Pub Date : 2025-02-24DOI: 10.1016/j.jempfin.2025.101599
Renbin Zhang , Tongbin Zhang
A large proportion of Chinese companies are dual-listed in both the mainland (A-share) and Hong Kong (H-share) markets. A-shares usually sell at a premium, known as the AH premium, which is large and volatile. The AH premium resembles a globally well-known premium puzzle in “Siamese twin” stocks. We find that a model of subjective stock price expectations, where agents forecast the future capital gains by extrapolating from the past provides a good explanation. This finding emphasizes the importance of modeling investors with extrapolative stock price expectations.
{"title":"The AH premium: A tale of “siamese twin” stocks","authors":"Renbin Zhang , Tongbin Zhang","doi":"10.1016/j.jempfin.2025.101599","DOIUrl":"10.1016/j.jempfin.2025.101599","url":null,"abstract":"<div><div>A large proportion of Chinese companies are dual-listed in both the mainland (A-share) and Hong Kong (H-share) markets. A-shares usually sell at a premium, known as the AH premium, which is large and volatile. The AH premium resembles a globally well-known premium puzzle in “Siamese twin” stocks. We find that a model of subjective stock price expectations, where agents forecast the future capital gains by extrapolating from the past provides a good explanation. This finding emphasizes the importance of modeling investors with extrapolative stock price expectations.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"81 ","pages":"Article 101599"},"PeriodicalIF":2.1,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-13DOI: 10.1016/j.jempfin.2025.101596
Trond Døskeland, André Wattø Sjuve, Andreas Ørpetveit
Following the framework established by Berk and Green (2004), mutual fund inflows and fees should be uncorrelated at equilibrium. We empirically explore this relationship by investigating the temporal changes in fund fees and flows. Our fee metrics focus on active management services rather than diversification. We analyze the additional fee compared to passive alternatives and additional fee per unit of active management, along with the traditionally used total fee. Our analysis of global data reveals a negative time series correlation between both measures of active management fee and fund flows.
{"title":"Do fees matter? Investor’s sensitivity to active management fees","authors":"Trond Døskeland, André Wattø Sjuve, Andreas Ørpetveit","doi":"10.1016/j.jempfin.2025.101596","DOIUrl":"10.1016/j.jempfin.2025.101596","url":null,"abstract":"<div><div>Following the framework established by Berk and Green (2004), mutual fund inflows and fees should be uncorrelated at equilibrium. We empirically explore this relationship by investigating the temporal changes in fund fees and flows. Our fee metrics focus on active management services rather than diversification. We analyze the additional fee compared to passive alternatives and additional fee per unit of active management, along with the traditionally used total fee. Our analysis of global data reveals a negative time series correlation between both measures of active management fee and fund flows.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"81 ","pages":"Article 101596"},"PeriodicalIF":2.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-07DOI: 10.1016/j.jempfin.2025.101579
Aleksandra Rzeźnik
I examine the active liquidity management of U.S. equity mutual funds facing unexpected, persistent investor withdrawals by exploiting two independent shocks: the 2003 mutual fund scandal and the 2016 introduction of Morningstar Sustainability Ratings. I document that fund managers increase portfolio liquidity by adjusting both equity and cash holdings when subject to sudden, moderate, and prolonged outflows. Among affected funds, those that more aggressively increase portfolio liquidity significantly outperform their less liquidity-focused peers, suggesting that skilled managers employ active liquidity management to minimize costs imposed by redemption obligations.
{"title":"Skilled active liquidity management: Evidence from shocks to fund flows","authors":"Aleksandra Rzeźnik","doi":"10.1016/j.jempfin.2025.101579","DOIUrl":"10.1016/j.jempfin.2025.101579","url":null,"abstract":"<div><div>I examine the active liquidity management of U.S. equity mutual funds facing unexpected, persistent investor withdrawals by exploiting two independent shocks: the 2003 mutual fund scandal and the 2016 introduction of Morningstar Sustainability Ratings. I document that fund managers increase portfolio liquidity by adjusting both equity and cash holdings when subject to sudden, moderate, and prolonged outflows. Among affected funds, those that more aggressively increase portfolio liquidity significantly outperform their less liquidity-focused peers, suggesting that skilled managers employ active liquidity management to minimize costs imposed by redemption obligations.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"81 ","pages":"Article 101579"},"PeriodicalIF":2.1,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143386462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-07DOI: 10.1016/j.jempfin.2025.101593
Fernanda Fuentes , Rodrigo Herrera , Adam Clements
This paper proposes a new class of marked point process models to capture the clustering behavior in extreme financial events. The idea of multiple dynamic parameters embedded in the context of score driven models is utilized to estimate a dynamic extreme value approach, labeled as the Orthogonal Score-Driven Peaks Over Threshold model. A Monte-Carlo study is conducted to study different time-varying parameter specifications. The results show that this approach can capture a range of different dynamics for the parameters. In an empirical application, we study the dynamics of the tail distribution over time, and in particular on VaR and ES forecasts, for the constituents of the S&P Banks Index. Finally, we study the behavior of extremely adverse returns in the financial system by means of a decomposition of the tail- risk measure, giving a deeper understanding of both the dynamics of the risk of an individual bank, and the systemic linkages associated with the stability of the global financial system.
{"title":"Tail risk dynamics of banks with score-driven extreme value models","authors":"Fernanda Fuentes , Rodrigo Herrera , Adam Clements","doi":"10.1016/j.jempfin.2025.101593","DOIUrl":"10.1016/j.jempfin.2025.101593","url":null,"abstract":"<div><div>This paper proposes a new class of marked point process models to capture the clustering behavior in extreme financial events. The idea of multiple dynamic parameters embedded in the context of score driven models is utilized to estimate a dynamic extreme value approach, labeled as the Orthogonal Score-Driven Peaks Over Threshold model. A Monte-Carlo study is conducted to study different time-varying parameter specifications. The results show that this approach can capture a range of different dynamics for the parameters. In an empirical application, we study the dynamics of the tail distribution over time, and in particular on VaR and ES forecasts, for the constituents of the S&P Banks Index. Finally, we study the behavior of extremely adverse returns in the financial system by means of a decomposition of the tail-<span><math><mi>β</mi></math></span> risk measure, giving a deeper understanding of both the dynamics of the risk of an individual bank, and the systemic linkages associated with the stability of the global financial system.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"81 ","pages":"Article 101593"},"PeriodicalIF":2.1,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-06DOI: 10.1016/j.jempfin.2025.101594
Rodrigo Hizmeri , Marwan Izzeldin , Giovanni Urga
In this paper, we examine the finite sample properties of test statistics designed to identify distinct underlying components of high-frequency financial data, specifically the Brownian component and infinite vs. finite activity jumps. We conduct a comprehensive set of Monte Carlo simulations to evaluate the tests under various types of microstructure noise, price staleness, and different levels of jump activity. We apply these tests to a dataset comprising 100 individual S&P 500 constituents from diverse business sectors and the SPY (S&P 500 ETF) to empirically assess the relative magnitude of these components. Our findings strongly support the presence of both Brownian and jump components. Furthermore, we investigate the time-varying nature of rejection rates and we find that periods with more jumps days are usually associated with an increase in infinite jumps and a decrease in finite jumps. This suggests a dynamic interplay between jump components over time.
{"title":"Identifying the underlying components of high-frequency data: Pure vs jump diffusion processes","authors":"Rodrigo Hizmeri , Marwan Izzeldin , Giovanni Urga","doi":"10.1016/j.jempfin.2025.101594","DOIUrl":"10.1016/j.jempfin.2025.101594","url":null,"abstract":"<div><div>In this paper, we examine the finite sample properties of test statistics designed to identify distinct underlying components of high-frequency financial data, specifically the Brownian component and infinite vs. finite activity jumps. We conduct a comprehensive set of Monte Carlo simulations to evaluate the tests under various types of microstructure noise, price staleness, and different levels of jump activity. We apply these tests to a dataset comprising 100 individual S&P 500 constituents from diverse business sectors and the SPY (S&P 500 ETF) to empirically assess the relative magnitude of these components. Our findings strongly support the presence of both Brownian and jump components. Furthermore, we investigate the time-varying nature of rejection rates and we find that periods with more jumps days are usually associated with an increase in infinite jumps and a decrease in finite jumps. This suggests a dynamic interplay between jump components over time.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"81 ","pages":"Article 101594"},"PeriodicalIF":2.1,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143349424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We assess the differential impacts of “Big Bang” and “Small Bang” contracts and convention changes on market participants across CDS markets and couple comprehensive bank-firm-level CDS trading data from the DTCC to the German credit register containing bi-lateral bank-firm credit exposures. We find that after the Bangs, the cost of buying CDS contracts becomes lower for non-dealer banks and that, because of this decrease in insurance costs, these banks extend relatively more credit to CDS-traded and affected firms compared to dealers, and hedge more effectively. Hence, standardization lowers the cost of credit insurance and leads to a relative increase in credit extensions by non-dealer banks.
{"title":"CDS and credit: The effect of the bangs on credit insurance, lending and hedging","authors":"Yalin Gündüz , Steven Ongena , Günseli Tümer-Alkan , Yuejuan Yu","doi":"10.1016/j.jempfin.2025.101583","DOIUrl":"10.1016/j.jempfin.2025.101583","url":null,"abstract":"<div><div>We assess the differential impacts of “Big Bang” and “Small Bang” contracts and convention changes on market participants across CDS markets and couple comprehensive bank-firm-level CDS trading data from the DTCC to the German credit register containing bi-lateral bank-firm credit exposures. We find that after the Bangs, the cost of buying CDS contracts becomes lower for non-dealer banks and that, because of this decrease in insurance costs, these banks extend relatively more credit to CDS-traded and affected firms compared to dealers, and hedge more effectively. Hence, standardization lowers the cost of credit insurance and leads to a relative increase in credit extensions by non-dealer banks.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"81 ","pages":"Article 101583"},"PeriodicalIF":2.1,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143231743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.jempfin.2025.101595
Jiawen Luo , Oguzhan Cepni , Riza Demirer , Rangan Gupta
We propose a procedure to forecast the realized covariance matrix for a given set of assets within a multivariate heterogeneous autoregressive (MHAR) framework. Utilizing high-frequency data for the U.S. aggregate and industry indexes and a large set of exogenous predictors that include financial, macroeconomic, sentiment, and climate-based factors, we evaluate the out-of-sample performance of industry portfolios constructed from forecasted realized covariance matrices across various univariate and multivariate forecasting models. Our findings show that LASSO-based multivariate HAR models employing predictors that capture climate uncertainty generally yield more consistent evidence regarding the accuracy of the realized covariance forecasts, providing further support for the growing evidence that climate related factors significantly drive return and volatility dynamics in financial markets. While international summits and global warming stand out as the dominant climate predictors for realized volatility forecasts, both climate and macroeconomic predictors prove equally important for longer term correlation forecasts. In these forecasts, the U.S. EPU index and natural disasters, along with U.S. climate policy uncertainty, play dominant predictive roles. Our results suggest that the MHAR framework, coupled with DRD decomposition that splits the covariance matrix into a diagonal matrix of realized variances and realized correlations, can be utilized in a high-frequency setting to implement diversification and smart beta strategies for various investment horizons.
{"title":"Forecasting multivariate volatilities with exogenous predictors: An application to industry diversification strategies","authors":"Jiawen Luo , Oguzhan Cepni , Riza Demirer , Rangan Gupta","doi":"10.1016/j.jempfin.2025.101595","DOIUrl":"10.1016/j.jempfin.2025.101595","url":null,"abstract":"<div><div>We propose a procedure to forecast the realized covariance matrix for a given set of assets within a multivariate heterogeneous autoregressive (MHAR) framework. Utilizing high-frequency data for the U.S. aggregate and industry indexes and a large set of exogenous predictors that include financial, macroeconomic, sentiment, and climate-based factors, we evaluate the out-of-sample performance of industry portfolios constructed from forecasted realized covariance matrices across various univariate and multivariate forecasting models. Our findings show that LASSO-based multivariate HAR models employing predictors that capture climate uncertainty generally yield more consistent evidence regarding the accuracy of the realized covariance forecasts, providing further support for the growing evidence that climate related factors significantly drive return and volatility dynamics in financial markets. While international summits and global warming stand out as the dominant climate predictors for realized volatility forecasts, both climate and macroeconomic predictors prove equally important for longer term correlation forecasts. In these forecasts, the U.S. EPU index and natural disasters, along with U.S. climate policy uncertainty, play dominant predictive roles. Our results suggest that the MHAR framework, coupled with DRD decomposition that splits the covariance matrix into a diagonal matrix of realized variances and realized correlations, can be utilized in a high-frequency setting to implement diversification and smart beta strategies for various investment horizons.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"81 ","pages":"Article 101595"},"PeriodicalIF":2.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143157559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-31DOI: 10.1016/j.jempfin.2025.101592
Shun Fu , Emma Li , Li Liao , Zhengwei Wang , Hongyu Xiang
Based on unique data containing the loan history and online consumption information of cash loan borrowers, we apply an exogenous credit supply shock to these borrowers and show that increased credit increases individuals' delinquency rates and reliance on cash loans. Higher credit supply increases the likelihood of a loan being overdue over 60 days by 5.7% and decreases platform exit by 33%. This effect on delinquency is significantly less prominent among individuals with greater financial literacy. Second, we demonstrate that credit expansion is positively associated with an increase in subsequent borrower consumption, particularly addictive consumption.
{"title":"Unveiling the villain: Credit supply and the debt trap","authors":"Shun Fu , Emma Li , Li Liao , Zhengwei Wang , Hongyu Xiang","doi":"10.1016/j.jempfin.2025.101592","DOIUrl":"10.1016/j.jempfin.2025.101592","url":null,"abstract":"<div><div>Based on unique data containing the loan history and online consumption information of cash loan borrowers, we apply an exogenous credit supply shock to these borrowers and show that increased credit increases individuals' delinquency rates and reliance on cash loans. Higher credit supply increases the likelihood of a loan being overdue over 60 days by 5.7% and decreases platform exit by 33%. This effect on delinquency is significantly less prominent among individuals with greater financial literacy. Second, we demonstrate that credit expansion is positively associated with an increase in subsequent borrower consumption, particularly addictive consumption.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"81 ","pages":"Article 101592"},"PeriodicalIF":2.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143231742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-27DOI: 10.1016/j.jempfin.2025.101580
Jie Cao , Jason C. Hsu , Linjia Song , Zhanbing Xiao , Xintong Zhan
We document that when smart beta ETFs are more actively traded, mutual fund flow sensitivity to multi-factor alphas increases significantly. This evidence is consistent with a friction hypothesis that active smart beta ETF trading reduces the costs of investing in non-market risk factors (e.g., SMB and HML). Consequently, when this friction is diminished, investors reward mutual fund managers more for multi-factor alphas. We show that the results are driven by sophisticated investors, ruling out behavioral explanations. The results are concentrated among mutual funds with high exposures to non-market risk factors. We further find that the gap between CAPM alpha and multi-factor alphas in explaining flows reduces when smart beta ETFs are actively traded.
{"title":"Smart beta, “smarter” flows","authors":"Jie Cao , Jason C. Hsu , Linjia Song , Zhanbing Xiao , Xintong Zhan","doi":"10.1016/j.jempfin.2025.101580","DOIUrl":"10.1016/j.jempfin.2025.101580","url":null,"abstract":"<div><div>We document that when smart beta ETFs are more actively traded, mutual fund flow sensitivity to multi-factor alphas increases significantly. This evidence is consistent with a friction hypothesis that active smart beta ETF trading reduces the costs of investing in non-market risk factors (e.g., SMB and HML). Consequently, when this friction is diminished, investors reward mutual fund managers more for multi-factor alphas. We show that the results are driven by sophisticated investors, ruling out behavioral explanations. The results are concentrated among mutual funds with high exposures to non-market risk factors. We further find that the gap between CAPM alpha and multi-factor alphas in explaining flows reduces when smart beta ETFs are actively traded.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"81 ","pages":"Article 101580"},"PeriodicalIF":2.1,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143157557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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