Working Papers

Thispaperstudieshowretailinvestorsform-andcontinuallyreshape-theirbeliefsabout future stock returns. Far from being anchored solely in economic fundamentals or rational expectations, investor beliefs emerge here as the outcome of an interplay among competing voices in the information ecosystem. Harnessing a uniquely comprehensive dataset of survey- based return expectations, coupled with text analyses of analyst reports and financial shows aired on 42 local news channels, I find that the sheer volume and prominence of certain analyst forecasts decisively shift investors’ views on the equity risk premium. When widely visible outlets broadcast optimistic signals - particularly about earnings growth - retail ex- pectations surge in a way that is both large and enduring, persisting for months. In contrast, less trumpeted insights from “quiet” experts are roundly ignored by the investing public, even though they contain predictive power for market returns. Remarkably, this attention- driven learning dynamic holds across almost all demographic segments, from high-net-worth investors to novices with modest portfolios. My findings present a new framework for under- standing how pockets of information can powerfully amplify or dampen collective sentiment. By revealing how specific streams of market information tip the scales of investor belief, I illuminate a potent channel through which narratives, rather than strict fundamentals alone, shape price dynamics.

Does the social identity of an investor affect information diffusion in financial markets? Using detailed holdings data for actively managed U.S. equity mutual funds from 1999 to 2022, I document a structural asymmetry in how the market processes information from male versus female managers. Portfolios mimicking the high-conviction buy trades of female managers generate significant abnormal returns for up to two quarters following disclosure, suggesting that female-originated signals diffuse slowly into prices. In contrast, male-originated buy signals are incorporated immediately, leaving no post-disclosure alpha. On the sell side, contrarian portfolios buying stocks sold by male managers yield large and persistent positive abnormal returns, whereas sell decisions by female managers elicit muted and delayed price responses. To identify the underlying mechanisms, I analyze heterogeneity in managerial visibility and social connectedness. Fund size (total net assets) and alumni network centrality strongly condition the speed of price incorporation for female managers but have little explanatory power for male managers. Female managers generate delayed abnormal returns only at intermediate levels of visibility or alumni centrality; at high levels, their ideas are incorporated immediately, consistent with faster information diffusion. In contrast, male managers’ trades are rapidly priced regardless of fund size or network position. Direct evidence from peer-response regressions shows that both male and female managers disproportionately react to trades made by male managers, while female-originated signals diffuse slowly and often indirectly. Stratified placebo tests confirm that these results are not artifacts of sample size or fund characteristics. Together, the results show that information diffusion depends crucially on the social position of their originators. Gender operates as a friction in information transmission: male managers occupy central positions in informal information networks and command immediate attention, while female managers face higher visibility thresholds before their ideas are efficiently incorporated into prices. These findings have implications for asset pricing, institutional trading, and the economic consequences of underrepresentation in financial markets.

Differences of opinion are central to theories of trading and volatility, yet existing disagreement proxies are too low-frequency or rely on platform-specific investor tags. We develop a replicable, daily disagreement measure in an unlabeled social-media environment and study how belief heterogeneity maps into trading in China’s A-share market. Using 52.3 million investor comments for CSI 300 constituents from 2016–2025, we implement an LLM stance-simulation design: prompt-engineered Neutral, Bullish, and Bearish agents generate training labels that we scale with three parallel BERT classifiers to construct within-group (information uncertainty) and cross-group (model conflict) disagreement. Within-group disagreement robustly predicts lower abnormal trading volume, whereas cross-group disagreement predicts higher volume. Mechanism tests show the within-group effect strengthens in high policy uncertainty, consistent with a value-of-waiting channel, while cross-group effects are amplified, consistent with gains from trade under competing valuation models. Taken together, our results imply that the trading consequences of disagreement depend on whether it captures within-model noise or across-model conflict, contributing to the heterogeneous-beliefs literature; our stance-simulation design further delivers a reproducible way to construct belief-heterogeneity measures in environments with scarce investor-type labels.

We find that firm-specific social media tone influences leveraged trading. A more positive tone predicts greater next-day net margin purchasing, driven predominantly by sentiment. High margin purchasing following positive social media tone consistently yields inferior performance over both short and long horizons. Short sellers are collectively more sophisticated. They capitalize on fluctuations in social media tone, both positive and negative, through strategies that adjust to different tone windows and holding periods. While experienced, rational short sellers can swiftly profit from temporary negative sentiment, high short selling following persistently high social media tone is highly profitable over longer horizons.

Social media platforms such as Twitter influence capital markets by rapidly disseminating information, yet this environment is increasingly shaped by non-human bots. Building on theories of investor attention and information salience, we examine whether bots amplify market reactions to earnings news by directing attention toward larger surprises. Using machine learning to classify 12.02 million tweets discussing S&P 1,500 firms in 2018, we measure firm-specific abnormal bot activity and analyze its association with market responses to earnings announcements. We find that bot activity amplifies the relationship between earnings surprises and abnormal returns. Additional analyses reveal that this effect is stronger when bot sentiment is positive but diminishes with excessive positivity, varies by bot type, and is most pronounced for firms with fewer analysts, further supporting our investor attention argument. Our findings highlight bots' role as "attention amplifiers" and underscore the need for greater scrutiny of algorithmic actors in financial markets.

This paper models stock manipulations where investors interact via social network communications. We propose a novel noise index in social media platforms. The model predicts that high volumes of social media noise significantly increase probability of success, profitability for manipulators as well as heighten trading volume of manipulated stocks. In addition, manipulation profitability increases with respect to the number of followers in social media posts mentioned the manipulated stock. Empirical investigations, based on over 3,800 U.S. small-cap stocks during January 2010 to 2018 December, confirm the theoretical predictions and hypotheses. Our paper demonstrates an urgent need for monitoring social media platforms in safeguarding financial market efficiency.

We study dynamic visual representations as a proxy for investor sentiment about the stock market. Our sentiment index, GIFsentiment, is constructed from millions of posts in the Graphics Interchange Format (GIF) on a leading investment social media platform. GIFsentiment correlates with seasonal mood variations and the severity of COVID lockdowns. It is positively associated with contemporaneous market returns and negatively predicts returns for up to four weeks, even after controlling for other sentiment and attention measures. These effects are stronger among portfolios that are more susceptible to mispricing. GIFsentiment positively predicts trading volume, market volatility, and flows toward equity funds and away from debt funds. Our evidence suggests that GIFsentiment is a proxy for misperceptions that are later corrected.

Utilizing a nearest-neighbor research design, I find that households exposed to green neighbors within 0.1 miles are 1.6 times more likely to make their homes green within a year than unexposed households. The exposure also increases the likelihood of multi-property owners certifying their faraway secondary prop- erties green, emphasizing that information from neighbors, not neighborhood characteristics alone, drives the effect. While financial benefits including green homeprices,electricitysavings,andregulatoryincentivesstrengthenpeereffects, pro-environmentalpreferencesdonot. Aninformation-cost-baseddiscretechoice modelexplainsthefindingsandsuggeststhatincorporatingpeereffectmetricsin subsidiesmayaccelerategreenhomeinvestments.

We use psychological game theory, cognitive dissonance, and network analysis to investigate how economic connections within firms and social connections outside of firms play a role in determining corporate culture. We demonstrate how employees’ social interactions and work interactions create networks in which their behavior can influence the behavior of others. Agents can play cooperatively or non-cooperatively in social and work networks, with equilibrium behavior in each network influenced by the behavior of others in the network. We show how non-cooperative behavior in psychological games played in social networks can be contagious, with otherwise cooperative players shifting to playing non-cooperatively. Because these players are also part of employee networks, contagion of “bad” behavior in social networks can spread to employee networks within firms and across firms. The main lesson of our analysis is that a firm’s culture does not exist in isolation from the culture of the society in which the firm is embedded. Contagion of non-cooperative behavior can begin far away from the network of the firm’s employees and eventually invade the firm. This invasion is less likely, the culture of the firm is more resilient, if the social density of its set of workers is large or if the critical value for invasion is low. If this gap is large, the firm’s culture can withstand shocks to either the social density of its workers or to the payoffs to cooperative behavior; but if it is small, even a slight perturbation in the network can cause a collapse in the firm’s culture.

Weexaminetheimpactoffinancialinfluencers(“finfluencers”)onretailinvestmentusingrealequity andderivativeinvestmentsacrossfourNordiccountries. Usinganinstrumentthatrandomlyassigns influencers to followers, we find the following: (1) Investors tend to follow influencers with high Sharpe ratios, frequent trades, a shared country of residence or language, and male gender. (2) Influencers affect followers’ portfolios and trading behavior, particularly when they have a large following, a central network position, or participate in group discussions. This effect is strongest for investors who follow fewer influencers, female investors, and when trading passive funds.

Do workplace ties among mutual fund managers channel value-relevant information, and what organizational structures facilitate workplace information flows? We introduce a novel measure of skill-weighted inter-fund comanager connections (ICC) to answer this question. ICC funds exhibit more similar portfolio holdings to connected funds and higher risk-adjusted returns than non-ICC funds. Causality is identified through plausibly exogenous shocks from superstar manager departures. Sharing value-relevant information is the source of this advantage: ICC funds generate abnormal returns on overlapping holdings in non-local and hard-to-research stocks. Finally, we present the first evidence of the evolution of workplace networks in the mutual fund industry. 1 Delegated investment managers earn economic rent from their informational advantages. Prior research shows that connections with other informed economic agents play an important role in explaining mutual fund portfolio decisions and performance. For instance, extant studies link fund performance to educational ties with corporate board members (Cohen, Frazzini, and Malloy 2008) and social connections with financial analysts and auditors (Gu et al. 2019; Chen et al. 2022). Other work highlights the role of geographical proximity in explaining fund portfolio overlaps, attributing such overlaps to social connections among portfolio managers (Hong, Kubik, and Stein 2005; Pool, Stoffman, and Yonker 2015). However, relatively little is known about the extent to which professional managers' social connections in the workplace influence their portfolio performance. Fund managers’ professional ties are primarily forged within their respective fund families. On the one hand, membership in a fund family facilitates better performance through economies of scale and enhanced information sharing (e.g. Chen et al. 2004; Brown and Wu 2016). On the other hand, managers within the same family face both competitive and collaborative ince

We investigate whether economic narratives in sermons influence individuals' financial decisions. Leveraging geographic variation in membership density of The Church of Jesus Christ of Latter-day Saints, we examine whether regions with more Church members exhibit relatively less indebtedness when Church leaders speak about debt avoidance in worldwide broadcasts. We show that the household debt-to-income ratio is relatively lower in regions with more Church members during years with debt-avoidance sermons. Our models suggest that this effect is economically meaningful, and several additional analyses corroborate our conclusions. Overall, our findings emphasize the importance of narratives originating beyond the usual setting of capital markets to better understand how individuals make financial decisions.