Relevant bibliographies by topics / Investor's sentiments

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Investor's sentiments'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Investor's sentiments"

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Gurav, Uma, and Kotrappa S. "Predict Stock Market's Fluctuating Behaviour : Role of Investor's Sentiments on Stock Market performance." International Journal of Engineering Trends and Technology 68, no. 11 (2020): 72–80. http://dx.doi.org/10.14445/22315381/ijett-v68i11p209.

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Zhang, Gaowei, Lingyu Xu, and Lei Wang. "Sentiments classification in stock network public opinion space based on long-short memory convolution neural network." MATEC Web of Conferences 189 (2018): 10010. http://dx.doi.org/10.1051/matecconf/201818910010.

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Deep learning is used to deal with natural language processing problems. Some are based on phrases and some are based on words. This article is inspired by the pixel level in the CV world and therefore retrains the neural network from a character perspective. Neural networks do not need to know about word lookup table or word2vec in advance, and the knowledge of these words is often high-dimensional and it is difficult to apply to convolutional neural networks. In addition, our long-short term memory convolutional neural networks no longer need to know the syntax and semantics in advance. The
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Maknickiene, Nijole, Indre Lapinskaite, and Algirdas Maknickas. "Application of ensemble of recurrent neural networks for forecasting of stock market sentiments." Equilibrium 13, no. 1 (2018): 7–27. http://dx.doi.org/10.24136/eq.2018.001.

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Research background: Research and measurement of sentiments, and the integration of methods for sentiment analysis in forecasting models or trading strategies for financial markets are gaining increasing attention at present. The theories that claim it is difficult to predict the individual investor’s decision also claim that individual investors cause market instability due to their irrationality. The existing instability increases the need for scientific research. 
 Purpose of the article: This paper is dedicated to establishing a link between the individual investors’ behavior, which i
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Neves, Maria Elisabete Duarte. "Payout and firm’s catering." International Journal of Managerial Finance 14, no. 1 (2018): 2–22. http://dx.doi.org/10.1108/ijmf-03-2017-0055.

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Purpose The purpose of this paper is to investigate whether investor sentiments exert significant influence on corporate dividend policy. Additionally it provides further evidence on the moderating role of certain firm’s characteristics on the relation between dividends and investor sentiment. Design/methodology/approach A sample of 635 firms from 12 Eurozone countries for the period of 1986-2003 has been used. A dividend model has been suggested which incorporates a variable at the firm level that proxies for the catering effect, as a measure of investor sentiments. The estimation model of di
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Prasanna, Kumar Nishanth Arul Dominic Sayyid Shadil KMP Evan Shaji. "IMPACT OF COVID-19 ON STOCK MARKET VOLATILITY." International Journal of Advanced Scientific and Technical Research 15, no. 2 (2025): 72–85. https://doi.org/10.5281/zenodo.15541859.

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Abstract: The global pandemic caused by COVID–19 has adversely affected the economic sectors of countries universally. Indian financial markets also reacted to these disruptions, and sharp volatility was witnessed. This paper especially attempts to analyses the impact Covid-19 had on the Nifty 50 index with reference to the price movements it had across the three different phases: pre-pandemic, during, and post-pandemic. In this research, there are various things that are explored, like macroeconomic factors, investor sentiment, government policies, and external shocks, which influence t
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Ruchi and Rakesh Kumar. "Impact of Investor Sentiment on Stock Market Returns: Evidence from India." Asian Journal of Economics, Business and Accounting 25, no. 5 (2025): 35–42. https://doi.org/10.9734/ajeba/2025/v25i51782.

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Aims: Behavioral finance assumes that investors choose investments as on their varied opinions and sentiments about the market. This study tries to determine the impact of investor sentiment on stock market returns by constructing an Investor sentiment index for the Indian market. Methodology: The present study employs BSE Sensex- financial year returns of ten years, and the sample period ranges from 1 April 2014 to 31 March 2024. The Principal Component Technique is applied to form an investor sentiment index using seven separate market proxies. Results: The regression analysis's beta value o
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Sayim, Mustafa, and Hamid Rahman. "The relationship between individual investor sentiment, stock return and volatility." International Journal of Emerging Markets 10, no. 3 (2015): 504–20. http://dx.doi.org/10.1108/ijoem-07-2012-0060.

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Purpose – The purpose of this paper is to examine the impact of Turkish individual investor sentiment on the Istanbul Stock Exchange (ISE) and to investigate whether investor sentiment, stock return and volatility in Turkey are related. Design/methodology/approach – This study used the monthly Turkish Consumer Confidence Index, published by the Turkish Statistical Institute, as a proxy for individual investor sentiments. First, Turkish market fundamentals were regressed on investor sentiments in order to capture the effects of macroeconomic risk factors on investor sentiments. Then, it used th
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Gadde, Nishant. "Machine Learning for Real-Time Portfolio Rebalancing: A Novel Approach to Financial Optimization." International Journal for Research in Applied Science and Engineering Technology 12, no. 10 (2024): 19–23. http://dx.doi.org/10.22214/ijraset.2024.64375.

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Portfolio rebalancing is an important practice in finance, which keeps the asset allocations of an investor's portfolio in conformance with his or her risk tolerance and financial goals. Traditional rebalancing strategies are largely of a static nature, with rebalancing being periodically performed or when the portfolio valuations exceed fixed thresholds. Obviously, these methods do not take into consideration the dynamic and rapidly changing nature of financial markets, wherein the prices of various assets can change drastically due to macroeconomic events, market sentiments, and other factor
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Yahya, Farzan, Zhang Shaohua, Muhammad Waqas, and Zhengde Xiong. "COVID-Induced Investor Sentiments and Market Reaction under Extreme Meteorological Conditions: Evidence from Clean Energy Sector of Asia-Pacific." Problemy Ekorozwoju 16, no. 1 (2021): 7–15. http://dx.doi.org/10.35784/pe.2021.1.01.

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The unprecedented global economic and social crisis caused by the coronavirus outbreak has not spared the energy sector. Using a dynamic model, we investigated the effect of COVID-19 cases on investor sentiments and stock returns of clean energy in the Asian-Pacific region. The results show that coronavirus cases negatively affect stock returns using investor sentiments as a transmission channel. We also find a negative effect of air pollution on stock returns. Since COVID-19 restricted trade and plummeted the oil prices, economies relied on non-renewable sources to meet energy demands. Nevert
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Asgari, Heshmatollah, and Hamed Najafi. "The Linkage between Sentiments and Stock Market Dynamics New Evidence from Iran." Journal of Business Administration Research 9, no. 2 (2020): 29. http://dx.doi.org/10.5430/jbar.v9n2p29.

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In recent years, the issue of financial behaviour and the impact of investors’ sentiments on their decision making have become such a popular issue. The sentiments of financial activists affect the market price of financial assets and particularly stocks, and therefore it is included in the new pricing models of capital assets. In this article, we seek the effect of investors’ sentiments on the dynamics of the Iranian stock market (TSE). To do this, among the companies accepted in the stock market we select 120, considering the research criteria and screening method, we examined TSE specifics
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Dissertations / Theses on the topic "Investor's sentiments"

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Hudson, Yawen. "Investor sentiment and herding : an empirical study of UK investor sentiment and herding behaviour." Thesis, Loughborough University, 2015. https://dspace.lboro.ac.uk/2134/17797.

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The objectives of this thesis are: first, to investigate the impact of investor sentiment in UK financial markets in different investment intervals through the construction of separate sentiment measures for UK investors and UK institutional investors; second, to examine institutional herding behaviour by studying UK mutual fund data; third, to explore the causal relation between institutional herding and investor sentiment. The study uses US, German and UK financial market data and investor sentiment survey data from 1st January 1996 to 30th June 2011. The impact of investor sentiment on UK e
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Liu, Jinjing. "Investor sentiment, institutional investors and the accrual anomaly : an empirical analysis of China's listed companies." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104518.

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Thesis: S.M. in Management Studies, Massachusetts Institute of Technology, Sloan School of Management, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 29-32).<br>The accrual anomaly is a phenomenon that investors gain future abnormal returns through accruals-based hedge portfolios. This paper first shows that China's institutional investors have a better understanding of the persistence of accounting accruals and they more accurately assess stock prices, and that an accrual-based hedge portfolio yields smaller future abnormal returns for firms with
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Chatterjee, Arijit. "Stock Prediction Analyzing Investor Sentiments." Diss., North Dakota State University, 2017. http://hdl.handle.net/10365/26045.

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We are going through a phase of data evolution where a major portion of the data from our daily lives is now been stored on social media platforms. In recent years, social media has become ubiquitous and important for social networking and content sharing. Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. In the financial sector, sentiments are also of paramount importance, and this dissertation mainly focuses on the effect of sentiments from investors [3] on the behavior of stock
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Salhin, Ahmed. "Managerial sentiment, investor sentiment and stock returns." Thesis, Heriot-Watt University, 2017. http://hdl.handle.net/10399/3375.

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It is well established that investor sentiment plays a vital role in global financial markets. However, the sentiment of other economic agents has received less attention in the behavioural finance literature. This thesis aims to address the impact of managerial sentiment on the UK stock market. It investigates the performance of managerial sentiment in predicting stock returns relative to investor and consumer sentiments. In addition, it examines how sentiment is transmitted from managers to investors and whether the response of investor sentiment is asymmetric towards positive versus negativ
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Wang, Jessica Yichun. "Investor attention and sentiment." Thesis, University of East Anglia, 2015. https://ueaeprints.uea.ac.uk/56867/.

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Investor sentiment and attention are often linked to the same non-economic events making it difficult to understand why and how asset prices are affected. This thesis disentangles these two potential drivers of market behaviour by studying how investors react to sports outcomes, weather conditions and merger and acquisition announcements. Firstly, a new dataset of medals for major participating countries and sponsor firms over four Summer Olympic Games is analysed. Results show that although Olympic success does not lead to abnormal stock returns, subsequent market activity is reduced substant
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Brookins, Benjamin David Lee. "Investor sentiment and stock returns." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/88379.

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Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, 2014.<br>Title as it appears in MIT degrees awarded booklet, February 2014: Sentiment shocks and stock returns. Cataloged from PDF version of thesis.<br>Includes bibliographical references (page 45).<br>Since Keynes coined the term animal spirits economists have been debating what the real impact human psychology is on economic variables. The major challenge in identifying these effects is the close ties between negative (positive) emotions and poor (good) future real outlook. I exploit a hi
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Ren, Jinjuan, and 任錦娟. "Investor sentiments, agency conflicts, and IPO underpricing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B42664342.

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Ren, Jinjuan. "Investor sentiments, agency conflicts, and IPO underpricing." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B42664342.

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Watkins, Boyce Dewhite. "Investor Sentiment, Trading Patterns and Return Predictability." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1038859045.

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Hao, Rui. "Option Pricing Model with Investor Sentiment." Thesis, Uppsala universitet, Tillämpad matematik och statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-325168.

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Books on the topic "Investor's sentiments"

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Burghardt, Matthias. Retail Investor Sentiment and Behavior. Gabler, 2011. http://dx.doi.org/10.1007/978-3-8349-6170-9.

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Barberis, Nicholas. A model of investor sentiment. National Bureau of Economic Research, 1997.

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Polk, Christopher. The real effects of investor sentiment. National Bureau of Economic Research, 2004.

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Baker, Malcolm. Investor sentiment in the stock market. National Bureau of Economic Research, 2007.

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Angeletos, Marios. Private sunspots and idiosyncratic investor sentiment. National Bureau of Economic Research, 2008.

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Baker, Malcolm. Investor sentiment in the stock market. National Bureau of Economic Research, 2007.

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Angeletos, Marios. Private sunspots and idiosyncratic investor sentiment. Massachusetts Institute of Technology, Dept. of Economics, 2008.

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Lee, Charles. Investor sentiment and the closed-end puzzle. LSE Financial Markets Group, 1990.

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Stambaugh, Robert F. The short of it: Investor sentiment and anomalies. National Bureau of Economic Research, 2011.

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Lamont, Owen A. Investor sentiment and corporate finance: Micro and macro. National Bureau of Economic Research, 2005.

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Book chapters on the topic "Investor's sentiments"

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Burghardt, Matthias. "Investor Sentiment Construction." In Retail Investor Sentiment and Behavior. Gabler, 2011. http://dx.doi.org/10.1007/978-3-8349-6170-9_3.

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Burghardt, Matthias. "Retail Investor Herding." In Retail Investor Sentiment and Behavior. Gabler, 2011. http://dx.doi.org/10.1007/978-3-8349-6170-9_5.

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Dhankar, Raj S. "Investor Sentiment and Returns." In Capital Markets and Investment Decision Making. Springer India, 2019. http://dx.doi.org/10.1007/978-81-322-3748-8_13.

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Burghardt, Matthias. "Introduction." In Retail Investor Sentiment and Behavior. Gabler, 2011. http://dx.doi.org/10.1007/978-3-8349-6170-9_1.

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Burghardt, Matthias. "Related Theoretical and Empirical Work." In Retail Investor Sentiment and Behavior. Gabler, 2011. http://dx.doi.org/10.1007/978-3-8349-6170-9_2.

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Burghardt, Matthias. "Construction of the Euwax Sentiment Index." In Retail Investor Sentiment and Behavior. Gabler, 2011. http://dx.doi.org/10.1007/978-3-8349-6170-9_4.

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Burghardt, Matthias. "The Predictive Power of Retail Investor Sentiment." In Retail Investor Sentiment and Behavior. Gabler, 2011. http://dx.doi.org/10.1007/978-3-8349-6170-9_6.

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Burghardt, Matthias. "Conclusion and Future Work." In Retail Investor Sentiment and Behavior. Gabler, 2011. http://dx.doi.org/10.1007/978-3-8349-6170-9_7.

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Liao, Mei-Hua, Chieh-Lin He, Ruirui Cui, and Ya-Lan Chan. "Investor Sentiment and Governance Mechanisms." In Innovative Mobile and Internet Services in Ubiquitous Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50399-4_57.

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Liao, Mei-Hua, Chun-Min Wang, and Ya-Lan Chan. "Investor Sentiment and Business Cycle." In Proceedings of the 4th Asia Pacific Management Research Conference (APMRC 2022). Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-076-3_14.

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Conference papers on the topic "Investor's sentiments"

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Kurnianingrum, Dian, Rachel Monica, Rosyidah Rahmah, Okky Rizkia Yustian, Isma Addi Jumbri, and Budi Rustandi Kartawinata. "Engaging Investors through Social Media: A Positive Sentiment Analysis of Emtrade’s Twitter." In 2024 International Conference on Intelligent Computing and Sustainable Innovations in Technology (IC-SIT). IEEE, 2024. https://doi.org/10.1109/ic-sit63503.2024.10862122.

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Madhuri, N., R. Tamilkodi, M. Sai Teja, M. Arjun Kumar, N. Ravi Swaroop, and L. Jayaprakash. "Investor Sentiment based Predictive Stock Market Forecasting using Deep Learning." In 2024 5th International Conference on Data Intelligence and Cognitive Informatics (ICDICI). IEEE, 2024. https://doi.org/10.1109/icdici62993.2024.10810985.

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Miao, Jia, Jianwu Lin, Tong Luo, and Guangling Liu. "Investor Sentiment Analysis of Financial Texts Based on GPT and RoBERTa." In 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650089.

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Hingane, Suraj, Manasi Bhate, Prakash Ukhalkar, Ravikant Zirmite, and Swati Hingane. "Exploring Investor Sentiment and Nifty 50 Volatility: A Behavioural Finance Perspective." In 2024 8th International Conference on Computing, Communication, Control and Automation (ICCUBEA). IEEE, 2024. https://doi.org/10.1109/iccubea61740.2024.10774954.

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Das, Tapas, Saidia Jeelani, Seshanwita Das, Pratibha Giri, and Arnab Chatterjee. "Utilizing Machine Learning to Analyze Investor Sentiment and Detect Market Anomalies." In 2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES). IEEE, 2024. https://doi.org/10.1109/ic3tes62412.2024.10877536.

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Karamadi, Swetha, Gopalakrishnan Chinnasamy, and Vinoth S. "Predictive Modelling of Investor Sentiment and Preferences in Green Bonds Using Machine Learning." In 2025 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE). IEEE, 2025. https://doi.org/10.1109/iitcee64140.2025.10915472.

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MAKNICKIENĖ, Nijolė, Jovita MASĖNAITĖ, Viktorija STASYTYTĖ, and Raimonda MARTINKUTĖ-KAULIENĖ. "INVESTIGATION OF THE HERDING AND CONTRARIAN BEHAVIOUR OF INVESTORS." In International Scientific Conference „Contemporary Issues in Business, Management and Economics Engineering". Vilnius Gediminas Technical University, 2021. http://dx.doi.org/10.3846/cibmee.2021.596.

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Purpose – The paper analyses two different paradigms of investor behaviour that exist in the financial mar-ket – the herding and contrarian behaviour. The main objective of the paper is to determine which pattern of investor behaviour better reflects the real changes in the prices of financial instruments in the financial markets. Research methodology – Algorithms of technical analysis, deep learning and classification of sentiments were used for the research; data of positions held by investors were analysed. Data mining was performed using “Tweet Sentiment Visualization” tool. Findings – The
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Maknickienė, Nijolė, and Lina Rapkevičiūtė. "A STUDY ON SOCIAL MEDIA OPINION ABOUT WOMEN INVESTORS." In International Scientific Conference „Contemporary Issues in Business, Management and Economics Engineering". Vilnius Gediminas Technical University, 2021. http://dx.doi.org/10.3846/cibmee.2021.625.

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Purpose – to investigate opinions on social networks about women’s investment and its determinants. Social network sentiment research aims to find out why investing remains a very masculine area of life. Research methodology – Twitter social network analysis tools will be used for data mining. Word clouds and sentiment index will be obtained using neural network classification algorithm based on Long Short-Term Memory (LSTM). Findings – the paper obtained the dynamics of three-week opinions on the social network Twitter, considering the main factors that influence women’s choice to invest. Res
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XIE, RUOTING. "THE IMPACT OF INVESTOR SENTIMENT ON THE RETURN OF STOCKS—EMPIRICAL ANALYSIS BASED ON THE DCC-GARCH MODEL." In 2021 INTERNATIONAL CONFERENCE ON ADVANCED EDUCATION AND INFORMATION MANAGEMENT (AEIM 2021). Destech Publications, Inc., 2021. http://dx.doi.org/10.12783/dtssehs/aeim2021/35991.

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Abstract. With the gradual inapplicability of the “rational man” and the efficient market hypothesis in the contemporary financial field, modern finance represented by behavioral finance has emerged. Behavioral finance is guided by the study of human psychology and behavior, exploring the internal connections and fluctuations in the financial market. Investor sentiment is often regarded as the most effective data reflected from a human perspective. Therefore, this article selects the monthly data of CICSI Investor Sentiment Index, Shenzhen Component Index, and Shanghai Composite Index logarith
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Bhatt, Saachin, Mustansar Ghazanfar, and Mohammad Hossein Amirhosseini. "Machine Learning based Cryptocurrency Price Prediction using Historical Data and Social Media Sentiment." In 5th International Conference on Machine Learning & Applications. Academy & Industry Research Collaboration, 2023. http://dx.doi.org/10.5121/csit.2023.131001.

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The purpose of this research is to investigate the impact of social media sentiments on predicting the Bitcoin price using machine learning models, with a focus on integrating onchain data and employing a Multi Modal Fusion Model. For conducting the experiments, the crypto market data, on-chain data, and corresponding social media data (Twitter) has been collected from 2014 to 2022 containing over 2000 samples. We trained various models over historical data including K-Nearest Neighbors, Logistic Regression, Gaussian Naive Bayes, Support Vector Machine, Extreme Gradient Boosting and a Multi Mo
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Reports on the topic "Investor's sentiments"

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Qiu, Lily, and Ivo Welch. Investor Sentiment Measures. National Bureau of Economic Research, 2004. http://dx.doi.org/10.3386/w10794.

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Barberis, Nicholas, Andrei Shleifer, and Robert Vishny. A Model of Investor Sentiment. National Bureau of Economic Research, 1997. http://dx.doi.org/10.3386/w5926.

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Polk, Christopher, and Paola Sapienza. The Real Effects of Investor Sentiment. National Bureau of Economic Research, 2004. http://dx.doi.org/10.3386/w10563.

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Angeletos, George-Marios. Private Sunspots and Idiosyncratic Investor Sentiment. National Bureau of Economic Research, 2008. http://dx.doi.org/10.3386/w14015.

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Baker, Malcolm, and Jeffrey Wurgler. Investor Sentiment in the Stock Market. National Bureau of Economic Research, 2007. http://dx.doi.org/10.3386/w13189.

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Stambaugh, Robert, Jianfeng Yu, and Yu Yuan. The Short of It: Investor Sentiment and Anomalies. National Bureau of Economic Research, 2011. http://dx.doi.org/10.3386/w16898.

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Lee, Charles, Andrei Shleifer, and Richard Thaler. Investor Sentiment and the Closed-End Fund Puzzle. National Bureau of Economic Research, 1990. http://dx.doi.org/10.3386/w3465.

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Lamont, Owen, and Jeremy Stein. Investor Sentiment and Corporate Finance: Micro and Macro. National Bureau of Economic Research, 2005. http://dx.doi.org/10.3386/w11882.

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Dumas, Bernard, Alexander Kurshev, and Raman Uppal. What Can Rational Investors Do About Excessive Volatility and Sentiment Fluctuations? National Bureau of Economic Research, 2005. http://dx.doi.org/10.3386/w11803.

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Baker, Malcolm, and Jeffrey Wurgler. Investor Sentiment and the Cross-Section of Stock Returns. National Bureau of Economic Research, 2004. http://dx.doi.org/10.3386/w10449.

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