RT Journal Article T1 A two-regime Markov-switching GARCH active trading algorithm for coffee, cocoa, and sugar futures A1 De la Torre Torres, Oscar V. A1 Aguilasocho Montoya, Dora A1 Del Rio Rama, María de la Cruz K1 5307.04 Estudios del desarrollo Económico K1 5307.06 Fluctuaciones Económicas K1 5302 Econometría AB In the present paper we tested the use of Markov-switching Generalized AutoRegressive Conditional Heteroscedasticity (MS-GARCH) models and their not generalized (MS-ARCH) version. This, for active trading decisions in the coffee, cocoa, and sugar future markets. With weekly data from 7 January 2000 to 3 April 2020, we simulated the performance that a futures’ trader would have had, had she used the next trading algorithm: To invest in the security if the probability of being in a distress regime is less or equal to 50% or to invest in the U.S. three-month Treasury bill otherwise. Our results suggest that the use of t-student Markov Switching Component ARCH Model (MS-ARCH) models is appropriate for active trading in the cocoa futures and the Gaussian MS-GARCH is appropriate for sugar. For the specific case of the coffee market, we did not find evidence in favor of the use of MS-GARCH models. This is so by the fact that the trading algorithm led to inaccurate trading signs. Our results are of potential use for futures’ position traders or portfolio managers who want a quantitative trading algorithm for active trading in these commodity futures. PB Mathematics SN 22277390 YR 2020 FD 2020-06-18 LK http://hdl.handle.net/11093/1877 UL http://hdl.handle.net/11093/1877 LA eng NO Mathematics, 8(6): 1001 (2020) DS Investigo RD 04-dic-2024