Stock Market Prediction Using Machine Learning

Authors

  • Vinay KM  Associate Professor, Department of Information Science and Engineering, East Point College of Engineering and Technology, Bangalore, Karnataka, India
  • Lalita Bhusal  Department of Information Science and Engineering, East Point College of Engineering and Technology, Bangalore, Karnataka, India
  • Shweta kumari  Professor, Department of Information Science and Engineering, East Point College of Engineering and Technology, Bangalore, Karnataka, India
  • Kemparaju N  Assistant Professor, Department of Electronics and Communication, JSS Academy of Technical Education, Bangalore, Karnataka, India
  • Gunasagari G S  

Keywords:

LSTM, Regression

Abstract

Financial exchange or Share market is maybe the foremost convoluted and complicated approach to figure together. Little possessions, financier enterprises, banking area, all depend upon this very body to create income and gap chances, a very confounded model. available Market Prediction, the purpose is to anticipate the longer term estimation of the monetary a lot of a corporation. The new pattern in securities exchange expectation advancements is that the utilization of Machine learning which makes expectations smitten by the qualities of current securities exchange lists via preparing on their past values. Machine Learning itself utilizes various models to create forecast simpler and genuine. Securities exchange expectation could be a significant effort within the field of money and putting in place organizations. Financial exchange is totally questionable because the costs of stocks continue fluctuating consistently thanks to various components that impact it. one in every of the customary methods of anticipating stock costs was by utilizing because it were recorded information. Yet, with time it absolutely was seen that different components as an example, people groups conclusions and other news occasions happening in also, round the nation influence the securities exchange, for instance public races, regular cataclysm then forth Speculators within the securities exchange seek for to amplify their benefits that they expect devices to dissect the prices and pattern of various stocks. AI calculations are utilized to plot new strategies to fabricate expectation models that may gauge the prices of stock and speak about the market pattern with great exactness. Numerous expectation models are proposed to fuse all the most considerations influencing the value of stocks. The paper centers round the utilization of LSTM based Machine deciding a way to foresee stock qualities. Variables considered are open, close, low, high and volume.

References

  1. Mehak Usmani, Syed Hasn Adilm Kamran Raza Syed Saad and Azhar Ali, "Stock Market Prediction using Machine Learning Techniques," 2018 4th International Conference on Computer and Information Sciences (ICCOINS), Kuala Lumpur, Malaysia 2016, pp.322-327.doi:10.1109/ICCOINS.2016.7783235
  2. Parkhar Vats and Prof. Krishna Samdani, "Study on Machine Learning Techniques in Financial Markets," 2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN), pp. 1-5, Mar. 2019. doi:10.1109/ICSCAN.2019.8878741
  3. Meghna Misra, Ajay Prakash Yadav and Harkiran Kaur, "Stock Market Prediction using Machine Learning Algorithms: A Classification Study," 2018 International Conference on Recent Innovations in Electrical, Electronics & Communication Engineering (ICRIEECE), Bhubaneswar, India, 2018, pp. 2475- 2478. doi:10.1109/ICRIEECE44171.2018.9009178
  4. Saloni Mohan, Shitya Mullapudi, Sudheer Sammeta, Parag Vijayvergia and David C. Anastasiu, “Stock Price Prediction Using News Sentiment Analysis,” 2019 IEEE Fifth International Conference on Big Data Computing Service and Applications (BigDataService), Newark, CA, USA, 2019, pp. 205-208. doi:10.1109/BigDataService.2019.00035
  5. Ashish Sharma, Dinesh Bhuriya and Upendra Singh, “Survey of Stock Market Prediction Using Machine Learning Approach,” 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA), Coimbatore, India, 2017, pp. 506-509. doi:10.1109/ICECA.2017.8212715
  6. Ishita Parmar, Navanshu Agarwal, Sheirsh Saxena, Ridam Arora, Shkhin Gupta, Himanshu Dhiman and Lokesh Chouhan, “Stock Market Prediction using Machine Learning”, 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC), Jalandar, India, 2018, pp.574-576. doi:10.1109/ICSCCC.2018.8703332
  7. Sondo Kim, Seungmo Ku, Woojin Chang and Jae wook Song, “Predicting the direction of US Stock prices using effective transfer entropy and machine learning techniques”, IEEE Access (Volume:8), IEEE, 2020, pp. 111660-111682. doi:10.1109/ACCESS.2020.3002174
  8. Rachna Sable, Dr Shivani Goel and Dr Pradeep Chatterjee, “Empirical Study on Stock Market Prediction using Machine Learning”, 2019 International Conference on Advances in Computing, Communication and Control (ICAC3), Mumbai, India, 2019, pp. 1-5. doi:10.1109/ICAC347590.2019.9036786
  9. Kunal Pahwa and Neha Agarwal, “Stock Market Analysis using Supervised Machine Learning”, 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCON), Faridabad, India, 2019, pp:197-200. doi: 10.1109/COMITCON 2019.8862225
  10. Vyom Unadkat, Parth Sayani, Prachi Doshi and Pratik Kanani, “Deep Learning for financial Prediction”, 2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET), Kottayam, India, 2018, pp. 1-6. doi:10.1109/ICCSDET.2018.8821178
  11. Jia Wang, Ton Sun, Benyuan Liu, Yu Cao and Degang Wang, “Financial Markets Prediction with Deep Learning”, 2018 17th IEEE International Conference on Machine Learning and Application (ICMCA), Orlando, FL, USA, 2018, pp. 97-104. doi:10.1109/ICMLA.2018.00022
  12. Mojtaba Nabipour, Pooyan Nayyeri, Hamed Jabani, Shahab S and Amir Mosavi, “Predicting Stock Market trends using Machine Learning and Deep Learning algorithms via continuous and binary data; a comparative analysis on the Tehran Stock Exchange,” IEEE Access (Volume:8), IEEE, 2020, pp. 150199- 150212. doi:10.1109/ACCESS.2020.3015966
  13. Jinho Lee, Raehyun Kim, Yookyung Kon and Jaewoo Kang, “Global Stock Market Prediction Based on Stock Chart Images Using Deep Q- Network”, IEEE Access (Volume:7), IEEE, 2019, pp. 167260-167277. doi:10.1109/ACCESS.2019.2953542
  14. Xianghui Yuan, Jin Yuan, Tianzhoo Jiang and Qurat Ul Ain, “Integrated Long-Term Stock Selection Models Based on Feature Selection and Machine Learning Algorithms for China Stock Market”, IEEE Access (Volume:8), IEEE, 2020, pp. 22672-22685. doi:10.1109/ACCESS.2020.2969293
  15. Shaikh Mohammad Idress, M. Afshar Alam, Parul Agarwal, “A Prediction Approach for Stock Market Volatility Based on Time Series Data,” IEEE Access (Volume:7), IEEE, 2019, pp. 17287- 17298. doi:10.1109/ACCESS.2019.2895252
  16. Dou Wei, “Prediction of Stock Price Based on LSTM Neural Network”, 2019 International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM), Dublin, Ireland, 2019, pp. 544-547. doi:10.1109/AIAM48774.2019.00113
  17. Mustain Billah, Sajjad Waheed, Abu Hanif, “Stock Market Prediction Using an Improved Training Algorithm of Neural Network”, 2016 2nd International Conference on Electrical, Computer and Telecommunication Engineering (ICECTE), Rajashahi, Bangladesh, 2016, pp. 1-4. doi:10.1109/ICECTE.2016.7879611
  18. Sukhman Singh, Tarun Kumar Madan, Jitendra Kumar and Ashutosh Kumar Singh, “Stock Market Forecasting using Machine Learning: Today and Tomorrow”, 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), Kannur, Kerala, India, 2019, pp. 738-745. doi:10.1109/ICICICT46008.2019.8993160
  19. Jeevan B, Naresh E, Vijaya Kumar B P and Prashanth Kambli, “Share Price Prediction using Machine Learning Technique”, 2018 IEEE Third International Conference on Circuits, Control, Communication and Computing, Bangalore, India, 2018, pp. 1- 4. doi:10.1109/CIMCA.2018.8739647
  20. Tristan Jordan and Heba Elgazzar, “ Stock market Prediction using Text-based Machine Learning”, 2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS), Vancouver, BC, Canada, 2020, pp. 1-5. doi: 10.1109/IEMTRONICS51293.2020.9216333
  21. Samuel Olusegan Ojo, Pius Adewale Owolawi, Maredi Mphahlele and Juliana Adeola Adisa, “ Stock Market Behaviour Prediction using Stacked LSTM Networks”, 2019 International Multidisciplinary Information Technology and Engineering Conference (IMITEC), Vanderbijlpark, South Africa, 2019, pp. 1-5. doi: 10.1109/IMITEC45504.2019.9015840
  22. Sumeet Sarode, Harsha G. Tolani, Prateek Kak and Lifna C S, “Stock price prediction using Machine Learning Techniques”, 2019 International Conference on Intelligent Sustainable Systems (ICISS), Palladam, Tamilnadu, India, 2019, pp. 177-181. doi: 10.1109/ISS1.2019.8907958

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2021-07-30

Issue

Volume 9, Issue 4, July-August-2021

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Vinay KM, Lalita Bhusal, Shweta kumari, Kemparaju N, Gunasagari G S "Stock Market Prediction Using Machine Learning" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 4, pp.160-164, July-August-2021.