Market prices are noisy signals of economic fundamentals. In a two-period model, we show that if the central bank uses market prices as guidance for intervention, large strategic investors who benefit from high prices would depress market prices to induce a market-supportive intervention. Stronger anticipated interventions lead to deeper price depressions preintervention and sharper price reversals post-intervention. The central bank intervention harms strategic investors even though it is the investors who tried to mislead the central bank. The model predicts a V-shaped price pattern around central bank interventions, consistent with recent evidence. (JEL G14, G18)
{"title":"Strategic Trading When Central Bank Intervention Is Predictable","authors":"Liyan Yang, Haoxiang Zhu","doi":"10.1093/rapstu/raab011","DOIUrl":"https://doi.org/10.1093/rapstu/raab011","url":null,"abstract":"Market prices are noisy signals of economic fundamentals. In a two-period model, we show that if the central bank uses market prices as guidance for intervention, large strategic investors who benefit from high prices would depress market prices to induce a market-supportive intervention. Stronger anticipated interventions lead to deeper price depressions preintervention and sharper price reversals post-intervention. The central bank intervention harms strategic investors even though it is the investors who tried to mislead the central bank. The model predicts a V-shaped price pattern around central bank interventions, consistent with recent evidence. (JEL G14, G18)","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"13 2","pages":""},"PeriodicalIF":13.1,"publicationDate":"2021-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138512356","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}
Pub Date : 2021-04-10eCollection Date: 2021-12-01DOI: 10.1093/rapstu/raab010
Jussi Keppo, Tyler Shumway, Daniel Weagley
We document significant persistence in the market timing performance of active individual investors, suggesting that some investors are skilled at timing. Using data on all trades by active Finnish individual investors over almost 15 years, we also show that the net purchases of skilled versus unskilled investors predict monthly market returns. Our results lend credibility to the view that market returns are predictable, without having to specify which variables active investors use to successfully time the market. (JEL G10, G11, G12, G14, G15).
{"title":"Are Monthly Market Returns Predictable?","authors":"Jussi Keppo, Tyler Shumway, Daniel Weagley","doi":"10.1093/rapstu/raab010","DOIUrl":"https://doi.org/10.1093/rapstu/raab010","url":null,"abstract":"<p><p>We document significant persistence in the market timing performance of active individual investors, suggesting that some investors are skilled at timing. Using data on all trades by active Finnish individual investors over almost 15 years, we also show that the net purchases of skilled versus unskilled investors predict monthly market returns. Our results lend credibility to the view that market returns are predictable, without having to specify which variables active investors use to successfully time the market. (<i>JEL</i> G10, G11, G12, G14, G15).</p>","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"11 4","pages":"806-836"},"PeriodicalIF":13.1,"publicationDate":"2021-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1093/rapstu/raab010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39903475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper considers the puzzle of increased trading volume around information releases through the lens of canonical models of disagreement. I use a unique data set of clicks on news by key finance professionals to simultaneously measure gradual information diffusion and differences of opinion. I find that neither channel subsumes the other and that the two are complementary in generating trading volume around news events. Their relative strengths depend on the characteristics of the underlying information: gradual information diffusion matters more for straightforward news, while differences of opinion play a larger role around textually ambiguous news. (JEL G12, G14, G41, D84) Received January 12, 2020; editorial decision: November 24, 2020 by Editor: Jeffrey Pontiff. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
{"title":"Disagreement after News: Gradual Information Diffusion or Differences of Opinion?","authors":"Anastassia Fedyk","doi":"10.1093/rapstu/raab008","DOIUrl":"https://doi.org/10.1093/rapstu/raab008","url":null,"abstract":"This paper considers the puzzle of increased trading volume around information releases through the lens of canonical models of disagreement. I use a unique data set of clicks on news by key finance professionals to simultaneously measure gradual information diffusion and differences of opinion. I find that neither channel subsumes the other and that the two are complementary in generating trading volume around news events. Their relative strengths depend on the characteristics of the underlying information: gradual information diffusion matters more for straightforward news, while differences of opinion play a larger role around textually ambiguous news. (JEL G12, G14, G41, D84) Received January 12, 2020; editorial decision: November 24, 2020 by Editor: Jeffrey Pontiff. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"9 2","pages":""},"PeriodicalIF":13.1,"publicationDate":"2021-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138512329","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}
This paper proposes that computational complexity generates noise. The same asset is often held for completely different reasons by many funds following a wide variety of threshold-based trading rules. Under these conditions, we show it can be computationally infeasible to predict how these various trading rules will interact with one another, turning the net demand from these funds into unpredictable noise. This noise-generating mechanism can operate in a wide range of markets and also predicts how noise volatility will vary across assets. We confirm this prediction empirically using data on exchange-traded funds. (JEL G00, G02, G14). Received May 28 2019; editorial decision December 16 2020 by Editor Thierry Foucault. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
{"title":"The Sound of Many Funds Rebalancing","authors":"Alex Chinco, Vyacheslav Fos","doi":"10.1093/rapstu/raab009","DOIUrl":"https://doi.org/10.1093/rapstu/raab009","url":null,"abstract":"This paper proposes that computational complexity generates noise. The same asset is often held for completely different reasons by many funds following a wide variety of threshold-based trading rules. Under these conditions, we show it can be computationally infeasible to predict how these various trading rules will interact with one another, turning the net demand from these funds into unpredictable noise. This noise-generating mechanism can operate in a wide range of markets and also predicts how noise volatility will vary across assets. We confirm this prediction empirically using data on exchange-traded funds. (JEL G00, G02, G14). Received May 28 2019; editorial decision December 16 2020 by Editor Thierry Foucault. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"2 2","pages":""},"PeriodicalIF":13.1,"publicationDate":"2021-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138512346","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}
Kalok Chan, A. Ellul, Itay Goldstein, C. Holden, Monika Piazzesi, Jeffrey Pontiff
{"title":"The Annual Report of the Society for Financial Studies for 2019–2020","authors":"Kalok Chan, A. Ellul, Itay Goldstein, C. Holden, Monika Piazzesi, Jeffrey Pontiff","doi":"10.1093/RCFS/CFAB001","DOIUrl":"https://doi.org/10.1093/RCFS/CFAB001","url":null,"abstract":"","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"15 1","pages":""},"PeriodicalIF":13.1,"publicationDate":"2021-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80145221","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}
Portfolio performance measures using holdings data are panel regressions. The returns of a fund’s stocks are regressed on its lagged portfolio weights. Stock fixed effects isolate average performance from time-series predictive ability. Control variables condition for fund performance on the characteristics of the stocks held. The long-term performance of average holdings drives some of the classical measures, while predictive ability drives others. A “buy-and-hold drift,” where portfolio weights increase over time in the higher alpha stocks, affects performance measures. Investor flows respond to average performance net of the buy-and-hold drift. (JEL G11, G14, G23, G29).
{"title":"A Panel Regression Approach to Holdings-Based Fund Performance Measures","authors":"Wayne Ferson, Junbo L Wang","doi":"10.1093/rapstu/raab007","DOIUrl":"https://doi.org/10.1093/rapstu/raab007","url":null,"abstract":"Portfolio performance measures using holdings data are panel regressions. The returns of a fund’s stocks are regressed on its lagged portfolio weights. Stock fixed effects isolate average performance from time-series predictive ability. Control variables condition for fund performance on the characteristics of the stocks held. The long-term performance of average holdings drives some of the classical measures, while predictive ability drives others. A “buy-and-hold drift,” where portfolio weights increase over time in the higher alpha stocks, affects performance measures. Investor flows respond to average performance net of the buy-and-hold drift. (JEL G11, G14, G23, G29).","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"13 4","pages":""},"PeriodicalIF":13.1,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138512353","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}
We analyze fund managers’ reputation concerns in an equilibrium model, in which we tie together a number of seemingly unrelated phenomena. The model shows that because of reputation concerns, hedge fund managers, especially those with an average reputation, prefer strategies with negatively skewed return distributions. One subtle consequence of this preference is that capital sometimes appears slow moving, leaving profitable investment opportunities unexploited, yet other times appears fast moving, causing large capital relocation and price fluctuations in the absence of fundamental news. More broadly, the analysis demonstrates a limitation of market discipline: fund managers may distort their investments precisely because of market discipline.
{"title":"Reputation Concerns and Slow-Moving Capital","authors":"Steven Malliaris, Hongjun Yan","doi":"10.1093/rapstu/raab006","DOIUrl":"https://doi.org/10.1093/rapstu/raab006","url":null,"abstract":"We analyze fund managers’ reputation concerns in an equilibrium model, in which we tie together a number of seemingly unrelated phenomena. The model shows that because of reputation concerns, hedge fund managers, especially those with an average reputation, prefer strategies with negatively skewed return distributions. One subtle consequence of this preference is that capital sometimes appears slow moving, leaving profitable investment opportunities unexploited, yet other times appears fast moving, causing large capital relocation and price fluctuations in the absence of fundamental news. More broadly, the analysis demonstrates a limitation of market discipline: fund managers may distort their investments precisely because of market discipline.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"1 1","pages":""},"PeriodicalIF":13.1,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138512349","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}
We show that endogenous information signaling in the CDS market, together with sluggish updates on corporate credit ratings assigned by major rating agencies, creates anomalies such as return momentum within the CDS market and across CDS-to-stock return momentum. Using 5-year credit default swap (CDS) contracts on 1,247 U.S. firms from 2003 to 2011, a three-month formation and one-month holding period CDS momentum strategy yields 52 bps per month with a Sharpe ratio of 0.423. The performance is better for entities with lower credit ratings (83 bps per month), high CDS depth (80 bps per month), and during the financial crisis (97 bps per month). Furthermore, our cross-market tests show that by incorporating past CDS returns into the stock momentum portfolio formation process, traditional stock momentum strategies avoid abrupt losses during the crisis period and improve their performance by a net of 104 bps per month. This joint-market momentum strategy is particularly profitable for entities with high CDS depth. Importantly, we show that both within the CDS market and CDS-to-stock joint-market, momentum profits exist because CDS returns correctly anticipate future credit rating changes. This mechanism completely differentiates CDS momentum from bond return momentum.
{"title":"CDS Momentum: Slow-Moving Credit Ratings and Cross-Market Spillovers","authors":"Jongsub Lee, A. Naranjo, Stace Sirmans","doi":"10.1093/RAPSTU/RAAA025","DOIUrl":"https://doi.org/10.1093/RAPSTU/RAAA025","url":null,"abstract":"We show that endogenous information signaling in the CDS market, together with sluggish updates on corporate credit ratings assigned by major rating agencies, creates anomalies such as return momentum within the CDS market and across CDS-to-stock return momentum. Using 5-year credit default swap (CDS) contracts on 1,247 U.S. firms from 2003 to 2011, a three-month formation and one-month holding period CDS momentum strategy yields 52 bps per month with a Sharpe ratio of 0.423. The performance is better for entities with lower credit ratings (83 bps per month), high CDS depth (80 bps per month), and during the financial crisis (97 bps per month). Furthermore, our cross-market tests show that by incorporating past CDS returns into the stock momentum portfolio formation process, traditional stock momentum strategies avoid abrupt losses during the crisis period and improve their performance by a net of 104 bps per month. This joint-market momentum strategy is particularly profitable for entities with high CDS depth. Importantly, we show that both within the CDS market and CDS-to-stock joint-market, momentum profits exist because CDS returns correctly anticipate future credit rating changes. This mechanism completely differentiates CDS momentum from bond return momentum.","PeriodicalId":21144,"journal":{"name":"Review of Asset Pricing Studies","volume":"5 1","pages":""},"PeriodicalIF":13.1,"publicationDate":"2021-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80161767","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}
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