Pub Date : 2025-11-27DOI: 10.1016/j.jempfin.2025.101671
Luca Vincenzo Ballestra , Enzo D’Innocenzo , Christian Tezza
We introduce a novel GARCH model that integrates two sources of uncertainty to better capture the rich, multi-component dynamics often observed in the volatility of financial assets. This model provides a quasi closed-form representation of the characteristic function for future log-returns, from which semi-analytical formulas for option pricing can be derived. A theoretical analysis is conducted to establish sufficient conditions for strict stationarity and geometric ergodicity, while also obtaining the continuous-time diffusion limit of the model. Empirical evaluations, conducted both in-sample and out-of-sample using S&P500 time series data, show that our model outperforms widely used single-factor models in predicting returns and option prices. The code for estimating the model, as well as for computing option prices, is made accessible in MATLAB language.1
{"title":"A GARCH model with two volatility components and two driving factors","authors":"Luca Vincenzo Ballestra , Enzo D’Innocenzo , Christian Tezza","doi":"10.1016/j.jempfin.2025.101671","DOIUrl":"10.1016/j.jempfin.2025.101671","url":null,"abstract":"<div><div>We introduce a novel GARCH model that integrates two sources of uncertainty to better capture the rich, multi-component dynamics often observed in the volatility of financial assets. This model provides a quasi closed-form representation of the characteristic function for future log-returns, from which semi-analytical formulas for option pricing can be derived. A theoretical analysis is conducted to establish sufficient conditions for strict stationarity and geometric ergodicity, while also obtaining the continuous-time diffusion limit of the model. Empirical evaluations, conducted both in-sample and out-of-sample using S&P500 time series data, show that our model outperforms widely used single-factor models in predicting returns and option prices. The code for estimating the model, as well as for computing option prices, is made accessible in MATLAB language.<span><span><sup>1</sup></span></span></div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"85 ","pages":"Article 101671"},"PeriodicalIF":2.4,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145617262","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 : 2025-11-25DOI: 10.1016/j.jempfin.2025.101673
Ulrich Hounyo , Jiahao Lin
This paper identifies the issue of “duplicate observations” in existing methods for analyzing mutual fund performance and proposes a solution using a novel wild bootstrap-based approach. Our proposed method preserves various characteristics of mutual fund databases, including entry/exit points for each fund (i.e., missing data) and cross-sectional information. We show that our proposed bootstrap tests have a near-optimal size and exhibit greater power compared to widely used standard bootstrap methods for evaluating mutual fund performance. Additionally, we present a new approach to picking the top-performing mutual funds. Our empirical results indicate that a measurable fraction of funds outperform the market.
{"title":"Can mutual fund “stars” really pick stocks? New evidence from a wild bootstrap analysis","authors":"Ulrich Hounyo , Jiahao Lin","doi":"10.1016/j.jempfin.2025.101673","DOIUrl":"10.1016/j.jempfin.2025.101673","url":null,"abstract":"<div><div>This paper identifies the issue of “duplicate observations” in existing methods for analyzing mutual fund performance and proposes a solution using a novel wild bootstrap-based approach. Our proposed method preserves various characteristics of mutual fund databases, including entry/exit points for each fund (i.e., missing data) and cross-sectional information. We show that our proposed bootstrap tests have a near-optimal size and exhibit greater power compared to widely used standard bootstrap methods for evaluating mutual fund performance. Additionally, we present a new approach to picking the top-performing mutual funds. Our empirical results indicate that a measurable fraction of funds outperform the market.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"85 ","pages":"Article 101673"},"PeriodicalIF":2.4,"publicationDate":"2025-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145600329","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 : 2025-11-20DOI: 10.1016/j.jempfin.2025.101672
Nicola Bartolini, Silvia Romagnoli, Amia Santini
This study explores how climate-related risk factors influence the European equity and fixed-income markets. We examine the effect of specific physical risk drivers, including temperature fluctuations, drought, floods, wind, and wildfire risk, on both stocks and bonds. Additionally, we assess the impact of transition risk using two potential indicators: the log-returns of futures on European Carbon Allowances and a Transition Risk Index derived from credit default spreads. We also compare them to see if they carry the same information. Our findings reveal that climate risk variables have different effects on stocks and bonds, with stock returns appearing mostly unaffected by climate-related variables. In contrast, bond z-spreads show significant statistical relationships with both physical and transition climate risks. Physical risk, on average, rewards the green bonds in the sample, and penalizes the traditional bonds. As for transition risk, the two proxies are shown to capture different types of information and to affect different bonds. This suggests that credit default swaps are pricing a transition risk that goes beyond carbon emissions.
{"title":"Understanding climate risk in Europe: Are transition and physical risk priced in equity and fixed-income markets?","authors":"Nicola Bartolini, Silvia Romagnoli, Amia Santini","doi":"10.1016/j.jempfin.2025.101672","DOIUrl":"10.1016/j.jempfin.2025.101672","url":null,"abstract":"<div><div>This study explores how climate-related risk factors influence the European equity and fixed-income markets. We examine the effect of specific physical risk drivers, including temperature fluctuations, drought, floods, wind, and wildfire risk, on both stocks and bonds. Additionally, we assess the impact of transition risk using two potential indicators: the log-returns of futures on European Carbon Allowances and a Transition Risk Index derived from credit default spreads. We also compare them to see if they carry the same information. Our findings reveal that climate risk variables have different effects on stocks and bonds, with stock returns appearing mostly unaffected by climate-related variables. In contrast, bond z-spreads show significant statistical relationships with both physical and transition climate risks. Physical risk, on average, rewards the green bonds in the sample, and penalizes the traditional bonds. As for transition risk, the two proxies are shown to capture different types of information and to affect different bonds. This suggests that credit default swaps are pricing a transition risk that goes beyond carbon emissions.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101672"},"PeriodicalIF":2.4,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568541","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 : 2025-11-20DOI: 10.1016/j.jempfin.2025.101670
Zhenshan Chen , Zhibing Li , Jie Liu , Xiaoyu Liu
We find that investor attention significantly increases stock price crash risk. To identify the causal effect, we employ daily repeated quasi-natural experiments where the difference of investor attention is not driven by stock fundamentals, but rather exogenous price rounding issue. This positive effect is more pronounced among firms with higher daily abnormal Baidu search index and higher abnormal small fund inflows ratio, but is mitigated for firms with more sophisticated investors, state-owned enterprise, and firms with relaxation of short-sale constraints. Additionally, we provide supporting evidence that information asymmetry triggered by noise attention serves as a channel through which investor attention amplifies stock price crash risk. Finally, we provide additional evidence illustrating the generalizability of our findings.
{"title":"Information salience, investor attention, and stock price crash risk","authors":"Zhenshan Chen , Zhibing Li , Jie Liu , Xiaoyu Liu","doi":"10.1016/j.jempfin.2025.101670","DOIUrl":"10.1016/j.jempfin.2025.101670","url":null,"abstract":"<div><div>We find that investor attention significantly increases stock price crash risk. To identify the causal effect, we employ daily repeated quasi-natural experiments where the difference of investor attention is not driven by stock fundamentals, but rather exogenous price rounding issue. This positive effect is more pronounced among firms with higher daily abnormal Baidu search index and higher abnormal small fund inflows ratio, but is mitigated for firms with more sophisticated investors, state-owned enterprise, and firms with relaxation of short-sale constraints. Additionally, we provide supporting evidence that information asymmetry triggered by noise attention serves as a channel through which investor attention amplifies stock price crash risk. Finally, we provide additional evidence illustrating the generalizability of our findings.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"85 ","pages":"Article 101670"},"PeriodicalIF":2.4,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145787455","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 : 2025-11-20DOI: 10.1016/j.jempfin.2025.101669
Chae-Deug Yi
This study investigates the dynamic structure of intraday volatility and jump behavior in the Chinese yuan and US dollar exchange market by employing a Gumbel-distribution-based threshold derived from extreme value theory. Using five-minute high-frequency data over 2,450 trading days, we construct a daily jump probability index and examine its responsiveness to major economic shocks, including the U.S.–China trade war and the COVID-19 pandemic. Regression and simulation analyses (5,000 replications) show that the Gumbel-based jump metric provides superior explanatory power in detecting large and irregular jumps. The Gumbel distribution offers a clear and theoretically grounded thresholding mechanism, making it particularly effective in identifying episodic volatility clusters during the 2010s. Tests by Lee and Hannig (2010) and Laurent and Shi (2020) also suggest that the Gumbel jump statistic is more appropriate for capturing the frequent and discontinuous jumps in foreign exchange volatility. Furthermore, after filtering for intraday periodicity, the estimated jump probabilities significantly decline, indicating the importance of periodicity adjustment. This study also confirms that jump probabilities were notably higher during the U.S.–China trade war and the COVID-19 pandemic than in the overall sample period. Sensitivity tests on volatility filtering and simulation parameters further demonstrate the robustness of the Gumbel-based jump distribution.
{"title":"Volatility and jumps in the Chinese Yuan using Gumbel distribution during the trade war and COVID-19 pandemic","authors":"Chae-Deug Yi","doi":"10.1016/j.jempfin.2025.101669","DOIUrl":"10.1016/j.jempfin.2025.101669","url":null,"abstract":"<div><div>This study investigates the dynamic structure of intraday volatility and jump behavior in the Chinese yuan and US dollar exchange market by employing a Gumbel-distribution-based threshold derived from extreme value theory. Using five-minute high-frequency data over 2,450 trading days, we construct a daily jump probability index and examine its responsiveness to major economic shocks, including the U.S.–China trade war and the COVID-19 pandemic. Regression and simulation analyses (5,000 replications) show that the Gumbel-based jump metric provides superior explanatory power in detecting large and irregular jumps. The Gumbel distribution offers a clear and theoretically grounded thresholding mechanism, making it particularly effective in identifying episodic volatility clusters during the 2010s. Tests by Lee and Hannig (2010) and Laurent and Shi (2020) also suggest that the Gumbel jump statistic is more appropriate for capturing the frequent and discontinuous jumps in foreign exchange volatility. Furthermore, after filtering for intraday periodicity, the estimated jump probabilities significantly decline, indicating the importance of periodicity adjustment. This study also confirms that jump probabilities were notably higher during the U.S.–China trade war and the COVID-19 pandemic than in the overall sample period. Sensitivity tests on volatility filtering and simulation parameters further demonstrate the robustness of the Gumbel-based jump distribution.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"85 ","pages":"Article 101669"},"PeriodicalIF":2.4,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682650","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 : 2025-11-01DOI: 10.1016/j.jempfin.2025.101667
Pierluca Pannella
This paper documents that the dividend payout ratios of larger US banks rise when interest rates increase. To account for this pattern, I develop a model of optimal investment and deposit issuance under a risk-based constraint. Smaller banks primarily generate profits from the Fed funds-deposit spread, which typically widens with higher rates. Larger banks, by contrast, hold a greater share of risky assets and keep government bonds mainly as precautionary buffers. In high-interest-rate environments, these larger banks see only a modest increase in profitability. Consequently, they have weaker incentives to expand their investments and instead opt to reduce their buffer of safe assets to distribute higher dividends. Empirical evidence on payout behavior and leverage across banks that gain different shares of income from government bonds aligns with the prediction of the model. The findings highlight the importance of monitoring banks’ payout and leverage during periods of rising interest rates.
{"title":"Bank dividends, interest expenses, and leverage","authors":"Pierluca Pannella","doi":"10.1016/j.jempfin.2025.101667","DOIUrl":"10.1016/j.jempfin.2025.101667","url":null,"abstract":"<div><div>This paper documents that the dividend payout ratios of larger US banks rise when interest rates increase. To account for this pattern, I develop a model of optimal investment and deposit issuance under a risk-based constraint. Smaller banks primarily generate profits from the Fed funds-deposit spread, which typically widens with higher rates. Larger banks, by contrast, hold a greater share of risky assets and keep government bonds mainly as precautionary buffers. In high-interest-rate environments, these larger banks see only a modest increase in profitability. Consequently, they have weaker incentives to expand their investments and instead opt to reduce their buffer of safe assets to distribute higher dividends. Empirical evidence on payout behavior and leverage across banks that gain different shares of income from government bonds aligns with the prediction of the model. The findings highlight the importance of monitoring banks’ payout and leverage during periods of rising interest rates.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101667"},"PeriodicalIF":2.4,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145516363","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 : 2025-10-16DOI: 10.1016/j.jempfin.2025.101666
Jiaxing Tian , Hong Xiang , Minghai Xu
We show that the insider trading pattern on anomaly long-short portfolio stocks can forecast anomaly returns. Specifically, we use the fraction of anomaly long-leg (short-leg) stocks being bought (sold) by insiders as a signal to extract insiders’ information on expected returns of the anomaly. Based on a composite anomaly measure that combines 11 prominent anomalies, we show that the insider trading signal significantly forecasts anomaly returns both in-sample and out-of-sample. These findings also help disentangle the risk-based and the mispricing-based explanations for anomaly returns.
{"title":"Insider trading and anomalies","authors":"Jiaxing Tian , Hong Xiang , Minghai Xu","doi":"10.1016/j.jempfin.2025.101666","DOIUrl":"10.1016/j.jempfin.2025.101666","url":null,"abstract":"<div><div>We show that the insider trading pattern on anomaly long-short portfolio stocks can forecast anomaly returns. Specifically, we use the fraction of anomaly long-leg (short-leg) stocks being bought (sold) by insiders as a signal to extract insiders’ information on expected returns of the anomaly. Based on a composite anomaly measure that combines 11 prominent anomalies, we show that the insider trading signal significantly forecasts anomaly returns both in-sample and out-of-sample. These findings also help disentangle the risk-based and the mispricing-based explanations for anomaly returns.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101666"},"PeriodicalIF":2.4,"publicationDate":"2025-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321572","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 : 2025-10-10DOI: 10.1016/j.jempfin.2025.101664
Yuqi Gu , Mahsa Kaviani , Lily Li , Hosein Maleki , Connie X. Mao
We examine the impact of Sinclair Broadcast Group, the largest conservative media network in the US local TV markets, on corporate innovation following its staggered expansion across the country. We find a significant reduction in innovation output two to three years after Sinclair entry. As a larger proportion of inventors self-identify as left-leaning, we find that the effect runs through two mutually non-exclusive channels: the inventor productivity channel and the talent replacement channel. Inventors become less innovative when they stay in Sinclair-exposed firms, and firms face challenges replacing departed talent upon the local ideology shock induced by Sinclair.
{"title":"Media, inventors, and corporate innovation","authors":"Yuqi Gu , Mahsa Kaviani , Lily Li , Hosein Maleki , Connie X. Mao","doi":"10.1016/j.jempfin.2025.101664","DOIUrl":"10.1016/j.jempfin.2025.101664","url":null,"abstract":"<div><div>We examine the impact of Sinclair Broadcast Group, the largest conservative media network in the US local TV markets, on corporate innovation following its staggered expansion across the country. We find a significant reduction in innovation output two to three years after Sinclair entry. As a larger proportion of inventors self-identify as left-leaning, we find that the effect runs through two mutually non-exclusive channels: the inventor productivity channel and the talent replacement channel. Inventors become less innovative when they stay in Sinclair-exposed firms, and firms face challenges replacing departed talent upon the local ideology shock induced by Sinclair.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101664"},"PeriodicalIF":2.4,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145321571","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 : 2025-10-10DOI: 10.1016/j.jempfin.2025.101663
Mengmeng Dong
I provide novel evidence supporting the robust predictability of the “signal zoo” by clustering and aggregating 84 signals based on economic similarity. Economic clusters not only exhibit high (low) within-cluster (between-cluster) signal correlations — comparable to -means clusters — but also produce composites that non-redundantly explain the cross-section of U.S. stock returns. All composites exhibit robust predictability in the U.S. and certain evidence in the global regions. Subsample and long-run return tests suggest that predictability primarily arises from risk, except for momentum, which is driven by mispricing. Composites generally outperform an average-signal strategy due to their superior ability to identify less noisy stocks.
{"title":"Economic aggregation of return signals in global markets","authors":"Mengmeng Dong","doi":"10.1016/j.jempfin.2025.101663","DOIUrl":"10.1016/j.jempfin.2025.101663","url":null,"abstract":"<div><div>I provide novel evidence supporting the robust predictability of the “signal zoo” by clustering and aggregating 84 signals based on economic similarity. Economic clusters not only exhibit high (low) within-cluster (between-cluster) signal correlations — comparable to <span><math><mi>k</mi></math></span>-means clusters — but also produce composites that non-redundantly explain the cross-section of U.S. stock returns. All composites exhibit robust predictability in the U.S. and certain evidence in the global regions. Subsample and long-run return tests suggest that predictability primarily arises from risk, except for momentum, which is driven by mispricing. Composites generally outperform an average-signal strategy due to their superior ability to identify less noisy stocks.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101663"},"PeriodicalIF":2.4,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267521","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 : 2025-10-05DOI: 10.1016/j.jempfin.2025.101665
Yunqi Zhang , Yu Meng , Xiaoyu Zhang
Bankruptcy abuse prevention has been criticized for increasing foreclosure rates, imposing negative impacts on housing markets, and aggravating the financial crisis. By contrast, this paper documents that bankruptcy abuse prevention reduces household debt overhang, a phenomenon harmful to home values and housing markets. Using a difference-in-differences analysis, we find that households in recourse states increased their home improvement and maintenance expenditures after the Bankruptcy Abuse Prevention and Consumer Protection Act, a period during which the households paid considerable attention to the downside risk of the housing market, and that the effects vary by home equity level. The results remain unchanged with alternative specifications and cannot be explained by credit changes, judicial and nonjudicial foreclosures, homestead exemption, house sales, or heterogeneous expectations. Last but not least, we use entropy balancing to eliminate the differences between the treatment and control groups and get similar results.
{"title":"Household debt overhang and bankruptcy abuse prevention","authors":"Yunqi Zhang , Yu Meng , Xiaoyu Zhang","doi":"10.1016/j.jempfin.2025.101665","DOIUrl":"10.1016/j.jempfin.2025.101665","url":null,"abstract":"<div><div>Bankruptcy abuse prevention has been criticized for <em>increasing</em> foreclosure rates, imposing negative impacts on housing markets, and aggravating the financial crisis. By contrast, this paper documents that bankruptcy abuse prevention <em>reduces</em> household debt overhang, a phenomenon harmful to home values and housing markets. Using a difference-in-differences analysis, we find that households in recourse states increased their home improvement and maintenance expenditures after the Bankruptcy Abuse Prevention and Consumer Protection Act, a period during which the households paid considerable attention to the downside risk of the housing market, and that the effects vary by home equity level. The results remain unchanged with alternative specifications and cannot be explained by credit changes, judicial and nonjudicial foreclosures, homestead exemption, house sales, or heterogeneous expectations. Last but not least, we use entropy balancing to eliminate the differences between the treatment and control groups and get similar results.</div></div>","PeriodicalId":15704,"journal":{"name":"Journal of Empirical Finance","volume":"84 ","pages":"Article 101665"},"PeriodicalIF":2.4,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145568542","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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