Abstract
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.
Highlights
Energy futures, such as oil and natural gas, are a widely used means for hedging the commodity price risk and for investing and speculation
We found increasing literature related to testing the use of MS, GARCH, and MSGARCH models in European and emerging stock markets [41,44,45]
From the perspective of the use of MS and MSGARCH models in other types of time series, we found the works of Alexander and Kaeck [54] and Ma and Deng [55]
Summary
Energy futures, such as oil and natural gas, are a widely used means for hedging the commodity price risk and for investing and speculation. Given their close relationship with economic activity and general prices, energy commodities (especially oil) have been a source of portfolio diversification. The diversification benefit for a portfolio is observed only with agricultural commodities [4] and other types of alternative assets, such as real estate [5], hedge funds [6], volatility futures [3], or clean-energy (technology) stocks [7]. The issue of a diversified portfolio has been tested in several academic reviews, such as in [2,8,9] which are some of the most recent ones
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