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https://www.sciencedirect.com/science/article/pii/S0925231203003722
2.2. Prior applications of SVM in financial time-series forecasting. As mentioned above, the BP network has been widely used in the area of financial time series forecasting because of its broad applicability to many business problems and preeminent learning ability.Cited by: 1474
https://www.sciencedirect.com/science/article/abs/pii/S0925231203003722
Support vector machines (SVMs) are promising methods for the prediction of financial time-series because they use a risk function consisting of the em…Cited by: 1474
https://www.researchgate.net/publication/222661136_Financial_time_series_forecasting_using_support_vector_machines
Again, financial time series were predicted using support vector machines (Trafalis and Ince, 2000; Kim, 2003). There are also studies on the trend movement of the stock market and prediction of ...
http://article.sapub.org/10.5923.j.statistics.20140401.03.html
Forecasting financial time series, such as stock price indices, is a complex process. This is because financial time series are usually quite noisy and involve ambiguous seasonal effects due to holidays, weekends, irregular closure periods of the stock market, changes in interest rates, and announcements of macroeconomic and political events.Cited by: 6
https://www.semanticscholar.org/paper/Financial-Time-Series-Forecasting-Using-Support-Gui-Wei/182c4e2dc048454bada5b1bf7431bf3536e0b69d
In this paper, we transform the financial time series into fuzzy grain particle sequences, and use support vector machine regression to regress the upper and lower bounds of the fuzzy particles, and then apply regression model single-step prediction on the upper and lower bounds, which will limit the predict results within a range.
https://stackoverflow.com/questions/31048964/time-series-forecasting-using-support-vector-machine
Financial time series forecasting using support vector machine. Using Support Vector Machines in Financial Time Series Forecasting. Financial Forecasting Using Support Vector Machines. I really recommend that you go through the existent literature, but just for fun I will describe an easy way (probably not the best) to do it.
http://keddiyan.com/files/AHCI/week3/8.pdf
Financial time series forecasting using support vector machines Kyoung-jae Kim∗ Department of Information Systems, College of Business Administration, Dongguk University, 3-26, Pil-dong, Chung-gu, Seoul 100715, South Korea Received 28 February 2002; accepted 13 March2003 Abstract Support vector machines (SVMs) are promising methods for the ...
https://ieeexplore.ieee.org/document/4840324
Apr 24, 2009 · Time Series Prediction Using Support Vector Machines: A Survey ... support vector machines (SVM). The underlying motivation for using SVMs is the ability of this methodology to accurately forecast time series data when the underlying system processes are typically nonlinear, non-stationary and not defined a-priori. ...Cited by: 698
https://www.sciencedirect.com/science/article/pii/S0305048301000263
This paper deals with the application of a novel neural network technique, support vector machine (SVM), in financial time series forecasting. The objective of this paper is to examine the feasibility of SVM in financial time series forecasting by comparing it with a …Cited by: 1242
https://www.sciencedirect.com/science/article/pii/S0925231201006762
This paper proposes a modified version of support vector machines, called C-ascending support vector machine, to model non-stationary financial time series.The C-ascending support vector machines are obtained by a simple modification of the regularized risk function in support vector machines, whereby the recent ε-insensitive errors are penalized more heavily than the distant ε …Cited by: 525
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