Investor Sentiment

Investor Sentiment and Market Movements: A Granger Causality Perspective ArXiv ID: 2510.15915 “View on arXiv” Authors: Tamoghna Mukherjee Abstract The stock market is heavily influenced by investor sentiment, which can drive buying or selling behavior. Sentiment analysis helps in gauging the overall sentiment of market participants towards a particular stock or the market as a whole. Positive sentiment often leads to increased buying activity and vice versa. Granger causality can be applied to ascertain whether changes in sentiment precede changes in stock prices.The study is focused on this aspect and tries to understand the relationship between close price index and sentiment score with the help of Granger causality inference. The study finds a positive response through hypothesis testing. ...

Investor Sentiment in Asset Pricing Models: A Review of Empirical Evidence ArXiv ID: 2411.13180 “View on arXiv” Authors: Unknown Abstract This study conducted a comprehensive review of 71 papers published between 2000 and 2021 that employed various measures of investor sentiment to model returns. The analysis indicates that higher complexity of sentiment measures and models improves the coefficient of determination. However, there was insufficient evidence to support that models incorporating more complex sentiment measures have better predictive power than those employing simpler proxies. Additionally, the significance of sentiment varies based on the asset and time period being analyzed, suggesting that the consensus relying on the BW index as a sentiment measure may be subject to change. ...

Internet sentiment exacerbates intraday overtrading, evidence from A-Share market ArXiv ID: 2404.12001 “View on arXiv” Authors: Unknown Abstract Market fluctuations caused by overtrading are important components of systemic market risk. This study examines the effect of investor sentiment on intraday overtrading activities in the Chinese A-share market. Employing high-frequency sentiment indices inferred from social media posts on the Eastmoney forum Guba, the research focuses on constituents of the CSI 300 and CSI 500 indices over a period from 01/01/2018, to 12/30/2022. The empirical analysis indicates that investor sentiment exerts a significantly positive impact on intraday overtrading, with the influence being more pronounced among institutional investors relative to individual traders. Moreover, sentiment-driven overtrading is found to be more prevalent during bull markets as opposed to bear markets. Additionally, the effect of sentiment on overtrading is observed to be more pronounced among individual investors in large-cap stocks compared to small- and mid-cap stocks. ...

Causality between investor sentiment and the shares return on the Moroccan and Tunisian financial markets ArXiv ID: 2305.16632 “View on arXiv” Authors: Unknown Abstract This paper aims to test the relationship between investor sentiment and the profitability of stocks listed on two emergent financial markets, the Moroccan and Tunisian ones. Two indirect measures of investor sentiment are used, SENT and ARMS. These sentiment indicators show that there is an important relationship between the stocks returns and investor sentiment. Indeed, the results of modeling investor sentiment by past observations show that sentiment has weak memory; on the other hand, series of changes in sentiment have significant memory. The results of the Granger causality test between stock return and investor sentiment show us that profitability causes investor sentiment and not the other way around for the two financial markets studied.Thanks to four autoregressive relationships estimated between investor sentiment, change in sentiment, stock return and change in stock return, we find firstly that the returns predict the changes in sentiments which confirms with our hypothesis and secondly, the variation in profitability negatively affects investor sentiment.We conclude that whatever sentiment measure is used there is a positive and significant relationship between investor sentiment and profitability, but sentiment cannot be predicted from our various variables. ...

A Risk Perception Primer: A Narrative Research Review of the Risk Perception Literature in Behavioral Accounting and BehavioralFinance ArXiv ID: ssrn-566802 “View on arXiv” Authors: Unknown Abstract A significant topic within the behavioral finance literature is the notion of perceived risk pertaining to novice investors (i.e. individuals, finance students) Keywords: Behavioral finance, Perceived risk, Novice investors, Investor sentiment, Risk tolerance Complexity vs Empirical Score Math Complexity: 1.0/10 Empirical Rigor: 0.5/10 Quadrant: Philosophers Why: The paper is a narrative literature review focusing on conceptual definitions and theoretical frameworks of risk perception, with no original mathematical modeling, empirical testing, or implementation details. flowchart TD RQ["Research Goal:<br>Examine risk perception in<br>behavioral finance/accounting"] --> Method["Methodology:<br>Narrative literature review"] Method --> Inputs["Key Inputs:<br>- Novice investor studies<br>- Behavioral finance models<br>- Risk tolerance metrics"] Inputs --> Comp["Analysis Process:<br>Identify patterns &<br>theoretical frameworks"] Comp --> Outcome1["Outcome 1:<br>Perceived risk ≠<br>actual financial risk"] Comp --> Outcome2["Outcome 2:<br>Heuristics & biases<br>drive investor sentiment"] Comp --> Outcome3["Outcome 3:<br>Education gaps in<br>novice risk assessment"]

Is Money Really ‘Smart’? New Evidence on the Relation between Mutual Fund Flows, Manager Behavior, and Performance Persistence ArXiv ID: ssrn-414420 “View on arXiv” Authors: Unknown Abstract Mutual fund returns strongly persist over multi-year periods - that is the central finding of this paper. Further, consumer and fund manager behavior both play Keywords: Mutual Fund Persistence, Performance Persistence, Fund Manager Behavior, Investor Sentiment, Long-Term Returns, Mutual Funds Complexity vs Empirical Score Math Complexity: 4.0/10 Empirical Rigor: 8.5/10 Quadrant: Street Traders Why: The paper employs extensive empirical data analysis (CRSP mutual fund database, cross-sectional regressions, style adjustments) to test hypotheses about fund flows and performance, but uses relatively standard financial econometrics without complex mathematical derivations. flowchart TD A["Research Goal<br>Test Persistence of Mutual Fund Returns<br>and Roles of Manager Behavior & Flows"] --> B["Key Methodology<br>Longitudinal Performance Analysis"] B --> C{"Data / Inputs"} C --> C1["Multi-Year Mutual Fund Returns"] C --> C2["Manager Behavior Data"] C --> C3["Net Flows & Investor Sentiment"] C1 & C2 & C3 --> D["Computational Process<br>Regression & Persistence Metrics"] D --> E["Key Findings / Outcomes"] E --> E1["Strong Multi-Year Persistence Found"] E --> E2["Manager Behavior Explains Persistence"] E --> E3["Flows Reinforce Manager Behavior"]