[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-152753-105":3,"doc-detail-152753-en":81,"detail-sidebar-cat-0-en-105":98},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","a-dynamic-scenario-driven-technique-for-stock-price-prediction-and-trading","A dynamic scenario-driven technique for stock price prediction and trading","","Accurately forecasting stock market behavior remains difficult because markets are extremely nonlinear and dynamically evolving. Prior work suggests that combining technical indicators with machine learning models can improve forecasting, but selecting effective indicators and prediction models is challenging across varying market regimes. The proposed DSdT method introduces scenario recognition and integration within the forecasting pipeline to drive scenario-aware stock price prediction. A shallow neural network with a gating mechanism integrates current market scenarios using many technical indicators, evaluated on 11 Indian stocks.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/a-dynamic-scenario-driven-technique-for-stock-price-prediction-and-trading/152753/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/a-dynamic-scenario-driven-technique-for-stock-price-prediction-and-trading/152753.png","ImageObject",300,407,{"name":42,"@type":43},"Ivy","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-31","2026-08-27",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",16,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What problem does DSdT address in stock forecasting?","Question",{"text":63,"@type":64},"DSdT targets the difficulty of predicting stock behavior in highly nonlinear, dynamic market conditions where no single indicator set or model consistently dominates.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How does DSdT incorporate market information into predictions?",{"text":68,"@type":64},"DSdT uses a scenario recognition and integration module to identify the current market scenario and integrate it into the forecasting pipeline, producing scenario-driven predictions.",{"name":70,"@type":61,"acceptedAnswer":71},"How are the proposed results evaluated?",{"text":72,"@type":64},"Experiments are conducted on 11 stocks from the Indian stock market, comparing next-day prediction performance using MAPE and evaluating a derived trading strategy against multiple baselines.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},152753,1787866908,{"code":4,"msg":82,"data":83},"success",{"doc_id":79,"user_id":84,"nickname":42,"user_avatar":85,"doc_module":4,"category_id":86,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":87,"file_id":88,"file_url":89,"file_type":90,"file_size":91,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":92,"language":93,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":94,"faqs":95,"seo_title":96,"seo_description":12,"update_tm":80,"read_time":97,"preview_page_count":4},549758252649,"https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Received: 19 July 2021 Revised: 10 December 2021 Accepted: 21 December 2021  \nDOI: 10.1002/for.2848  \nRESE ARCH ARTICL E  \nA dynamic scenario-driven technique for stock price prediction and trading  \nYash Thesia | Vidhey Oza | Priyank Thakkar   \nComputer Science and Engineering Department, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India  \nCorrespondence  \nPriyank Thakkar, Computer Science and Engineering Department, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India. [Email: priyank.thakkar@nirmauni.ac.in](Email: priyank.thakkar@nirmauni.ac.in)  \nAbstract  \nIt has always been a challenge to accurately forecast the behavior of a stock market due to its extremely nonlinear and dynamic nature. Numerous studies have shown that technical indicators describing stocks in conjunction with machine learning models can serve as useful tools for forecasting in the stock market. There are various challenges, and one of them is the choice of the right technical indicators and prediction models. It is believed that there is no optimal set of technical indicators that work well in all market scenarios in a dynamic environment such as the stock market. The statement also applies to different prediction models. There is no definite winner, and different settings can emerge as winners in different market scenarios. On this premise, we propose DSdT: a dynamic scenario-driven technique for stock price prediction and trading strategy enhancement. The proposed novel technique uses the scenario recognition and integration module to identify and integrate the current market scenario into the forecasting pipeline, resulting in a scenario-driven stock price prediction. We use a large set of technical indicators and a shallow neural network equipped with a gating mechanism to capture and integrate the current market scenario in the prediction process. Experiments are performed on 11 stocks of the Indian Stock Market. The proposed approach yields mean absolute percentage error (MAPE) of 1.67% compared with 2.4% of its closest nonscenario-driven counterpart for the next day's stock price prediction task. A trading strategy is also devised using the proposed technique, and thereturns are compared with different baselines. Results show that the devised trading strategy yields an approximate average return of 54% compared with 25% of the return obtained by the nearest benchmark.  \nKEYWOR DS  \nneural networks, scenario-driven technique, stock price prediction, support vector regressors, trading strategy  \n1 | INTRODUCTION  \nStock market forecasting is a classic problem that has been studied for decades. Fundamental analysis and technical analysis are two prevalent methods when  \nit comes to forecasting and investing in the stock market.  \nFundamental analysis is a process whereby an investor evaluates the value of an asset by taking a holistic approach to markets. As a matter of fact, a fundamental  \nJournal of Forecasting. 2022;41:653–674.  \n[wileyonlinelibrary.com/journal/for](wileyonlinelibrary.com/journal/for)  \n© 2021 John Wiley & Sons, Ltd.  \n653  \n1099131x, 2022, 3, Downloaded from [https://onlinelibrary.wiley.com/doi/10.1002/for.2848 by Egyptian National Sti. Network (Enstinet), Wiley Online Library on [06/11/2022]. See the Terms and Conditions (](https://onlinelibrary.wiley.com/doi/10.1002/for.2848 by Egyptian National Sti. Network (Enstinet), Wiley Online Library on [06/11/2022]. See the Terms and Conditions ()[https://onlinelibrary.wiley.com/terms-and-conditions](https://onlinelibrary.wiley.com/terms-and-conditions)) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License  \nanalyst might consider a number of factors to be the rationale for their investments. These factors can be macroeconomic, including the health of the entire country's economy, which sectors are doing well in that economy, news reports and politics at national and international stage, how ","cbCaibUloma1o0eV","https://ap.wps.com/l/cbCaibUloma1o0eV","pdf",5403100,22,"English","# Introduction\n## Fundamental analysis and technical analysis\n## Scenario recognition for forecasting","[{\"question\":\"What problem does DSdT address in stock forecasting?\",\"answer\":\"DSdT targets the difficulty of predicting stock behavior in highly nonlinear, dynamic market conditions where no single indicator set or model consistently dominates.\"},{\"question\":\"How does DSdT incorporate market information into predictions?\",\"answer\":\"DSdT uses a scenario recognition and integration module to identify the current market scenario and integrate it into the forecasting pipeline, producing scenario-driven predictions.\"},{\"question\":\"How are the proposed results evaluated?\",\"answer\":\"Experiments are conducted on 11 stocks from the Indian stock market, comparing next-day prediction performance using MAPE and evaluating a derived trading strategy against multiple baselines.\"}]","A dynamic scenario-driven technique for stock price prediction and trading | PDF",55,{"code":4,"msg":82,"data":99},[100,104,108,112,117,122,127,130,135,138,142],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":101,"show_sort_weight":102,"slug":103},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":105,"show_sort_weight":106,"slug":107},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":109,"show_sort_weight":110,"slug":111},"Exam",70,"exam",{"id":113,"doc_module":4,"doc_module_name":25,"category_name":114,"show_sort_weight":115,"slug":116},5,"Comic",60,"comic",{"id":118,"doc_module":4,"doc_module_name":25,"category_name":119,"show_sort_weight":120,"slug":121},6,"Technology",50,"technology",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":125,"slug":126},7,"Healthcare",40,"healthcare",{"id":86,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":128,"slug":129},30,"research-report",{"id":131,"doc_module":4,"doc_module_name":25,"category_name":132,"show_sort_weight":133,"slug":134},9,"Religion & Spirituality",20,"religion-spirituality",{"id":133,"doc_module":4,"doc_module_name":25,"category_name":136,"show_sort_weight":133,"slug":137},"World Cup","world-cup",{"id":139,"doc_module":4,"doc_module_name":25,"category_name":140,"show_sort_weight":139,"slug":141},10,"Lifestyle","lifestyle",{"id":143,"doc_module":4,"doc_module_name":25,"category_name":144,"show_sort_weight":113,"slug":145},19,"General","general"]