Han and Lesmond (2011) find that stock liquidity, namely bid-ask bounce, affects the pricing of idiosyncratic volatility. Following Ang et al. (2009) and Han and Lesmond (2011), we investigate the pricing of idiosyncratic volatility and liquidity-adjusted idiosyncratic volatility over the period January 2004 to December 2013 using a comprehensive Australian dataset. Our results indicate that (1) both lagged idiosyncratic volatility and lagged liquidity-adjusted idiosyncratic volatility are strongly and positively related to stock returns over the sample period; (2) consistent with Han and Lesmond (2011), the pricing of idiosyncratic volatility is largely captured by stock liquidity; (3) our liquidity adjusted idiosyncratic volatility estimates work well in explaining the variations of the stocks of small firms but do not explain much variations in stocks of large firms when size and BE/ME are controlled; (4) high idiosyncratic volatility stocks tend to be of small, volatile and illiquid.
Han和Lesmond(2011)发现股票流动性，即买卖反弹，会影响特质波动的定价。继Ang et al.(2009)和Han and Lesmond(2011)之后，我们使用综合的澳大利亚数据集研究了2004年1月至2013年12月期间的特殊波动率和流动性调整的特殊波动率的定价。研究结果表明:(1)滞后特质波动率和滞后流动性调整特质波动率与股票收益呈显著正相关;(2)与Han and Lesmond(2011)一致，股票流动性在很大程度上反映了特质波动率的定价;(3)流动性调整后的特质波动率估计可以很好地解释小公司股票的变化，但在控制规模和BE/ME时，不能解释大公司股票的变化;(4)高特质波动率股票往往规模小、波动大、流动性差。
{"title":"The Bid-Ask Bounce Effect and the Pricing of Cross-Sectional Idiosyncratic Volatility: An Australian Study","authors":"B. Liu, M. Dempsey, M. Tan","doi":"10.2139/ssrn.2563610","DOIUrl":"https://doi.org/10.2139/ssrn.2563610","url":null,"abstract":"Han and Lesmond (2011) find that stock liquidity, namely bid-ask bounce, affects the pricing of idiosyncratic volatility. Following Ang et al. (2009) and Han and Lesmond (2011), we investigate the pricing of idiosyncratic volatility and liquidity-adjusted idiosyncratic volatility over the period January 2004 to December 2013 using a comprehensive Australian dataset. Our results indicate that (1) both lagged idiosyncratic volatility and lagged liquidity-adjusted idiosyncratic volatility are strongly and positively related to stock returns over the sample period; (2) consistent with Han and Lesmond (2011), the pricing of idiosyncratic volatility is largely captured by stock liquidity; (3) our liquidity adjusted idiosyncratic volatility estimates work well in explaining the variations of the stocks of small firms but do not explain much variations in stocks of large firms when size and BE/ME are controlled; (4) high idiosyncratic volatility stocks tend to be of small, volatile and illiquid.","PeriodicalId":422957,"journal":{"name":"2015 Financial Markets & Corporate Governance Conference (Archive)","volume":"371 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122762830","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 investigates the impact of announcements of European environmental regulations on the French equity market. Using event study methodology and asset pricing models, we assess whether announcements of stringent and lax policies affect returns of environmentally-friendly businesses and polluters. Additionally, we estimate the change in systematic risk following the new regulations and develop a test to check if these effects are excessive. According to the results, the French capital market is particularly sensitive to announcements made by the European Union Emission Trading System and furthermore environmental regulations are excessive in a relatively small proportion of firms.
{"title":"Are European Environmental Regulations Excessive?","authors":"V. Ramiah, Huy Nguyen Anh Pham, I. Moosa","doi":"10.2139/SSRN.2560357","DOIUrl":"https://doi.org/10.2139/SSRN.2560357","url":null,"abstract":"This paper investigates the impact of announcements of European environmental regulations on the French equity market. Using event study methodology and asset pricing models, we assess whether announcements of stringent and lax policies affect returns of environmentally-friendly businesses and polluters. Additionally, we estimate the change in systematic risk following the new regulations and develop a test to check if these effects are excessive. According to the results, the French capital market is particularly sensitive to announcements made by the European Union Emission Trading System and furthermore environmental regulations are excessive in a relatively small proportion of firms.","PeriodicalId":422957,"journal":{"name":"2015 Financial Markets & Corporate Governance Conference (Archive)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121836846","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 a new model that captures the interaction between duration and magnitude of changes in asset prices, and thus provides a convenient framework to test statistically the existence of such relationship. The model is flexible and contains various well known models as special cases, including, the Exponential Generalised Autoregressive Heteroskedasticity (EGARCH) model of Nelson (1991) and the Logarithmic Conditional Duration (Log-ACD) model of Bauwens and Giot (2000). Despite having the EGARCH model as a special case, the objective of the model is not trying to model conditional duration and conditional volatility jointly. As shown in Ghysels and Jasiak (1998), modelling conditional duration and volatility jointly is technically challenging. This is due to the fact that volatility is defined over a regular sampling frequency but duration is defined over irregular time intervals. Given GARCH model is not generally closed under temporal aggregation, this creates a challenging modelling problem. The aim of this paper is to avoid this challenge by not modelling the conditional volatility, but instead, model the dynamics in the magnitudes of price change. The paper argues that since volatility is a function of the magnitudes of price change, testing the relationship between duration and the magnitude of price change provides an indirect test on the relationship between duration and volatility. The paper also obtains theoretical results for the Quasi-Maximum Likelihood Estimator (QMLE) for the proposed model. Specifically, sufficient conditions for consistency and asymptotic normality are derived under mild assumptions. Monte Carlo experiments also provide further support of the theoretical results and demonstrate that the QMLE has reasonably good finite sample performance. The paper then applies the model to nine different assets from three different asset classes, namely two exchange rate, two commodities and five stocks. The two currencies are Australia/US and British Pound/US exchange rates; the two commodities are Gold and Silver and the five stocks are BHP, Rio Tinto, CBS, ANZ and Apple. The sample spans from 4 January 2010 to 30 December 2011 with an average of 100,000 observations.
{"title":"Modelling the Relationships between Duration and Volatility in Asset Prices","authors":"F. Chan, J. Petchey","doi":"10.2139/ssrn.2559726","DOIUrl":"https://doi.org/10.2139/ssrn.2559726","url":null,"abstract":"This paper proposes a new model that captures the interaction between duration and magnitude of changes in asset prices, and thus provides a convenient framework to test statistically the existence of such relationship. The model is flexible and contains various well known models as special cases, including, the Exponential Generalised Autoregressive Heteroskedasticity (EGARCH) model of Nelson (1991) and the Logarithmic Conditional Duration (Log-ACD) model of Bauwens and Giot (2000). Despite having the EGARCH model as a special case, the objective of the model is not trying to model conditional duration and conditional volatility jointly. As shown in Ghysels and Jasiak (1998), modelling conditional duration and volatility jointly is technically challenging. This is due to the fact that volatility is defined over a regular sampling frequency but duration is defined over irregular time intervals. Given GARCH model is not generally closed under temporal aggregation, this creates a challenging modelling problem. The aim of this paper is to avoid this challenge by not modelling the conditional volatility, but instead, model the dynamics in the magnitudes of price change. The paper argues that since volatility is a function of the magnitudes of price change, testing the relationship between duration and the magnitude of price change provides an indirect test on the relationship between duration and volatility. The paper also obtains theoretical results for the Quasi-Maximum Likelihood Estimator (QMLE) for the proposed model. Specifically, sufficient conditions for consistency and asymptotic normality are derived under mild assumptions. Monte Carlo experiments also provide further support of the theoretical results and demonstrate that the QMLE has reasonably good finite sample performance. The paper then applies the model to nine different assets from three different asset classes, namely two exchange rate, two commodities and five stocks. The two currencies are Australia/US and British Pound/US exchange rates; the two commodities are Gold and Silver and the five stocks are BHP, Rio Tinto, CBS, ANZ and Apple. The sample spans from 4 January 2010 to 30 December 2011 with an average of 100,000 observations.","PeriodicalId":422957,"journal":{"name":"2015 Financial Markets & Corporate Governance Conference (Archive)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124094298","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 demonstrate the importance of firm-specific and industry-specific factors in the leverage decision of Australian firms. Empirical findings show that some firm-specific factors vary across industry, while prior literature assumes equal impact of these factors. In addition, we find that industry-specific factors have direct and indirect impact on the formation of capital structure of Australian firms.
{"title":"Firm and Industry Specific Determinants of Capital Structure: Evidence from Australian Market Paper","authors":"Lary Li, S. Islam","doi":"10.2139/ssrn.2557861","DOIUrl":"https://doi.org/10.2139/ssrn.2557861","url":null,"abstract":"We demonstrate the importance of firm-specific and industry-specific factors in the leverage decision of Australian firms. Empirical findings show that some firm-specific factors vary across industry, while prior literature assumes equal impact of these factors. In addition, we find that industry-specific factors have direct and indirect impact on the formation of capital structure of Australian firms.","PeriodicalId":422957,"journal":{"name":"2015 Financial Markets & Corporate Governance Conference (Archive)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124991104","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}
China’s stock market has grown rapidly since its introduction in 1991 and it has become one of the world’s leading stock markets. This study is concerned with the dependence structures that exist between the Chinese stock market and other major stock markets including those in the US, UK, Japan, Hong Kong and Taiwan. In this research, we use time-varying copula to model dependence due to its ability to capture the non-normality distribution compared to linear correlation. Furthermore, this study uses Extreme Value Theory (EVT) to model the tails for the marginal distributions. Our results reveal a strong dependence between Chinese and Hong Kong stock markets for the upper tail dependence. Lower tail dependence exists between Taiwan markets. This indicates the boom in the Chinese stock market could affect the Hong Kong one and a crash in Taiwan could potentially damage the latter. The outcomes of this cannot be explained using linear correlation. Findings also show that the Hong Kong stock market has stronger upper dependence compared to its lower tail and this serves as an alternative diversification strategy during a downturn. These findings provide better information and suggestions for risk management, specifically in portfolio diversification and international asset allocation benefits. Chinese stock market investors could use this information to devise risk management strategies.
{"title":"Modeling International Diversification between the Chinese Stock Market and Others","authors":"S. Hussain, Steven Li","doi":"10.2139/ssrn.2556623","DOIUrl":"https://doi.org/10.2139/ssrn.2556623","url":null,"abstract":"China’s stock market has grown rapidly since its introduction in 1991 and it has become one of the world’s leading stock markets. This study is concerned with the dependence structures that exist between the Chinese stock market and other major stock markets including those in the US, UK, Japan, Hong Kong and Taiwan. In this research, we use time-varying copula to model dependence due to its ability to capture the non-normality distribution compared to linear correlation. Furthermore, this study uses Extreme Value Theory (EVT) to model the tails for the marginal distributions. Our results reveal a strong dependence between Chinese and Hong Kong stock markets for the upper tail dependence. Lower tail dependence exists between Taiwan markets. This indicates the boom in the Chinese stock market could affect the Hong Kong one and a crash in Taiwan could potentially damage the latter. The outcomes of this cannot be explained using linear correlation. Findings also show that the Hong Kong stock market has stronger upper dependence compared to its lower tail and this serves as an alternative diversification strategy during a downturn. These findings provide better information and suggestions for risk management, specifically in portfolio diversification and international asset allocation benefits. Chinese stock market investors could use this information to devise risk management strategies.","PeriodicalId":422957,"journal":{"name":"2015 Financial Markets & Corporate Governance Conference (Archive)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129034675","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}
Many recent governance reforms require that a majority of directors on corporate boards should be independent, and that only independent directors should serve on firm sub-committees. We examine the efficacy of these reforms by examining how board independence affects market liquidity and price efficiency. We focus on a comprehensive sample of 239 listed firms from 2004 to 2009 and find that firms with greater board independence have narrower spreads and greater speed of adjustment to new information. Additionally, improvements in board independence over time are positively associated with improvements in firm liquidity and efficiency. The results suggest that greater board independence can lower the probability of informed trading resulting in greater liquidity provision and smaller price delay.
{"title":"Board Independence, Stock Liquidity, and Price Efficiency","authors":"Angelo Aspris, A. Frino","doi":"10.2139/ssrn.1922608","DOIUrl":"https://doi.org/10.2139/ssrn.1922608","url":null,"abstract":"Many recent governance reforms require that a majority of directors on corporate boards should be independent, and that only independent directors should serve on firm sub-committees. We examine the efficacy of these reforms by examining how board independence affects market liquidity and price efficiency. We focus on a comprehensive sample of 239 listed firms from 2004 to 2009 and find that firms with greater board independence have narrower spreads and greater speed of adjustment to new information. Additionally, improvements in board independence over time are positively associated with improvements in firm liquidity and efficiency. The results suggest that greater board independence can lower the probability of informed trading resulting in greater liquidity provision and smaller price delay.","PeriodicalId":422957,"journal":{"name":"2015 Financial Markets & Corporate Governance Conference (Archive)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124020439","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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