[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-153099-105":59,"doc-detail-153099-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","the-industrial-asymmetry-of-the-stock-price-prediction-with-investor-sentiment-based-on-the-comparison-of-predictive-effects-with-svr","The Industrial Asymmetry of the Stock Price Prediction with Investor Sentiment - based on the comparison of predictive effects with SVR","","As a representative emerging financial market, the Chinese stock market shows strong volatility driven by investor sentiment. The study compares the predictive performance of ANN, SVR, and ARIMA to evaluate how sentiment influences stock price forecasting and then analyzes industry-level asymmetry using SVR. After incorporating relevant financial indicators, the Shenwan first-class industries are divided into two categories, revealing that sentiment-sensitive industries tend to feature young, high-growth firms under high operating pressure. The findings also indicate a high prevalence of investment bubbles in these firms.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/the-industrial-asymmetry-of-the-stock-price-prediction-with-investor-sentiment-based-on-the-comparison-of-predictive-effects-with-svr/153099/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/the-industrial-asymmetry-of-the-stock-price-prediction-with-investor-sentiment-based-on-the-comparison-of-predictive-effects-with-svr/153099.png","ImageObject",300,407,{"name":92,"@type":93},"Aurelia","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-08-27",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",12,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"Why is investor sentiment important for stock price forecasting in the Chinese market?","Question",{"text":113,"@type":114},"The paper argues that investor sentiment increasingly affects stock price movements and contributes to the market’s volatility, motivating efficient prediction methods.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"Which models are compared for predictive performance, and what is the selection outcome?",{"text":118,"@type":114},"The study compares ANN, SVR, and ARIMA, and selects SVR to examine the asymmetry effect of investor sentiment on industry index prediction.",{"name":120,"@type":111,"acceptedAnswer":121},"How does the paper characterize industries affected by investor sentiment?",{"text":122,"@type":114},"Using financial indicators, it divides Shenwan first-class industries into two types and finds sentiment-affected industries mainly comprise young, high-growth companies facing high operating pressure, with many investment bubbles.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},153099,1787871003,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":46,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":130,"read_time":31,"preview_page_count":4},1099514068365,"https://ap-avatar.wpscdn.com/avatar/10000253d8d9f28188e?_k=1776742907772140068","Guo Kun (Orcid ID: 0000-0002-4787-8406)  \nThe Industrial Asymmetry of the Stock Price Prediction with Investor Sentiment: based on the comparison of predictive effects with SVR  \nZhenni Jina,c,d, Kun Guob,c,d*, Yi Sunb*, Lin Laie, Zhewen Liaob,c,d  \naSino-Danish College, University of Chinese Academy of Science, Beijing, China  \nbSchool of Economics and Management, University of Chinese Academy of Science, Beijing, China  \ncResearch Center on Fictitious Economy & Data Science, Chinese Academy of Science, Beijing, China  \ndKey Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Science, Beijing, China  \ne HSBC Business School, Peking University, Shenzhen, China  \nAbstract: As a representative emerging financial market, Chinese stock market is more prone to volatility because of investor sentiment. It is reasonable to use efficient predictive methods to analyze the influence of investor sentiment on stock price forecasting. This paper conductsa comparative study about the predictive performance of ANN, SVR and ARIMA and selects SVR to study the asymmetry effect of investor sentiment on different industry index prediction. After studying the relevant financial indicators, the results divide the Shenwan first-class industries into two types and show that the industries affected by investor sentiment are composed by young companies with high-growth and high operative pressure and there are a great number of investment bubbles in those companies.  \nKey words: Investor Sentiment; Stock Price Prediction; SVR; Industries Asymmetry  \n* Corresponding author at: School of Economics and Management, University of Chinese Academy of Sciences, Beijing, 100190, [China. Email: ](China. Email: guokun@ucas.ac.cn)[guokun@ucas.ac.cn](China. Email: guokun@ucas.ac.cn), [suny@ucas.ac.cn](suny@ucas.ac.cn).  \n1. Introduction  \nWith the rapid development of financial industry, Stock prediction is increasingly attractive for different agents in stock markets recently. Individual investors as one important agent in the market, their sentiment plays more and more important role in the movements of stock prices. A growing number of studies showed that investor sentiment can be used to predict the stock volatility to some extent. However, facing the challenges from the poor performance of Efficient Market Hypothesis, Considerable attention has been paid to explore efficient methods for forecasting stock market behavior.  \nSince years, Machine learning techniques have been widely implemented in predicting stock markets. Some studies found that Artificial Neural Network (ANN) has successfully built prediction models to predict financial time series (Cheng et al., 1996; Sharda and Patil, 1994; Van and Robert, 1997) . Hamid and Iqbal (2004) applied ANN and the Barone-Adesi and Whaley (BAW) American futures options pricing model to forecast volatility of the S&P 500 Index futures prices. They found that predictions from neural networks outperform the financial time series model. Adebiyi et al (2014) employed the stock data from New York Stock Exchange to test the predicting ability of conventional Box-Jenkins ARIMA model and artificial neural networks model. The empirical results indicated that ARIMA model performs better in forecasting stock's direction but ANN has superior performance over ARIMA model on the whole. Moghaddam et al (2016) studied the performance of ANN in forecasting the daily NASDAQ stock exchange rate. The values of NASDAQ exchange rate of last four and nine working days are used as the input parameters. The results showed that there is no obvious difference between the prediction performance of the two input parameters. Chopra et al (2019) employed the data of nine stocks and CNX NIFTY50 to investigate the prediction ability of ANN before and after demonetization in India. The regression values for all networks are 0.999 during training state indicated that the high prediction ability of Neural Network designed. However,","cbCaiqSwulIqTxwj","https://ap.wps.com/l/cbCaiqSwulIqTxwj","pdf",1358433,"English","# Introduction\n## Background and Motivation\n## Related Work on Prediction Models","[{\"question\":\"Why is investor sentiment important for stock price forecasting in the Chinese market?\",\"answer\":\"The paper argues that investor sentiment increasingly affects stock price movements and contributes to the market’s volatility, motivating efficient prediction methods.\"},{\"question\":\"Which models are compared for predictive performance, and what is the selection outcome?\",\"answer\":\"The study compares ANN, SVR, and ARIMA, and selects SVR to examine the asymmetry effect of investor sentiment on industry index prediction.\"},{\"question\":\"How does the paper characterize industries affected by investor sentiment?\",\"answer\":\"Using financial indicators, it divides Shenwan first-class industries into two types and finds sentiment-affected industries mainly comprise young, high-growth companies facing high operating pressure, with many investment bubbles.\"}]","The Industrial Asymmetry of the Stock Price Prediction with Investor Sentiment - based on the comparison of predictive effects with SVR | PDF"]