[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117422-en":3,"doc-seo-117422-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":11,"language":21,"language_code":22,"site_id":23,"html_lang":22,"table_of_contents":24,"faqs":25,"seo_title":26,"seo_description":14,"update_tm":27,"read_time":28},117422,13056703019404,"Miles","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Stock Market Prediction using Machine Learning - Journal Article","Stock market prediction aims to estimate future values of traded stocks or financial instruments, reducing uncertainty in investment decisions. This paper presents a machine learning approach trained on historical stock data, using technical, fundamental, and time-series concepts as inputs. The study proposes Support Vector Machine (SVM) to forecast stock prices across large and small capitalizations and multiple market contexts with daily and near-real-time frequencies, implemented in Python.","International Journal of Innovative Research in Science  \nEngineering and Technology (IJIRSET)  \n(A Monthly, Peer Reviewed, Refereed, Scholarly Indexed, Open Access Journal)  \nImpact Factor: 8.699 Volume 14, Issue 4 , April 2025  \n|[www.ijirset.com](www.ijirset.com |A Monthly)[ |A Monthly](www.ijirset.com |A Monthly), Peer Reviewed & Refereed Journal| e-ISSN: 2319-8753| p-ISSN: 2347-6710|  \nVolume 14, Issue 4, April 2025  \n|DOI: 10.15680/IJIRSET.2025.1404556|  \nStock Market Prediction using Machine Learning  \nM. Krishna Karthik, M. Naresh, M. Vishnu Teja, M. Mahendhra  \nDept. of CSE, Bharath institute of higher education and research, Chennai, India  \nABSTRACT: In the finance world stock trading is one of the most important activities. Stock market prediction is an act of trying to determine the future value of a stock other financial instrument traded on a financial exchange. This paper explains the prediction of a stock using Machine Learning. The technical and fundamental or the time series analysis is used by the most of the stockbrokers while making the stock predictions. The programming language is used to predict the stock market using machine learning is Python. In this paper we propose a Machine Learning (ML) approach that will be trained from the available stocks data and gain intelligence and then uses the acquired knowledge for an accurate prediction. In this context this study uses a machine learning technique called Support Vector Machine (SVM) to predict stock prices for the large and small capitalizationsand in the three different markets, employing prices with both daily and up-to-the-minute frequencies.  \nKEYWORDS: Stock Market, Machine Learning, Predictions, Support Vector Machine  \nI. INTRODUCTION  \nBasically, quantitative traders with a lot of money from stock markets buy stocks derivatives and equities at a cheap price and later on selling them at high price. The trend in a stock market prediction is not a new thing and yet this issue is kept being discussed by various organizations. There are two types to analyze stocks which investors perform before investing in a stock, first is the fundamental analysis, in this analysis investors look at the intrinsic value of stocks, and performance of the industry, economy, political climate [etc. to](etc. to) decide that whether to invest or not. On the other hand, the technical analysis it is an evolution of stocks by the means of studying the statistics generated by market activity, such as past prices and volumes.  \nIn the recent years, increasing prominence of machine learning in various industries have enlightened many traders to apply machine learning techniques to the field, and some of them have produced quite promising results.  \nThis paper will develop a financial data predictor program in which there will be a dataset storing all historical stock prices and data will be treated as training sets for the program. The main purpose of the prediction is to reduce uncertainty associated to investment decision making.  \nStock Market follows the random walk, which implies that the best prediction you can have about tomorrow ’s value is today ’s value. Indisputably, the forecasting stock indices is very difficult because of the market volatility that needs accurate forecast model. The stock market indices are highly fluctuating and it effects the investor ’s belief. Stock prices are considered to be avery dynamic and susceptible to quick changes because of underlying nature of the financial domain and in part because of the mix of a known parameters (Previous day’s closing price, P/E ratio etc.) and the unknown factors (like Election Results, Rumors etc.) . There has been numerous attempts to predict stock price with Machine Learning. The focus of each research projects varies a lot in three ways. (1) The targeting price change can be near-term (less than a minute), short-term (tomorrow to a few days later), and a long-term (months later),(2) The set of stocks ca","cbCaiiddZ5BhUEBR","https://ap.wps.com/l/cbCaiiddZ5BhUEBR","pdf",1276391,1,"English","en",105,"# Abstract\n# Introduction\n# Methodology\n## Support Vector Machine (SVM)","[{\"question\":\"What is the main objective of the stock market prediction discussed in the paper?\",\"answer\":\"To determine future stock values using machine learning and reduce uncertainty in investment decision making.\"},{\"question\":\"Which machine learning technique does the paper use for prediction?\",\"answer\":\"The paper uses Support Vector Machine (SVM).\"},{\"question\":\"What data and implementation approach are mentioned for building the predictor?\",\"answer\":\"Historical stock prices are stored as a dataset for training, and the prediction is programmed using Python.\"}]","Stock Market Prediction using Machine Learning - Journal Article | PDF",1785675794,20,{"code":4,"msg":30,"data":31},"ok",{"site_id":23,"language":22,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":27},"stock-market-prediction-using-machine-learning-journal-article","",{"@graph":35,"@context":84},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/stock-market-prediction-using-machine-learning-journal-article/117422/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":22,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"What is the main objective of the stock market prediction discussed in the paper?","Question",{"text":74,"@type":75},"To determine future stock values using machine learning and reduce uncertainty in investment decision making.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"Which machine learning technique does the paper use for prediction?",{"text":79,"@type":75},"The paper uses Support Vector Machine (SVM).",{"name":81,"@type":72,"acceptedAnswer":82},"What data and implementation approach are mentioned for building the predictor?",{"text":83,"@type":75},"Historical stock prices are stored as a dataset for training, and the prediction is programmed using Python.","https://schema.org",{"og:url":51,"og:type":86,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":88,"canonical":51},"index,follow",{"doc_id":7,"site_id":23},{"code":4,"msg":5,"data":91},[92,96,100,104,109,114,119,122,126,129,133],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":93,"show_sort_weight":94,"slug":95},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":105,"doc_module":4,"doc_module_name":45,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":45,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":45,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":45,"category_name":124,"show_sort_weight":28,"slug":125},9,"Religion & Spirituality","religion-spirituality",{"id":28,"doc_module":4,"doc_module_name":45,"category_name":127,"show_sort_weight":28,"slug":128},"World Cup","world-cup",{"id":130,"doc_module":4,"doc_module_name":45,"category_name":131,"show_sort_weight":130,"slug":132},10,"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":45,"category_name":135,"show_sort_weight":105,"slug":136},19,"General","general"]