{"title":"Risk Aversion in Corporate Bond Markets","authors":"Antje Berndt, I. Dergunov, Jean Helwege","doi":"10.2139/ssrn.3939949","DOIUrl":"https://doi.org/10.2139/ssrn.3939949","url":null,"abstract":"We examine the time variation of risk aversion in corporate bond markets and its relationship with monetary policy, using data from 1973 to 2020. Our approach extracts the portion of corporate credit spreads due to changing risk aversion with a new methodology that relies on the fact that credit spreads reflect the probability of default, default betas, macroeconomic uncertainty and risk aversion. We identify substantial temporal variation in measured risk aversion, and show that risk aversion tends to be higher when monetary policy is tighter. We document that contrary to popular belief, the prolonged post-GFC period of ultra-low interest rates did not result in excessive \"Reaching for Yield\" behavior.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131068996","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 Smoothing and Loan Fund Flows: Can Investors See Through to Fair Value?","authors":"M. Emin, C. James","doi":"10.2139/ssrn.3931100","DOIUrl":"https://doi.org/10.2139/ssrn.3931100","url":null,"abstract":"Over the past decade loan mutual funds have emerged as major investors in syndicated loans. Unlike other investors in syndicated loans, mutual funds are required to mark their loans to market daily when calculating the funds’ net asset value (NAV). Marking to market is challenging because loans are not traded on a centralized exchange and unlike corporate bonds trades, loan trades lack post trade transparency. Thus, determining the fair value of loans involves potentially greater discretion on the part of fund managers. In this paper we examine whether loan mutual fund managers use their discretion to smooth their reported returns and whether misreported returns affect the relationship between fund flows and performance. Overall, we find that evidence of widespread return smoothing by loan funds managers. We find that institutional investors are less likely to chase the returns of loan funds that engage in aggressive pricing of their holdings.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127283270","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":"Intangible assets and the cross-section of stock returns","authors":"Dion Bongaerts, Xiaowei Kang, Mathijs A. Van Dijk","doi":"10.2139/ssrn.3927990","DOIUrl":"https://doi.org/10.2139/ssrn.3927990","url":null,"abstract":"We examine whether intangible assets are priced in the cross-section of stock returns. We find that intangible asset intensity has more explanatory power than size, value, profitability, and investment. An intangibles-based long-short factor has a higher Sharpe ratio than these established factors. Adding the intangible factor to the Fama-French five-factor model improves the description of average returns and makes the investment factor redundant. The intangible factor is distinct from traditional growth strategies, provides a hedge to value and quality strategies, and expands investors’ opportunity sets. Intangible intensity as characteristic is more important than as risk factor, consistent with intangibles-based mispricing.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122421881","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":"Equity Market Fragmentation and Capital Investment Efficiency","authors":"Wayne Landsman, Jing Pan, Stephen R. Stubben","doi":"10.2139/ssrn.3757751","DOIUrl":"https://doi.org/10.2139/ssrn.3757751","url":null,"abstract":"This study examines how equity market fragmentation affects firms’ capital investment decisions. Recent empirical research finds that market fragmentation lowers trading costs and thus improves market quality. We examine whether this increase in market quality translates into greater revelatory price efficiency, where stock prices reveal with greater precision information to managers and/or creditors about firms’ investment opportunities. Consistent with this notion, our findings reveal that the association between capital investment and investment opportunities is increasing in market fragmentation. Additional evidence suggests that (a) market fragmentation increases revelatory price efficiency at least in part by encouraging information acquisition and informed trade by equity investors and (b) the more efficient stock prices inform both managers and creditors about firms’ investment opportunities. Inferences based on difference-in-differences and instrumental variable tests are consistent with those based on our primary findings. This paper was accepted by Suraj Srinivasan, accounting. Funding: The authors are grateful to the Kenan-Flagler Business School, Cox School of Business, Smeal School of Business, and David Eccles School of Business for funding our research. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4905 .","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133691878","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":"Does the Capital Market Recognize Financial Misrepresentations? – Fundamental Value and Market Analysis","authors":"Ingolf Kloppenburg","doi":"10.2139/ssrn.3926293","DOIUrl":"https://doi.org/10.2139/ssrn.3926293","url":null,"abstract":"The efficiency of a (capital) market is a key element in economics (e.g. Marshall 2009; Mankiw 2014). This paper attempts to shed more light into the market efficiency in case of the rare event of a deliberate violation of GAAP (misrepresentation). The aim of the paper is twofold. The first aim is to determine the amount by which misrepresented firms are overvalued due to the misrepresentation. I therefore compare the actual firm value with hypothetical firm value based on the fundamental value of the firm without the misrepresentation. The latter is calculated with conventional valuation methods. The second aim is to compare the value difference with the market reaction once the misrepresentation emerges to test market efficiency. The firm value difference is then compared with the market reaction around the date when the misrepresentation gets revealed to the public e.g. with a restatement announcement. The method is thereby an OLS-regression. The analysis bases on a dataset of misrepresenting firms detected by the US Securities and Exchange Commission (AAER cases). Results indicate a substantially higher market value due to the misrepresentation depending on the method of an average value of up to 29.6% and median values ranging from 1.6% to 17.6%. Moreover, results indicate that the market reaction once the misrepresentation is revealed is independent of the value difference. The results are robust for the valuation method and market reaction horizon. My interpretation is that the results provide statistical and economical evidence of an anomaly of the market efficiency hypothesis.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133621388","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":"Dividend Announcements and Market Trends","authors":"Nagendra Marisetty, S. M","doi":"10.2139/ssrn.3891332","DOIUrl":"https://doi.org/10.2139/ssrn.3891332","url":null,"abstract":"This research primarily aims to study the impact of dividend announcements on the stock price of companies listed in the Indian stock market. Incidental to the study, it is necessary to understand whether the market trends have any role in affecting the changes in share prices due to dividend announcements. The companies listed on the stock market are diverse in terms of the industry, market capitalization, and performance. We analyze the S&P BSE 500 index stocks, which declare cash dividend every year without fail for ten years from 2008 – 17. Total 1755 sample was tested for dividend announcement and sample divided into large, medium, and small sample sizes based on the market capitalization of the stocks to test the market trend effect. Event methodology market model used to calculate the abnormal returns on the dividend announcement day. \u0000 \u0000The present research study examined the impact of dividend announcements on stocks in the Indian stock market. The results observe in twenty-four times based on market capitalization wise and market trend-wise dividend announcements. The results of the study are not the same for all dividend announcement observations. The study found positive abnormal returns on event day in most of the dividend announcement observations and it is similar to Litzenberger and Ramaswamy (1982), Asquith and Mullins Jr (1983), Grinblatt, Masulis, and Titman (1984), Chen, Nieh, Da Chen, and Tang (2009) and many previous research results studied in major developed stock markets and emerging stock markets. Full sample, large-cap, and small-cap final dividend average abnormal returns are positively significant only in bull market trend (period 2) similar to Below and Johnson (1996) and other market trends final dividend announcement abnormal returns are positive in most of the observations, but returns are not significant. Average abnormal returns are sensitive to market trends, especially abnormal small-cap returns more vulnerable to market trends.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114277338","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":"Market Efficiency - A Structural Study","authors":"Rajeev R. Bhattacharya","doi":"10.2139/ssrn.3742378","DOIUrl":"https://doi.org/10.2139/ssrn.3742378","url":null,"abstract":"I use eight different metrics as separate objective and systematic measures of the efficiency of the market for a stock. I develop a seven-equation (six- for non-Nasdaq stocks) structural model with market efficiency as a function of exogenous factors (transaction costs & constraints, short sales costs & constraints, and dispersion in investor valuations) and endogenous market activities (trading volume, short interest, number of analysts, institutional holdings, shares outstanding, and number of market makers (for Nasdaq stocks)), and each endogenous market activity as a function of the exogenous factors and all other endogenous market activities. I propose a theoretical model that shows that higher trading volume (or another similar market activity) is caused by lower transaction costs, lower short sales costs, and/or higher dispersion of investor valuations, and therefore, that the impact on market efficiency of transaction costs or short sales costs is an empirical question. I apply Three Stage Least Squares and Errors in Variables to estimate the structural system and test the corresponding hypotheses, using panel-based instrumentation strategies for endogenous and inaccurately measured variables. Analyzing Nasdaq and non-Nasdaq stocks separately, I find that transaction costs & constraints have a significant positive (negative) impact on market efficiency for Nasdaq (non-Nasdaq) stocks, whereas short sales costs & constraints and dispersion in investor valuations have ambiguous impacts on market efficiency, that Fama-French Factors are substantially important in affecting these relationships in sign and significance, and that market efficiency is not directly positively associated with trading volume, short interest, number of analysts, institutional holdings, and number of market makers (for Nasdaq stocks), but is directly positively associated with shares outstanding.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130652534","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":"Future Hedging Costs: Back to Basics","authors":"Christophe Patry, J. Mozley","doi":"10.2139/ssrn.3924377","DOIUrl":"https://doi.org/10.2139/ssrn.3924377","url":null,"abstract":"The Black-Scholes model is based on replication theory which makes several unrealistic assumptions, notably that one can hedge continuously and trade without transaction costs. This paper presents a framework incorporating future hedging costs in the valuation process. It determines the trade-off between hedging costs and hedging errors due to discrete hedging for a carefully chosen utility function. It provides some equations to solve for the expectation of the hedging costs and the standard deviation of the hedging errors. The chosen utility function is based on these two quantities, allowing us to determine the optimal risk management strategy without resorting to numerical techniques. This approach could be used by regulators to define quantities relevant to the calculation of future hedging costs in the context of Prudent Value. This approach could also be used as a basis for Fair Value reserves and the pricing of the exotic deals.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133754731","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":"What Are Benefits of Attracting Gambling Investors? Evidence from Stock Splits in China","authors":"Conghui Hu, Ji-Chai Lin, Yu-Jane Liu","doi":"10.2139/ssrn.3922178","DOIUrl":"https://doi.org/10.2139/ssrn.3922178","url":null,"abstract":"Analyzing a sample of Chinese firms splitting their stocks via stock dividends and using proprietary trading data to measure investors’ gambling preference, we find that stock splits raise the stocks’ lottery characteristics, making them attractive to gambling investors, who willingly pay higher prices for skewed securities. Split firms also become more risk-taking. Furthermore, their cost of equity declines, largely due to increased gambling investors’ pricing influence. Our findings suggest that firms with weak lottery characteristics and those with inefficient risk sharing, can use stock splits to attract gambling investors to improve risk sharing and to lower their cost of equity.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"239 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116066226","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":"Language and Domain Specificity: A Chinese Financial Sentiment Dictionary","authors":"Zijia Du, A. Huang, Russ Wermers, Wenfeng Wu","doi":"10.2139/ssrn.3759258","DOIUrl":"https://doi.org/10.2139/ssrn.3759258","url":null,"abstract":"We use supervised machine learning to develop a financial sentiment dictionary from 3.1 million Chinese-language financial news articles. Our dictionary maps semantically similar words to a subset of human-expert generated financial sentiment words. In validation tests, our dictionary scores the sentiment of articles consistently with human reading of full articles. In return association tests, our dictionary outperforms and subsumes previous Chinese financial sentiment dictionaries, such as direct translations of Loughran and McDonald’s (2011) English-language financial dictionary. We also generate a list of politically-related positive words that is unique to China; we find that this list has a weaker association with returns than does the list of other positive words. We demonstrate that state media uses more politically-related positive and fewer negative words, and exhibits a sentiment bias. This bias renders the state media’s sentiment as less return-informative. Our findings demonstrate that dictionary-based sentiment analysis exhibits strong language and domain specificity.","PeriodicalId":260048,"journal":{"name":"Capital Markets: Market Efficiency eJournal","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127897133","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}