{"title":"The Distribution of Investor Beliefs, Stock Ownership and Stock Returns","authors":"G. Hardouvelis, Georgios Karalas, Dimitri Vayanos","doi":"10.2139/ssrn.3824433","DOIUrl":"https://doi.org/10.2139/ssrn.3824433","url":null,"abstract":"We study theoretically and empirically the relationship between investor beliefs, ownership \u0000dispersion and stock returns. We find that high dispersion, measured by high breadth or low \u0000Herfindahl index, forecasts returns positively for large stocks, as in Chen, Hong, and Stein (2002), \u0000but negatively for small stocks. We explain that relationship in a difference-of-opinion model \u0000in which stocks differ in the size of investor disagreements and the extent of belief polarization. \u0000These differences are characterized by range and kurtosis, respectively. Proxying investor beliefs \u0000by analyst forecasts, we find that range and kurtosis affect ownership dispersion in the way that \u0000our model predicts.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122182480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Microstructure of Cointegrated Assets","authors":"Sasha Stoikov, Peter Decrem, Yikai Hua, Anne Shen","doi":"10.2139/ssrn.3824298","DOIUrl":"https://doi.org/10.2139/ssrn.3824298","url":null,"abstract":"We define the micro price of multiple cointegrated assets. This yields a notion of fair prices, as a function of the observable state of multiple order books. We compute the microprices of two highly cointegrated assets, using Level-1 data collected on Interactive Brokers. We design an execution algorithm based on this two dimentional microprice and show that it can save half of the bid-ask spread cost.<br><br>The code for this paper is available here: https://github.com/xhshenxin/Micro_Price","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116667021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Changes in the DJIA: Market Reactions and Impact of Estimation Window","authors":"Patricia A. Ryan, Sriram V Villupuram","doi":"10.2139/ssrn.3823523","DOIUrl":"https://doi.org/10.2139/ssrn.3823523","url":null,"abstract":"Changes in the DJIA from 1929-2019 are examined to evaluate the immediate and long-term market reaction after a component change in the DJIA. Using multiple event study methodologies, there is a clear increase in wealth when a firm is added to the DJIA and a decrease in wealth around the time of deletion from the DJIA. Additions earn positive abnormal returns regardless of estimation window. The choice of estimation window is critical for deletions as we show that this is the reason for the difference in results in the literature. Using a post-estimation window, deletions have a more significant negative wealth effect. Using pre-estimation window, returns are negative post announcement, but not at the announcement. Long term, firms added to the DJIA have positive abnormal returns in the second year after inclusion. Deletions from the DJIA after the Great Depression have negative returns three years after removal thus implying a potential investment opportunity upon DJIA changes. <br>","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133475672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Monetary Policy, Twitter and Financial Markets: Evidence from Social Media Traffic","authors":"D. Masciandaro, Davide Romelli, Gaia Rubera","doi":"10.2139/ssrn.3823185","DOIUrl":"https://doi.org/10.2139/ssrn.3823185","url":null,"abstract":"How does central bank communication affect financial markets? This paper shows that the monetary policy announcements of three major central banks, i.e. the European Central Bank, the Federal Reserve and the Bank of England, trigger significant discussions on monetary policy on Twitter. Using machine learning techniques we identify Twitter messages related to monetary policy around the release of monetary policy decisions and we build a metric of the similarity between the policy announcement and Twitter traffic before and after the announcement. We interpret large changes in the similarity of tweets and announcements as a proxy for monetary policy surprise and show that market volatility spikes after the announcement whenever changes in similarity are high. These findings suggest that social media discussions on central bank communication are aligned with bond and stock market reactions.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129275632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Information Inertia and Limited Information Processing Capacity in Selecting Index ETFs","authors":"Yizhe Xie, Darcy Pu","doi":"10.2139/ssrn.3881432","DOIUrl":"https://doi.org/10.2139/ssrn.3881432","url":null,"abstract":"We investigate the role of information inertia and limited information processing capacity in creating an anomaly in the US index ETF industry. We fi nd that tracking errors and long-term returns are significant and consistent predictors of future returns, while there is little evidence that investors' flows are sensitive to them. In line with this finding, we provide a trading strategy that chases small tracking errors, which outperforms the equal-weighted portfolio of all S&P 500 index ETFs by 1.65% annually over 2003-2020. Mutual fund managers who just joined the fund are more likely to switch to better index ETFs than existing managers, suggesting investors face information inertia. Unsophisticated investors have limited information processing capacity as index ETFs held by more institutional investors deliver higher returns. Overall, our results suggest that the anomaly in low-return and low-tracking error sensitivity in the index ETF industry can be explained by information inertia and limited information processing capacity.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123420727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Extrapolative Market Participation","authors":"Wanbin Pan, Zhiwei Su, Jianfeng Yu","doi":"10.2139/ssrn.3830569","DOIUrl":"https://doi.org/10.2139/ssrn.3830569","url":null,"abstract":"This paper proposes a simple dynamic asset pricing model featuring extrapolative market participation by retail investors, that is, increased market participation following high returns in the stock market and high new participation growth (NPG). The model implies that extrapolative market participation induces asset bubbles and large trading volume and produces momentum and value effects simultaneously. More important, the model also implies that NPG positively predicts momentum strategy returns and negatively predicts value strategy returns. Using a composite measure for NPG, we find empirical support for these predictions. The momentum effect is 1.96% per month following high NPG and only 0.51% following low NPG, whereas the value effect is -0.10% per month following high NPG and 0.68% following low NPG. A similar, albeit weaker, pattern also holds for the time-series momentum and value effect.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115805425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Stock Sale Induced by Anxiety in the Face of Risk","authors":"Seiya Kuno, Y. Osaki","doi":"10.2139/ssrn.3809596","DOIUrl":"https://doi.org/10.2139/ssrn.3809596","url":null,"abstract":"It is observed that stock price fluctuations are slowly in upward phases like bubble, but fast in downward phases like its burst. This paper provides a new theoretical explanation of this phenomenon, especially why stock price drops sharply, based on the timing of stock sales. Investors tend to be more risk averse when the timing of decision making is closer for the present. This tendency can explain that the timing of stock sales is different according to risk aversion. When investors become excessive risk averse, they tend to sell stocks more in the present. This result is consistent with asymmetric patterns of stock price fluctuation when investors are moderate risk averse in normal economic conditions, but excessive risk averse in abnormal economic condition like the fear of financial crises.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123328704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Partisan Return Gap: The Polarized Stock Market in the Time of a Pandemic","authors":"Jinfei Sheng, Zheng Sun, Wanyi Wang","doi":"10.2139/ssrn.3809575","DOIUrl":"https://doi.org/10.2139/ssrn.3809575","url":null,"abstract":"Using two proxies for investors’ political affiliation, we document sharp differences in stock returns between firms likely dominated by Democratic investors (blue stocks) and those dominated by Republican investors (red stocks) during the COVID pandemic. Red stocks have 20 basis points higher risk-adjusted returns than blue stocks on COVID news days (Partisan Return Gap). Lockdown policies, COVID cases, industry and firm fundamentals only explain at most 40% of the return gap. Polarized political beliefs about COVID, revealed through people’s social distancing behavior, contribute to about 40% of the return gap beyond the fundamental channel. Our paper provides partisanship as a novel aspect in understanding abnormal stock returns during the pandemic. This paper was accepted by Lukas Schmid, finance. Supplemental Material: The data and e-companion are available at https://doi.org/10.1287/mnsc.2023.4913 .","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129217780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dissecting Climate Risks: Are they Reflected in Stock Prices?","authors":"Renato Faccini, R. Matin, G. Skiadopoulos","doi":"10.2139/ssrn.3795964","DOIUrl":"https://doi.org/10.2139/ssrn.3795964","url":null,"abstract":"We construct novel proxies of aggregate physical and transition climate risks by conducting textual analysis of Reuters climate-change news over 2000-2018. This analysis uncovers four textual risk factors related to the topics of U.S. climate policy, international summits, natural disasters, and global warming, respectively. The first two factors proxy transition risks, whereas the last two proxy physical risks. We find that only the climate policy factor is priced in the U.S. stock market, with the evidence being more pronounced over 2012-2018. The documented positive premium is consistent with the argument that investors hedge short-term transition risks. We validate this explanation using a narrative approach to mark the content of climate news. Our results imply that investors' attention is an important driver of asset returns.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122206680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Bradley, Jan Hanousek Jr., Russell Jame, Zicheng Xiao
{"title":"Place Your Bets? The Market Consequences of Investment Research on Reddit's Wallstreetbets","authors":"D. Bradley, Jan Hanousek Jr., Russell Jame, Zicheng Xiao","doi":"10.2139/ssrn.3806065","DOIUrl":"https://doi.org/10.2139/ssrn.3806065","url":null,"abstract":"We examine the market consequences of due diligence (DD) reports on Reddit’s Wallstreetbets (WSB) platform. We find average ‘buy’ recommendations result in two-day announcement returns of 1.1%. Further, the returns drift upwards by 2% over the subsequent month and nearly 5% over the subsequent quarter. Retail trading increases sharply in the intraday window following publication, and retail investors are more likely to be net buyers following reports that earn larger returns. Thus, in sharp contrast to regulators concerns that WSB investment advice is harming retail traders, our findings suggest that both WSB posters and users are skilled.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133343443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}