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- Title
Markov-Switching Stochastic Processes in an Active Trading Algorithm in the Main Latin-American Stock Markets.
- Authors
De la Torre-Torres, Oscar V.; Galeana-Figueroa, Evaristo; Álvarez-García, José
- Abstract
In the present paper, we review the use of two-state, Generalized Auto Regressive Conditionally Heteroskedastic Markovian stochastic processes (MS-GARCH). These show the quantitative model of an active stock trading algorithm in the three main Latin-American stock markets (Brazil, Chile, and Mexico). By backtesting the performance of a U.S. dollar based investor, we found that the use of the Gaussian MS-GARCH leads, in the Brazilian market, to a better performance against a buy and hold strategy (BH). In addition, we found that the use of t-Student MS-ARCH models is preferable in the Chilean market. Lastly, in the Mexican case, we found that is better to use Gaussian time-fixed variance MS models. Their use leads to the best overall performance than the BH portfolio. Our results are of use for practitioners by the fact that MS-GARCH models could be part of quantitative and computer algorithms for active trading in these three stock markets.
- Subjects
BELO Horizonte (Brazil); CHILE; STOCK exchanges; ALGORITHMS; COMPUTER algorithms; FINANCIAL engineering; STOCHASTIC processes
- Publication
Mathematics (2227-7390), 2020, Vol 8, Issue 6, p942
- ISSN
2227-7390
- Publication type
Article
- DOI
10.3390/math8060942