Intelligent stock trading system based on SVM algorithm and oscillation box prediction

Wen, Qinghua; Yang, Zehong; Song, Yong; Jia, Peifa

doi:10.1109/ijcnn.2009.5178843

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…Wen et al [8] worked in trading decision support system using Support Vector Machine and Oscillation Box where importance was put on breakout point. They discussed that if the strength of buying or selling beat that of the another, the price will effectively break out the upper bound or the lower bound and the time of the breakout is supposed to be the best time to buy or sell the stock.…”

Section: Related Workmentioning

confidence: 99%

Breakout Stocks Identification using Machine Learning Approaches

Ansary

2022

ENPESJ

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Stock market offers a platform for people to engage in trading. It contributes to the growth of nation. Decision making regarding investments needs to be done very carefully so that an investor does not suffer massive loss. Since the share market is susceptible to experience huge change at any given moment, with the probability of profit comes huge risks of losing a fortune. In our research, we have worked on prediction of breakout stocks. If identified properly, it can help one to invest efficiently. We have used multiple machine learning approaches as ML models can offer more effective predictions compared to other methods due to the ability to learn and adapt from dataset information. In our experiment, the models have yielded very good results.

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Section: Related Workmentioning

confidence: 99%

Breakout Stocks Identification using Machine Learning Approaches

Ansary

2022

ENPESJ

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“…Fundamental analysis is the technique to analyze the company performance by calculating profit and liabilities. A macroeconomic analysis is a technique to analyze the recent decision taken by the company and its impact on the market [4], [5]. The aim of the research is to build an intelligent system illustrated in Fig.…”

Section: Introductionmentioning

confidence: 99%

“…Qiaghua wen et al [4], have proposed an intelligent stock recommendation system using SVM techniques and box theory of stock. The SVM uses statistical learning theory and structural risk minimisation principle.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy based Soft Computing Technique to Predict the Movement of the Price of a Stock

Dutta¹

2018

ijacsa

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Abstract-Soft computing is a part of an artificial intelligence, and fuzzy logic is the study of fuzziness on data. The combination of these two techniques can provide an intelligent system with more ability and flexibility. The nature of data in the stock/capital market is more complex and challenging to predict the movement of the price of the stock. The study has combined both fuzzy c-means and neural network technique for the prediction of the price of the stock. The research finds an optimum solution to predict the future price of a stock. The comparison of time and space complexity proved that the proposed method is better than the existing methods.

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A volatility-driven stock trading framework based on automated, short-term recommendation method

Das

2017

2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC)

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Intelligent stock trading system based on SVM algorithm and oscillation box prediction

Cited by 5 publications

References 14 publications

Breakout Stocks Identification using Machine Learning Approaches

Breakout Stocks Identification using Machine Learning Approaches

A Fuzzy based Soft Computing Technique to Predict the Movement of the Price of a Stock

A volatility-driven stock trading framework based on automated, short-term recommendation method

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