This study examined how industry concentration structure can affect mutual fund performance under the dual channels of fund manager effort and investor erosion.Using quarterly data from Chinese equity and equity-orien...This study examined how industry concentration structure can affect mutual fund performance under the dual channels of fund manager effort and investor erosion.Using quarterly data from Chinese equity and equity-oriented hybrid funds from 2015 to 2022,the study investigated this relationship and its underlying mechanisms.The results show that greater industry concentration significantly improved fund performance.The positive effect stemmed from the interplay between managers'strategic efforts and the erosive impact of investor behavior.Mechanism analysis indicates that fund managers enhanced performance primarily through professional skill-driven industry allocation strategies rather than informational advantages.Industry concentration also produced time-lagged effects on performance.The effort-driven component of concentration contributed positively to performance,whereas investor subscriptions and redemptions generated significant erosion effects.The results identify industry concentration structure as a critical determinant of fund performance,providing theoretical and empirical foundations for re-evaluating fund performance sources.展开更多
This study explores the influence of investor behavior and market sentiment on asset pricing mechanisms in both developed and emerging market economies.By comparing markets such as the United States,Japan,Brazil,and I...This study explores the influence of investor behavior and market sentiment on asset pricing mechanisms in both developed and emerging market economies.By comparing markets such as the United States,Japan,Brazil,and India,the research investigates how psychological factors,including overconfidence,loss aversion,and sentiment,affect asset returns and market volatility.Data spanning 10 years(2010-2020)is analyzed,incorporating traditional financial indicators,macroeconomic factors,and sentiment data derived from social media,news platforms,and sentiment indices.The empirical findings reveal significant heterogeneity across markets.In emerging markets,investor sentiment demonstrates a more pronounced effect on asset pricing,with sentiment fluctuations contributing significantly to volatility.In contrast,developed markets like the U.S.and Japan exhibit more stability,with investor behavior driven largely by fundamentals.A new sentiment resonance model is developed to capture the spillover effect of sentiment from developed to emerging markets,while behavioral finance models are enhanced to account for the emotional transmission between investor decisions and asset prices.The study suggests that incorporating behavioral insights into traditional asset pricing models can improve their explanatory power,particularly in emerging markets where investor sentiment plays a pivotal role in shaping asset prices.展开更多
In the context of vigorously developing China＇s securities market institutional investors in the period of economic transition, this paper does the empirical research on the herd behavior from the view of the interac...In the context of vigorously developing China＇s securities market institutional investors in the period of economic transition, this paper does the empirical research on the herd behavior from the view of the interaction between individual and institutional investors. This paper adopts the standard deviation of trading volume the cross-section to measure herd behavior. The results show that no matter what the market is in bull status and bear status, institutional investors perform herd behavior and with the expansion of the shareholding scale in a bull market, the herd behavior is higher, which suggests that the vigorous development of institutional investors has not eliminated herd behavior. This paper further confirms that there is the endogenous volatility in the market based on an artificial stock market. Finally it is demonstrated the herd behavior of institutional investors cause abnormal fluctuations in the market.展开更多
With the rapid development of Internet media,Internet media coverage has more or less influence on investors'psychological level.This article uses Python technology to climb 2019.9 to 2020.1 of the monthly news re...With the rapid development of Internet media,Internet media coverage has more or less influence on investors'psychological level.This article uses Python technology to climb 2019.9 to 2020.1 of the monthly news reports on A share listed companies in the Snowball net,and studies the relationship between media attention and investors'heterogeneous beliefs.It is found that media attention is positively correlated with investors'heterogeneous beliefs,that is,investors are more likely to choose stocks frequently reported by media.Further research finds that media reports will strengthen investors'heterogeneous beliefs,affect investors'investment behavior,and ultimately lead to the increase of stock trading volume.展开更多
Although momentum strategies result in abnormal profitability,thereby challenging the efficient market hypothesis(EMH),concerns persist regarding their reliability due to their significant volatility and susceptibilit...Although momentum strategies result in abnormal profitability,thereby challenging the efficient market hypothesis(EMH),concerns persist regarding their reliability due to their significant volatility and susceptibility to substantial losses.In this study,we investigate the limitations of these strategies and propose a solution.Our literature review reveals that the volatile profits are due to statistical analyses that assume the persistence of past patterns,leading to unreliable results in out-of-sample scenarios when underlying mechanisms evolve.Statistical analysis,the predominant method in financial economics,often proves inadequate in explaining market fluctuations and predicting crashes.To overcome these limitations,a paradigm shift towards dynamic approaches is essential.Drawing inspiration from three groundbreaking economists,we introduce the extended Samuelson model(ESM),a dynamic model that connects price changes to market participant actions.This paradigm transition uncovers several significant findings.First,timely signals indicate momentum initiations,cessations,and reversals,validated using S&P 500 data from 1999 to 2023.Second,ESM predicts the 1987 Black Monday crash weeks in advance,offering a new perspective on its underlying cause.Third,we classify sequential stock price data into eight distinct market states,including their thresholds for transitions,laying the groundwork for market trend predictions and risk assessments.Fourth,the ESM is shown to be a compelling alternative to EMH,offering potent explanatory and predictive power based on a single,realistic assumption.Our findings suggest that ESM has the potential to provide policymakers with proactive tools,enabling financial institutions to enhance their risk assessment and management strategies.展开更多
基金support from the National Social Science Fund Youth Project(No.24CJY050)the Key Project of the Beijing Municipal Social Science Fund(No.25BJ02003).
文摘This study examined how industry concentration structure can affect mutual fund performance under the dual channels of fund manager effort and investor erosion.Using quarterly data from Chinese equity and equity-oriented hybrid funds from 2015 to 2022,the study investigated this relationship and its underlying mechanisms.The results show that greater industry concentration significantly improved fund performance.The positive effect stemmed from the interplay between managers'strategic efforts and the erosive impact of investor behavior.Mechanism analysis indicates that fund managers enhanced performance primarily through professional skill-driven industry allocation strategies rather than informational advantages.Industry concentration also produced time-lagged effects on performance.The effort-driven component of concentration contributed positively to performance,whereas investor subscriptions and redemptions generated significant erosion effects.The results identify industry concentration structure as a critical determinant of fund performance,providing theoretical and empirical foundations for re-evaluating fund performance sources.
文摘This study explores the influence of investor behavior and market sentiment on asset pricing mechanisms in both developed and emerging market economies.By comparing markets such as the United States,Japan,Brazil,and India,the research investigates how psychological factors,including overconfidence,loss aversion,and sentiment,affect asset returns and market volatility.Data spanning 10 years(2010-2020)is analyzed,incorporating traditional financial indicators,macroeconomic factors,and sentiment data derived from social media,news platforms,and sentiment indices.The empirical findings reveal significant heterogeneity across markets.In emerging markets,investor sentiment demonstrates a more pronounced effect on asset pricing,with sentiment fluctuations contributing significantly to volatility.In contrast,developed markets like the U.S.and Japan exhibit more stability,with investor behavior driven largely by fundamentals.A new sentiment resonance model is developed to capture the spillover effect of sentiment from developed to emerging markets,while behavioral finance models are enhanced to account for the emotional transmission between investor decisions and asset prices.The study suggests that incorporating behavioral insights into traditional asset pricing models can improve their explanatory power,particularly in emerging markets where investor sentiment plays a pivotal role in shaping asset prices.
基金supported by the National Nature Science Foundation under Grant No.71201124
文摘In the context of vigorously developing China＇s securities market institutional investors in the period of economic transition, this paper does the empirical research on the herd behavior from the view of the interaction between individual and institutional investors. This paper adopts the standard deviation of trading volume the cross-section to measure herd behavior. The results show that no matter what the market is in bull status and bear status, institutional investors perform herd behavior and with the expansion of the shareholding scale in a bull market, the herd behavior is higher, which suggests that the vigorous development of institutional investors has not eliminated herd behavior. This paper further confirms that there is the endogenous volatility in the market based on an artificial stock market. Finally it is demonstrated the herd behavior of institutional investors cause abnormal fluctuations in the market.
文摘With the rapid development of Internet media,Internet media coverage has more or less influence on investors'psychological level.This article uses Python technology to climb 2019.9 to 2020.1 of the monthly news reports on A share listed companies in the Snowball net,and studies the relationship between media attention and investors'heterogeneous beliefs.It is found that media attention is positively correlated with investors'heterogeneous beliefs,that is,investors are more likely to choose stocks frequently reported by media.Further research finds that media reports will strengthen investors'heterogeneous beliefs,affect investors'investment behavior,and ultimately lead to the increase of stock trading volume.
文摘Although momentum strategies result in abnormal profitability,thereby challenging the efficient market hypothesis(EMH),concerns persist regarding their reliability due to their significant volatility and susceptibility to substantial losses.In this study,we investigate the limitations of these strategies and propose a solution.Our literature review reveals that the volatile profits are due to statistical analyses that assume the persistence of past patterns,leading to unreliable results in out-of-sample scenarios when underlying mechanisms evolve.Statistical analysis,the predominant method in financial economics,often proves inadequate in explaining market fluctuations and predicting crashes.To overcome these limitations,a paradigm shift towards dynamic approaches is essential.Drawing inspiration from three groundbreaking economists,we introduce the extended Samuelson model(ESM),a dynamic model that connects price changes to market participant actions.This paradigm transition uncovers several significant findings.First,timely signals indicate momentum initiations,cessations,and reversals,validated using S&P 500 data from 1999 to 2023.Second,ESM predicts the 1987 Black Monday crash weeks in advance,offering a new perspective on its underlying cause.Third,we classify sequential stock price data into eight distinct market states,including their thresholds for transitions,laying the groundwork for market trend predictions and risk assessments.Fourth,the ESM is shown to be a compelling alternative to EMH,offering potent explanatory and predictive power based on a single,realistic assumption.Our findings suggest that ESM has the potential to provide policymakers with proactive tools,enabling financial institutions to enhance their risk assessment and management strategies.
