%0 Journal Article %1 noauthororeditor %A Bagade, Mr. Ketan Ashok Bagade | Yogini %D 2023 %J INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT %K %R(WPR), (CCI), (EMA), (LSTM), (MA), (MACD), (MOM) (ROC), (RSI), (SO), (STIs), (SVM), Average Averages Change Channel Commodity Convergence Divergence Exponential Index Indicators Long Machine Momentum Moving Oscillator Rate Relative Short-Term Stochastic Stock Strength Support Technical Vector William memory of %N 2 %P 1026-1033 %T Artificial Intelligence Based Stock Market Prediction Model using Technical Indicators %U https://www.ijtsrd.com.com/management/other/53854/artificial-intelligence-based-stock-market-prediction-model-using-technical-indicators/mr-ketan-ashok-bagade %V 7 %X The stock market is highly volatile and complex in nature. However, notion of stock price predictability is typical, many researchers suggest that the Buy and Sell prices are predictable and investor can make above average profits using efficient Technical Analysis TA .Most of the earlier prediction models predict individual stocks and the results are mostly influenced by company’s reputation, news, sentiments and other fundamental issues while stock indices are less affected by these issues. In this work, an effort is made to predict the Buy and Sell decisions of stocks, trends of stock by utilizing Stock Technical Indicators STIs As a part of prediction model the Long Short Term Memory LSTM , Support Virtual Machine SVM Artificial intelligence algorithms will be used with Stock Technical Indicators STIs. The project will be carried on National Stock Exchange NSE Stocks of India. Mr. Ketan Ashok Bagade | Yogini Bagade Ärtificial Intelligence Based Stock Market Prediction Model using Technical Indicators" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-2 , April 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd53854.pdf Paper URL: https://www.ijtsrd.com.com/management/other/53854/artificial-intelligence-based-stock-market-prediction-model-using-technical-indicators/mr-ketan-ashok-bagade

@article{noauthororeditor, abstract = {The stock market is highly volatile and complex in nature. However, notion of stock price predictability is typical, many researchers suggest that the Buy and Sell prices are predictable and investor can make above average profits using efficient Technical Analysis TA .Most of the earlier prediction models predict individual stocks and the results are mostly influenced by company’s reputation, news, sentiments and other fundamental issues while stock indices are less affected by these issues. In this work, an effort is made to predict the Buy and Sell decisions of stocks, trends of stock by utilizing Stock Technical Indicators STIs As a part of prediction model the Long Short Term Memory LSTM , Support Virtual Machine SVM Artificial intelligence algorithms will be used with Stock Technical Indicators STIs. The project will be carried on National Stock Exchange NSE Stocks of India. Mr. Ketan Ashok Bagade | Yogini Bagade "Artificial Intelligence Based Stock Market Prediction Model using Technical Indicators" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-2 , April 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd53854.pdf Paper URL: https://www.ijtsrd.com.com/management/other/53854/artificial-intelligence-based-stock-market-prediction-model-using-technical-indicators/mr-ketan-ashok-bagade }, added-at = {2023-07-13T08:13:22.000+0200}, author = {Bagade, Mr. Ketan Ashok Bagade | Yogini}, biburl = {https://www.bibsonomy.org/bibtex/23311da130c4e03895f7a06c9522addb7/ijtsrd}, interhash = {43f05fde898a383f9ff2c6f965e6b6a0}, intrahash = {3311da130c4e03895f7a06c9522addb7}, issn = {2456-6470}, journal = {INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT}, keywords = {%R(WPR), (CCI), (EMA), (LSTM), (MA), (MACD), (MOM) (ROC), (RSI), (SO), (STIs), (SVM), Average Averages Change Channel Commodity Convergence Divergence Exponential Index Indicators Long Machine Momentum Moving Oscillator Rate Relative Short-Term Stochastic Stock Strength Support Technical Vector William memory of}, language = {english}, month = apr, number = 2, pages = {1026-1033}, timestamp = {2023-07-13T08:13:22.000+0200}, title = {Artificial Intelligence Based Stock Market Prediction Model using Technical Indicators }, url = {https://www.ijtsrd.com.com/management/other/53854/artificial-intelligence-based-stock-market-prediction-model-using-technical-indicators/mr-ketan-ashok-bagade}, volume = 7, year = 2023 }