New York University Stern School of Business Research Paper Series最新文献

Market Efficiency in the Age of Machine Learning

New York University Stern School of Business Research Paper Series Pub Date : 2021-03-24 DOI: 10.2139/ssrn.3783221

Leonidas G. Barbopoulos, Rui Dai, Tālis J. Putniņš, A. Saunders

引用次数: 0

Why Did Bank Stocks Crash during COVID-19? 为什么银行股在COVID-19期间崩盘?

New York University Stern School of Business Research Paper Series Pub Date : 2021-03-01 DOI: 10.2139/ssrn.3799590

V. Acharya, R. Engle, Sascha Steffen

引用次数: 42

A COVID Diary: Searching for Investment Serenity COVID日记:寻找投资宁静

New York University Stern School of Business Research Paper Series Pub Date : 2021-02-26 DOI: 10.2139/SSRN.3799691

A. Damodaran

引用次数: 1

Value Investing: Requiem, Rebirth or Reincarnation? 价值投资:安魂曲、重生还是轮回?

New York University Stern School of Business Research Paper Series Pub Date : 2021-02-04 DOI: 10.2139/ssrn.3779481

Bradford Cornell, A. Damodaran

{"title":"Value Investing: Requiem, Rebirth or Reincarnation?","authors":"Bradford Cornell, A. Damodaran","doi":"10.2139/ssrn.3779481","DOIUrl":"https://doi.org/10.2139/ssrn.3779481","url":null,"abstract":"For much of the last century, value investors considered themselves to be the winners in the investment world, a result they attributed to their patience, maturity and good sense. That view, at least on the surface, was backed up by evidence that “value” stocks, defined as stocks that trade at low multiples of earnings and book value, earned higher returns than “growth” stocks, defined loosely as companies that trade at high multiples of earnings or book value. It was reinforced by the mythology of great value investors, with Warren Buffett and Charlie Munger taking center stage, as deep thinkers, with profound insights on how markets work. In the last two decades, value investing lost its edge, and a debate has revolved around whether this is a temporary phase, and the result of an unusual macro environment, or a reflection of a permanent change in economies and markets. In this paper, we argue that value investing, at least as practiced today, has become rigid and ritualistic, and that while some of its failures can be attributed to external factors, many can be traced back to practices and rules of thumb that have outlived their usefulness. We argue that if value investing is to be successful in the future, it needs to develop a more dynamic view of value and a greater willingness to live with and invest in the face of uncertainty.","PeriodicalId":124312,"journal":{"name":"New York University Stern School of Business Research Paper Series","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129117992","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}

引用次数: 2

Understanding Credit Risk for Chinese Companies using Machine Learning: A Default-Based Approach 利用机器学习了解中国企业的信用风险:基于违约的方法

New York University Stern School of Business Research Paper Series Pub Date : 2020-11-23 DOI: 10.2139/ssrn.3734053

E. Altman, Xiaolu Hu, Jing Yu

{"title":"Understanding Credit Risk for Chinese Companies using Machine Learning: A Default-Based Approach","authors":"E. Altman, Xiaolu Hu, Jing Yu","doi":"10.2139/ssrn.3734053","DOIUrl":"https://doi.org/10.2139/ssrn.3734053","url":null,"abstract":"In response to the recent elevated corporate credit risk environment in China’s credit market, we develop a probability of default (PD) measure for Chinese companies using actual corporate bond defaults by applying the Least Absolute Shrinkage and Selection Operator (LASSO) machine learning model. Our PD measure is applicable to publicly listed and also, importantly, to unlisted companies. Our measure’s bond default prediction accuracy outperforms models generated by alternative machine learning techniques and other prominent credit risk measures. Further analysis documents a large pricing effect of corporate default risk using our PD measure in primary and secondary bond markets. The pricing effect of default risk became more pronounced following two crucial market events in 2014 that raised market awareness of credit risk and is stronger for bonds likely traded by retail and foreign investors. In the cross section of bond and stock returns, we observe a positive distress risk premium after controlling for common risk factors. Finally, stocks of low PD firms outperformed those of high PD firms during the COVID-19 pandemic.","PeriodicalId":124312,"journal":{"name":"New York University Stern School of Business Research Paper Series","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124465017","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}

引用次数: 1

Divided We Fall 分裂就会失败

New York University Stern School of Business Research Paper Series Pub Date : 2020-11-19 DOI: 10.2139/ssrn.3733317

J. Livnat, Amir Rubin, D. Segal

引用次数: 1

Passive and Active Attention to Baseball Telecasts: Implications for Content (Re-)Design 对棒球电视转播的被动与主动关注:对内容(再)设计的启示

New York University Stern School of Business Research Paper Series Pub Date : 2020-10-23 DOI: 10.2139/ssrn.3717894

Xiao Liu, M. Shum, Kosuke Uetake

引用次数: 4

Do Suspense and Surprise Drive Entertainment Demand? Evidence from Twitch.tv 悬念和惊喜驱动娱乐需求吗?证据来自Twitch.tv

New York University Stern School of Business Research Paper Series Pub Date : 2020-10-19 DOI: 10.2139/ssrn.3711801

Andrey Simonov, Raluca M. Ursu, Carolina Zheng

{"title":"Do Suspense and Surprise Drive Entertainment Demand? Evidence from Twitch.tv","authors":"Andrey Simonov, Raluca M. Ursu, Carolina Zheng","doi":"10.2139/ssrn.3711801","DOIUrl":"https://doi.org/10.2139/ssrn.3711801","url":null,"abstract":"We measure the relative importance of suspense and surprise in the entertainment preference of viewers of Twitch.tv, the largest online video game streaming platform. Using detailed viewership and game statistics data from broadcasts of tournaments of a popular video game, Counter Strike: Global Offensive, we compute measures of suspense and surprise for a rational Bayesian viewer. We then develop and estimate a stylized utility model that underlies viewers' decisions to both join and to leave a game stream, allowing for a differential effect of suspense and surprise on these decisions. The estimates reveal that suspense enters the consumer utility but provide little evidence of the effect of surprise. The magnitudes imply that a one standard deviation increase in round-level suspense decreases the probability of leaving a stream by 0.2 percentage points. Consistent with the observation that only current viewers of a game observe the amount of suspense and surprise revealed in the game, we find no detectable effect of suspense and surprise on the decision to join a game. In a simulation exercise, we show that a change in game's realized suspense explains 8.1% of the observed range of the evolution of streams' viewership levels. Our results provide a general tool for content producers and platforms to use when designing and evaluating media products.","PeriodicalId":124312,"journal":{"name":"New York University Stern School of Business Research Paper Series","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128360612","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}

引用次数: 5

Are Critical Audit Matters Informative? 关键审计事项是否具有信息性?

New York University Stern School of Business Research Paper Series Pub Date : 2020-09-02 DOI: 10.2139/ssrn.3685369

Julia Klevak, J. Livnat, D. Pei, Kate Suslava

{"title":"Are Critical Audit Matters Informative?","authors":"Julia Klevak, J. Livnat, D. Pei, Kate Suslava","doi":"10.2139/ssrn.3685369","DOIUrl":"https://doi.org/10.2139/ssrn.3685369","url":null,"abstract":"Breaking from a long stretch of using largely standard language in unqualified audit opinions, the Public Company Accounting Oversight Board (PCAOB) expanded audit reports to disclose Critical Audit Matters (CAMs) and the audit procedures used to address them. The first wave of CAM disclosures began for large accelerated filers after June 2019, with most disclosures occurring in February 2020. Using Natural Language Processing (NLP) techniques, this study examines the types of CAMs disclosed by auditors and the typical audit procedures used to address them. We then explore whether CAMs are informative to investors and security analysts. Our findings are consistent with greater amounts of CAM disclosures as indicators of greater uncertainty. We document that market reactions are more negative for firms with more CAM disclosures; analysts reduce their earnings forecasts to a larger extent for such firms; stock prices become more volatile; and the dispersion of analyst forecasts are greater for firms with more CAM disclosures. We further find that many issues related to CAMs are raised in earnings conference calls with analysts during the immediately subsequent quarter. While these findings indicate that CAMs are informative to investors and analysts, their effects are concentrated around the time of disclosure. We do not find evidence of a drift in returns after the initial disclosures.","PeriodicalId":124312,"journal":{"name":"New York University Stern School of Business Research Paper Series","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114332668","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}

引用次数: 9

Measuring and Hedging Geopolitical Risk 衡量和对冲地缘政治风险

New York University Stern School of Business Research Paper Series Pub Date : 2020-09-01 DOI: 10.2139/ssrn.3685213

R. Engle, Susana Campos-Martins

引用次数: 13