfling, Bernd
    QUANTITATIVE FINANCE, 2016, 16 (03) : 411 - 426
  • [28] On Markov-switching periodic ARMA models
    Aliat, Billel
    Hamdi, Faycal
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2018, 47 (02) : 344 - 364
  • [29] Spectral analysis of Markov switching GARCH models with statistical inference
    Cavicchioli, Maddalena
    SCANDINAVIAN JOURNAL OF STATISTICS, 2023, 50 (01) : 102 - 119
  • [30] Dealing with Markov-switching parameters in quantile regression models
    Kim, Yunmi
    Huo, Lijuan
    Kim, Tae-Hwan
    COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2022, 51 (11) : 6773 - 6791