期刊名称：International Journal of Combinatorial Optimization Problems and Informatics
印刷版ISSN：2007-1558
电子版ISSN：2007-1558
出版年度：2017
卷号：8
期号：2
页码：10-18
语种：English
出版社：International Journal of Combinatorial Optimization Problems and Informatics
其他摘要：The behavior of stoc k exchanges around the world has an important role in the financial development of countries . The Mexican Stock Exchange (BMV , for its acronym in Spanish ) is the financial entity in Mexico where investors build and manage investment portfolios to generate profit. Financial time series forecasting is an important problem for investment portfolios creation and optimization becaus e it allows them to have a prediction of the value of investment assets over time, therefore reducing at some extent the uncertainty of these operations . Classical models, such as ARIMA, artificial neural networks and support vector machines, are usually used as forecast ing tools. In this pap er , we forecast financial time series of the BMV using a hybrid parallel algorithm that employs both simulated annealing (SA) and support vector machines for regression (SVR). Finally, the resulting Mean Absolute Percent Error (MAPE) of t his hybrid algorithm is compare d with that of an ARIMA model
