Find all needed information about Forecasting Stock Market Movement Direction With Support Vector Machine. Below you can see links where you can find everything you want to know about Forecasting Stock Market Movement Direction With Support Vector Machine.
https://www.sciencedirect.com/science/article/pii/S0305054804000681
In this paper, we study the use of support vector machines to predict financial movement direction. SVM is a promising type of tool for financial forecasting. As demonstrated in our empirical analysis, SVM is superior to the other individual classification methods in forecasting weekly movement direction of NIKKEI 225 Index.Cited by: 896
https://www.researchgate.net/publication/222570103_Forecasting_stock_movement_direction_with_support_vector_machine
Forecasting stock movement direction with support vector machine Article in Computers & Operations Research 32(10):2513-2522 · October 2005 with 583 Reads How we measure 'reads'
https://ieeexplore.ieee.org/document/8326522/
Mar 27, 2018 · Forecasting Stock Market Movement Direction Using Sentiment Analysis and Support Vector Machine Abstract: Investor sentiment plays an important role on the stock market. User-generated textual content on the Internet provides a precious source to reflect investor psychology and predicts stock prices as a complement to stock market data.Cited by: 9
https://www.semanticscholar.org/paper/Forecasting-stock-market-movement-direction-with-Huang-Nakamori/ed036a6f69d192c98a750e8b937061eecf1aba50
Support vector machine (SVM) is a very specific type of learning algorithms characterized by the capacity control of the decision function, the use of the kernel functions and the sparsity of the solution. In this paper, we investigate the predictability of financial movement direction with SVM by forecasting the weekly movement direction of NIKKEI 225 index. To evaluate the forecasting ...
https://preserve.lehigh.edu/cgi/viewcontent.cgi?article=2098&context=etd
A SVM Approach in Forecasting the Moving Direction of Chinese Stock Indices Zhongyuan Wei Lehigh University, 2012 Supervisor: Professor Katya Scheinberg Support vector machine (SVM) has been shown to be a reliable tool in prediction andCited by: 2
https://dl.acm.org/citation.cfm?id=1073572
Forecasting stock market movement direction with support vector machine. Authors: Wei Huang: Institute of Systems Science, Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing 100080, China ... Support vector machine (SVM) is a very specific type of learning algorithms characterized by the capacity control of the ...Cited by: 896
https://www.researchgate.net/publication/220472531_Forecasting_stock_market_movement_direction_with_support_vector_machine
Huang et al. have exploited a support vector machine (SVM) to forecast the stock market direction by using a small data set made up of 676 pairs of observation, achieving a hit ratio of nearly 70% ...
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=876544
Jan 24, 2006 · Forecasting Stock Index Movement: A Comparison of Support Vector Machines and Random Forest ... Empirical experimentation suggests that the SVM outperforms the other classification methods in terms of predicting the direction of the stock market movement and random forest method outperforms neural network, discriminant analysis and logit model ...Cited by: 98
https://www.sciencedirect.com/science/article/abs/pii/S0305054804000681
Forecasting stock market movement direction with support vector machine. Author links open overlay panel Wei Huang a b Yoshiteru Nakamori a Shou-Yang Wang b 1Cited by: 896
https://www.cs.princeton.edu/sites/default/files/uploads/saahil_madge.pdf
Predicting Stock Price Direction using Support Vector Machines Saahil Madge Advisor: Professor Swati Bhatt Abstract Support Vector Machine is a machine learning technique used in recent studies to forecast stock prices. This study uses daily closing prices for 34 …Cited by: 8
Need to find Forecasting Stock Market Movement Direction With Support Vector Machine information?
To find needed information please read the text beloow. If you need to know more you can click on the links to visit sites with more detailed data.