Financial time series forecasting with a bio-inspired fuzzy model
نویسندگان
چکیده
0957-4174/$ see front matter 2012 Elsevier Ltd. A http://dx.doi.org/10.1016/j.eswa.2012.02.135 ⇑ Corresponding author. E-mail address: jose-luis.aznarte@mines-paristech In general, times series forecasting is considered as a highly complex problem, which is particularly true for financial time series. In this paper, a fuzzy model evolved through a bio-inspired algorithm is proposed to produce accurate models for the prediction of these time series. The performance of this model is compared to that of a group of state-of-the-art statistical models. A thorough experimental study is designed and carry out in order to assess the merits of the proposal. The experimental results allow us to state that our proposal forecasts consistently outperform the other considered methods. 2012 Elsevier Ltd. All rights reserved.
منابع مشابه
AN EXTENDED FUZZY ARTIFICIAL NEURAL NETWORKS MODEL FOR TIME SERIES FORECASTING
Improving time series forecastingaccuracy is an important yet often difficult task.Both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. In this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...
متن کاملOverview and Comparison of Short-term Interval Models for Financial Time Series Forecasting
In recent years, various time series models have been proposed for financial markets forecasting. In each case, the accuracy of time series forecasting models are fundamental to make decision and hence the research for improving the effectiveness of forecasting models have been curried on. Many researchers have compared different time series models together in order to determine more efficien...
متن کاملTime Variant Fuzzy Time Series Approach for Forecasting Using Particle Swarm Optimization
Fuzzy time series have been developed during the last decade to improve the forecast accuracy. Many algorithms have been applied in this approach of forecasting such as high order time invariant fuzzy time series. In this paper, we present a hybrid algorithm to deal with the forecasting problem based on time variant fuzzy time series and particle swarm optimization algorithm, as a highly effi...
متن کاملResidual analysis using Fourier series transform in Fuzzy time series model
In this paper, we propose a new residual analysis method using Fourier series transform into fuzzy time series model for improving the forecasting performance. This hybrid model takes advantage of the high predictable power of fuzzy time series model and Fourier series transform to fit the estimated residuals into frequency spectra, select the low-frequency terms, filter out high-frequency term...
متن کاملA hybrid computational intelligence model for foreign exchange rate forecasting
Computational intelligence approaches have gradually established themselves as a popular tool for forecasting the complicated financial markets. Forecasting accuracy is one of the most important features of forecasting models; hence, never has research directed at improving upon the effectiveness of time series models stopped. Nowadays, despite the numerous time series forecasting models propos...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Expert Syst. Appl.
دوره 39 شماره
صفحات -
تاریخ انتشار 2012