A. Abramov, A. Radygin, M. Chernova, Andrey Kosyrev
{"title":"Risks and Concerns: Review of Financial Markets (September 1 – October 15, 2020)","authors":"A. Abramov, A. Radygin, M. Chernova, Andrey Kosyrev","doi":"10.2139/ssrn.3717923","DOIUrl":"https://doi.org/10.2139/ssrn.3717923","url":null,"abstract":"Fears mount on the global market regarding a “bubble” on the stock market transition of major institutional investors to riskier assets, growth in issuers credit risks. The domestic market demonstrates stock market stagnation against the background<br>of ruble’s depreciation.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75585114","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":"Dollar Carry Timing","authors":"Tom Lenaerts, I. Zisis","doi":"10.2139/ssrn.3712255","DOIUrl":"https://doi.org/10.2139/ssrn.3712255","url":null,"abstract":"Dollar carry trade risk premiums - unlike dollar-neutral or foreign exchange carry risk premiums - are positively correlated with firm-level dispersions in investment, profitability, and book-to-market in addition to the Treasury-bill rate, long term bond yield, term spread, and default spread. This predictability is also statistically and economically significant out of sample: It generates Sharpe ratios as large as 1.37 (compared to 0.44 unconditionally), for example. Indeed, several forecasting models pin down the few periods responsible for the entire premium. Finally, any detailed narrative (typically based on untestable claims) in which the variables above are proxies for the latent (quantity of) risk and price of risk states - and the business cycle - in the U.S. explains the results in the present paper. However, I avoid making this type of less scientific claims as much as possible and focus on the evidence, instead.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82220765","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 Asset Durability Premium","authors":"Kai Li, Chi-yang Tsou","doi":"10.2139/ssrn.3714348","DOIUrl":"https://doi.org/10.2139/ssrn.3714348","url":null,"abstract":"This paper studies how the durability of assets affects the cross-section of stock returns. More durable assets incur lowers frictionless user costs but are more \"expensive\", in the sense that they need more down payments making them hard to finance. In recessions, firms become more financially constrained and prefer \"cheaper\" less durable assets. As a result, the price of less durable assets is less procyclical and therefore less risky than that of durable assets. We provide strong empirical evidence to support this prediction. Among financially constrained stocks, firms with higher asset durability earn average returns about 5% higher than firms with lower asset durability. We develop a general equilibrium model with heterogeneous firms and collateral constraints to quantitatively account for such a positive asset durability premium.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"52 Pt 3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83913604","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":"Do Reference Prices Impact How Investors Respond to News?","authors":"B. Cannon, Hannes Mohrschladt","doi":"10.2139/ssrn.3712902","DOIUrl":"https://doi.org/10.2139/ssrn.3712902","url":null,"abstract":"We provide evidence that reference prices impact how investors respond to news. When current prices are farther from a reference price, investors react more strongly to news. We first document that individual investors are more (less) likely to sell a stock following bad (good) news when the stock's trading price is farther from the investor's purchase price. Motivated by this micro-level evidence, we construct a stock-level measure to capture the distance between a stock's trading price and its purchase price for the average investor. We provide evidence that this distance from purchase price produces a substantial amount of cross-sectional variation in the degree to which stocks over- or underreact to news. Stocks trading farthest from their purchase price react more strongly to news than stocks trading near their purchase price. Consistent with relative overreaction, stocks trading farthest from their purchase price also exhibit greater return reversals following news days. We document that a cross-sectional strategy exploiting these return patterns earns a monthly alpha of 0.93%. These findings are distinct from alternative explanations related to size, illiquidity, and volatility. Our evidence instead suggests that reference prices have a meaningful impact on how investors respond to news.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85647162","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 Conduits of Price Discovery: A Machine Learning Approach","authors":"Amy Kwan, R. Philip, Andriy Shkilko","doi":"10.2139/ssrn.3710491","DOIUrl":"https://doi.org/10.2139/ssrn.3710491","url":null,"abstract":"When examining information flow into prices, empirical literature usually focusses on direct conduits such as order submissions. Meanwhile, theory suggests that market conditions should have substantial additional effects. Empirical analyses of such effects are methodologically challenging and therefore uncommon. We bypass these challenges using a machine learning technique that allows for multiple conditioning variables. Consistent with theory, price discovery is notably affected by such conditions as the state of the limit order book, price history, bid-ask spread, and order arrival frequency. The state of the book and price history stand out as conduits, whose magnitudes rival that of order submissions.<br>","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"262 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76741843","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":"Green Sentiment in Financial Markets: A Global Warning","authors":"Marie Bessec, Julien Fouquau","doi":"10.2139/ssrn.3710489","DOIUrl":"https://doi.org/10.2139/ssrn.3710489","url":null,"abstract":"We use textual analysis to measure the growing concern about climate issues and to assess its impact on stock prices in the United States. Using a dataset of 71,785 articles published in The Wall Street Journal from 2010 to 2019, we create several scores capturing media coverage of environmental issues and investigate their influence on S&P500 constituents in a Fama-French model. We find a significant impact of green sentiment on the stock returns of nearly 25% of firms. The response varies across the different sectors. The effect is negative in energy and materials, particularly in chemicals and metals. A positive impact is found in real estate and utilities. An assessment of the results at company level shows that this impact is related to their environmental performance. The results are robust to the use of alternative lexicons and weighting schemes, various specifications and sample periods.<br>","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"69 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85494004","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":"Real Effects in the Option Market","authors":"Botong Shang","doi":"10.2139/ssrn.3710222","DOIUrl":"https://doi.org/10.2139/ssrn.3710222","url":null,"abstract":"I investigate whether and how managers extract private information from the option market to guide investment decisions. The level of private information is negatively associated with the sensitivity of both investment amount and timing to implied volatility. This finding is consistent with the real options theory, where managers extract market-expected uncertainty from the option market. Managerial learning from the option market is beneficial to firms by improving investment efficiency. Cross-sectional variation in real effects aligns with predictions based on investment irreversibility, executive incentives, and industry competition. The results are robust to alternative explanations.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86639827","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":"Towards a Better Fed Model","authors":"R. Micaletti","doi":"10.2139/ssrn.3704963","DOIUrl":"https://doi.org/10.2139/ssrn.3704963","url":null,"abstract":"We present an alternative to the widely known and much-maligned \"Fed model.\" The proposed alternative makes a coherent comparison between equities and bonds that eliminates the theoretical and empirical flaws of the original (as well as any need for ad hoc asset-class volatility adjustments). The output of the model is a time-series value factor, which is then used to develop a tactical asset allocation strategy. Historical simulations suggest the resulting strategy is superior not only to the original Fed model, but to tactical strategies based on other popular time-series value factors as well. Beyond its forecasting and tactical allocation performance, the proposed model also provides significant insight into equity market dynamics--insight that has been validated by recent historical events.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84849831","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":"Retail Investor Experience, Asset Learning, and Portfolio Risk-Adjusted Returns","authors":"Sturla Lyngnes Fjesme","doi":"10.2139/ssrn.3722721","DOIUrl":"https://doi.org/10.2139/ssrn.3722721","url":null,"abstract":"Abstract It is well documented in the finance literature that retail investors (households) underperform on a risk-adjusted basis when trading in securities markets. More recently, however, there is growing evidence that some retail investors increase risk-adjusted returns from security selection (portfolio concentration). I show that these mixed findings are driven by investor trading experience. Using unique portfolio holdings data of all the 620,970 domestic retail investors on the Oslo Stock Exchange (OSE) from 1993 to 2006, I document that inexperienced investors reduce returns from portfolio concentration. However, as investors gain trading experience their ability to turn portfolio concentration into excess returns improves.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81399676","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":"Analysts Don’t Catch Alpha but Their Behavior Bias Do!","authors":"R. Dhoyer","doi":"10.2139/ssrn.3696535","DOIUrl":"https://doi.org/10.2139/ssrn.3696535","url":null,"abstract":"This article was not written for discriminating against analysts. If their roles have often been controversial through pessimistic articles, I remain convinced that my fellow analysts have an important role to play in the markets. Although known by financial players, their contribution is often questioned: - do they have a real impact on prices? - how to create alpha thanks to their recommendations and target prices? So many questions that have drawn the attention of Quantology to provide a quantitative answer.","PeriodicalId":18611,"journal":{"name":"Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal","volume":"86 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84182646","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}