{"title":"Cognitive Errors As Canary Traps","authors":"Alex Chinco","doi":"10.2139/ssrn.3705387","DOIUrl":"https://doi.org/10.2139/ssrn.3705387","url":null,"abstract":"When otherwise intelligent investors fail to correct an error, a researcher learns something about what these investors did not know. The investors must not have known about anything which would have allowed them to spot their mistake. If they had, they would have stopped making it. I show how a researcher can use this insight to identify how investors price assets. If X predicts returns, then any correlated predictor that investors know about but researchers have yet to discover represents a potential confound. I define a special kind of error, called a “cognitive error”, which otherwise intelligent investors will only fail to correct if they are not aware of any such omitted variables. So when investors fail to correct a priced cognitive error about X, then a researcher can be sure that investors are pricing assets based on X. Cognitive errors are instruments for identifying how mostly rational investors price assets.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128448994","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":"High-frequency tweeting and market making after hours","authors":"Stefan Scharnowski","doi":"10.2139/ssrn.3863943","DOIUrl":"https://doi.org/10.2139/ssrn.3863943","url":null,"abstract":"This paper analyzes differences between the regular and extended trading sessions in the high-frequency reaction of equity markets to potential news. Using presidential tweets as market-stirring events, I find that generally volatility increases and liquidity deteriorates within less than a second after a tweet. Compared to the regular trading session, the reduction in market quality is stronger and faster during the extended trading hours, when liquidity is lower and designated market maker participation is optional.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129307898","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":"Predicting Firm Profits: From Fama-MacBeth to Gradient Boosting","authors":"Murray Z. Frank, Keer Yang","doi":"10.2139/ssrn.3919194","DOIUrl":"https://doi.org/10.2139/ssrn.3919194","url":null,"abstract":"This paper studies the predictability of firm profits using Fama-MacBeth regressions and gradient boosting. Gradient boosting can use more relevant factors and it predicts better. Profits are more predictable at firms that are large, investment grade, low R&D, low market-to-book, low cash flow volatility. Effects on financing decisions, and cross-section of stock returns are studied. During recessions profits are less predictable - particularly non-investment grade firms. Both algorithms produce estimates like those interpreted in the literature as evidence of excessive human optimism during booms and excessive pessimism during recessions.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128508537","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":"Learning from Prospectuses","authors":"S. Abis, A. Buffa, Apoorva Javadekar, A. Lines","doi":"10.2139/ssrn.3865753","DOIUrl":"https://doi.org/10.2139/ssrn.3865753","url":null,"abstract":"We study qualitative information disclosures by mutual funds when investors learn from such disclosures in addition to past performance. We show theoretically that fund managers with specialized strategies optimally choose to disclose detailed strategy descriptions, while those with standardized strategies provide generic descriptions. Generic descriptions lead to benchmarking errors by investors who confuse factor returns and skill, resulting in higher fund flow volatility. While all managers dislike this volatility, those with above-average factor exposures also benefit from the errors on balance and thus grow larger. We find evidence for this trade-off in the data, using a comprehensive dataset of fund prospectuses: funds with more informative descriptions are larger and more specialized, exhibit lower flow-performance sensitivity, and show higher correlation between size and flow volatility. Investors in these funds make fewer benchmarking errors, and the effects are more pronounced for funds with shorter return histories.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127837346","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 Politics of Bank Opacity","authors":"Heng Yue, Liandong Zhang, Qinlin Zhong","doi":"10.2139/ssrn.3075115","DOIUrl":"https://doi.org/10.2139/ssrn.3075115","url":null,"abstract":"Abstract The distribution of power in the political system shapes the financial reporting opacity of banks. Specifically, banks located in states with senators on the Senate Banking Committee (BC senators) have greater abnormal loan loss provisions than banks in other states. The result is stronger for larger banks and banks with higher risk. In addition, BC senators have a negative effect on the likelihood of banks in their home states receiving enforcement actions, and, more importantly, this effect is stronger for more opaque banks. These findings suggest that politicians, regulators, and banks use opaque financial reporting to facilitate regulatory forbearance. Moreover, we show that opacity is a significant channel through which BC senators increase bank risk. During economic downturns, however, BC senators appear to promote bank opacity to encourage bank lending and create liquidity. Finally, the capital market does not penalize the reporting opacity of banks in states with BC senators.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122574653","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":"Return Predictability using Price-to-Earnings Ratio","authors":"Nikhil Vidhani","doi":"10.2139/ssrn.3910641","DOIUrl":"https://doi.org/10.2139/ssrn.3910641","url":null,"abstract":"In this paper, I revisit the predictive ability of the price to earnings (PE) ratio for future returns. I provide a model of expected returns by decomposing stock price into earnings and PE ratio. While the PE ratio is modeled as a mean-reverting AR(1) process, earnings follow a linear trend. Expected model returns are strongly correlated with future returns. An increase of 1% in expected returns is associated with 0.5% higher future returns. To this end, I propose an investment strategy that chooses between equity or debt investment based on predicted expected stock returns and risk-free bond returns. My strategy avoids short-selling and outperforms a buy-and-hold portfolio of stocks.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124634049","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":"Double Trouble? IRS's Attention to Financial Accounting Restatements","authors":"Zackery Fox, R. Wilson","doi":"10.2139/ssrn.3317839","DOIUrl":"https://doi.org/10.2139/ssrn.3317839","url":null,"abstract":"We examine whether the IRS uses public information to obtain qualitative signals regarding the quality of firms’ financial information or management integrity. Using the procurement of public information as a proxy for IRS attention, we test whether public signals of poor information quality (restatements) lead to an increase in IRS attention. To begin, we document that the IRS is both more likely and quicker to acquire public filings announcing a restatement than any other filing of the firm. Furthermore, we examine instances in which the IRS is more likely to learn of a restatement and find an increase in attention around both press releases and media coverage of the restatement. Next, we examine the implications of increased IRS attention. Employing path analysis, we find that IRS attention is associated with both higher levels of future tax settlements, and a greater likelihood of the mention of a tax audit. Overall, our results are consistent with the IRS responding to signals of poor information quality or management integrity as if financial misreporting and tax reporting are related.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114098883","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 Market Sentiment Analysis","authors":"Marco Bollinger","doi":"10.2139/ssrn.3909474","DOIUrl":"https://doi.org/10.2139/ssrn.3909474","url":null,"abstract":"Now, more than ever, data mining is finding its way into practical business usage. Data mining and data visualization techniques are creating pathways to solve complex issues and are empowering decision-makers in determining best business practice and strategy. Business managers and leaders can use data mining and data visualization to generate insights and create value (including financial value) in numerous ways. Two of the major applications involve textual data mining and behavioral analytics. Textual data mining involves a type of analysis in which valuable information is derived from high volumes of text-based data. Whereas, behavioral analytics allows data scientists to derive meaning from customer behavioral data and answer questions like why one product is preferred over a similar product. The analysis in this study revolves largely around sentiment analysis which is both textual and behavioral. In particular, there was great interest in determining whether any value could be derived through sentiment analysis regarding success within the stock market. Various aspects of human behavioral traits were utilized including categories like confidence level, goals/motivations, and strategy.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129471954","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":"Tesla and the Stock Market","authors":"Gretell Fernandez","doi":"10.2139/ssrn.3908812","DOIUrl":"https://doi.org/10.2139/ssrn.3908812","url":null,"abstract":"Tesla has changed the way in which the world views sustainable energy since its inception in 2003 and has become a strong force in the stock market. Tesla focuses on building all electric vehicles as well as clean energy generation storage products. The success of Tesla has been proven in the stock market with their steady increases in stock prices and interest of investors. Tesla is a prime example of sustainable energy companies beginning to surpass investor interest in the auto industry as more and more people begin to focus on the environmental impact of gas vehicles. Tesla produced massive share increases in 2020 showing that investor enthusiasm was at an all-time high. In 2021, this began to change when the company shares dropped approximately five percent. As more and more companies begin to invest in all electric vehicles and they start to offer additional electric alternatives to their gas vehicles at a much lower cost, is it possible for Tesla to maintain their momentum within the stock market? Tesla needs to remain innovative if they want to stay ahead of their competitors. In this article we discuss how an increase in all electric competitors and COVID-19 has impacted Tesla in the stock market. We review if innovation can be the only tool for success in order for Tesla to continue surpassing their competitors.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128358411","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":"Disaster Risk, Politicians, and Firm Capital Exuding: A New Role of Stock Market Participation","authors":"A. Durnev, Jiawei Wang","doi":"10.2139/ssrn.3908762","DOIUrl":"https://doi.org/10.2139/ssrn.3908762","url":null,"abstract":"We propose a new function of stock market – to align voters’ preferences to politicians’ policies. We build a model with politicians’ ability to abate negative disaster shocks. Pro-business politicians are more likely to get re-elected when voters hold firm equity, and because of less severe disaster shocks, firms exude less capital and allocate investment more efficiently. We construct a novel stock market participation data for U.S. states using IRS statistics. We find that companies in states with higher stock market participation invest more efficiently and elect pro-business politicians. We use a novel neighboring states methodology and financial literacy instrument to eliminate endogeneity concerns.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121842051","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}
京公网安备 11010802042870号
求助内容：
应助结果提醒方式：