Pub Date : 2008-02-01DOI: 10.1016/J.SOCEC.2006.12.032
Neil H. Buchanan
{"title":"How Realistic is the Supply/Demand Equilibrium Story? A Simple Demonstration of False Trading and its Implications for Market Equilibrium","authors":"Neil H. Buchanan","doi":"10.1016/J.SOCEC.2006.12.032","DOIUrl":"https://doi.org/10.1016/J.SOCEC.2006.12.032","url":null,"abstract":"","PeriodicalId":447775,"journal":{"name":"Capital Markets: Market Microstructure","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"118375057","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}
Dufour and Engle (J. Finance (2000) 2467) find evidence of increased presence of informed traders when the NYSE markets are most active. No such evidence, however, can be found by Manganelli (J. Financial Markets (2005) 377) for the infrequently traded stocks. This article investigates the issue of informed trading and its relation to liquidity in Shanghai Stock Exchange. Consistent with the hypothesis that information-based trade exists for all stocks, our findings suggest an increased presence of informed trading in both liquid and illiquid stocks when markets are active. Moreover, for the actively traded stocks, our results support the price formation model of Foster and Viswanathan (Rev. Financial Studies (1990) 593) that activities of informed traders deter uninformed investors from trading, thereby reducing market liquidity.
{"title":"Informed Trading and Liquidity in the Shanghai Stock Exchange","authors":"W. Wong, Di-jun Tan, Yixiang Tian","doi":"10.2139/ssrn.1084794","DOIUrl":"https://doi.org/10.2139/ssrn.1084794","url":null,"abstract":"Dufour and Engle (J. Finance (2000) 2467) find evidence of increased presence of informed traders when the NYSE markets are most active. No such evidence, however, can be found by Manganelli (J. Financial Markets (2005) 377) for the infrequently traded stocks. This article investigates the issue of informed trading and its relation to liquidity in Shanghai Stock Exchange. Consistent with the hypothesis that information-based trade exists for all stocks, our findings suggest an increased presence of informed trading in both liquid and illiquid stocks when markets are active. Moreover, for the actively traded stocks, our results support the price formation model of Foster and Viswanathan (Rev. Financial Studies (1990) 593) that activities of informed traders deter uninformed investors from trading, thereby reducing market liquidity.","PeriodicalId":447775,"journal":{"name":"Capital Markets: Market Microstructure","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126047159","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}
In the light of recent evidence that liquidity and idiosyncratic risk may be priced factors in the cross section of expected stock returns and that market capitalization significantly affects investor behavior and liquidity, we explore the interactions between liquidity, idiosyncratic risk and return across time as well as across size-based portfolios of stocks listed in the London Stock Exchange. In a Vector Autoregressive (VAR) analytical framework, we find that volatility spills over from large cap stocks to small cap stocks and vice versa. Volatility shocks can be predicted by illiquidity shocks in both large cap as well as in the small cap portfolios. Illiquidity can be predicted by return shocks in small cap stocks. Finally, we document some evidence of asymmetric liquidity spillovers, from large cap stocks to small cap ones, supporting the intuition that common information is first incorporated in the trading behavior of large-cap investors and the liquidity of large cap stocks and is then transmitted in the trading of small stocks.
{"title":"Idiosyncratic Risk, Returns and Liquidity in the London Stock Exchange: A Spillover Approach","authors":"A. Andrikopoulos, Timotheos Angelidis","doi":"10.2139/ssrn.1083997","DOIUrl":"https://doi.org/10.2139/ssrn.1083997","url":null,"abstract":"In the light of recent evidence that liquidity and idiosyncratic risk may be priced factors in the cross section of expected stock returns and that market capitalization significantly affects investor behavior and liquidity, we explore the interactions between liquidity, idiosyncratic risk and return across time as well as across size-based portfolios of stocks listed in the London Stock Exchange. In a Vector Autoregressive (VAR) analytical framework, we find that volatility spills over from large cap stocks to small cap stocks and vice versa. Volatility shocks can be predicted by illiquidity shocks in both large cap as well as in the small cap portfolios. Illiquidity can be predicted by return shocks in small cap stocks. Finally, we document some evidence of asymmetric liquidity spillovers, from large cap stocks to small cap ones, supporting the intuition that common information is first incorporated in the trading behavior of large-cap investors and the liquidity of large cap stocks and is then transmitted in the trading of small stocks.","PeriodicalId":447775,"journal":{"name":"Capital Markets: Market Microstructure","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129828003","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}
The desire to hire the best athletes and coaches in order to maximize team performance necessitates generous compensation contracts, which in turn increase the risk of financial distress or even bankruptcy for team owners. Indeed, one of the largest expense items in the budget of professional sport teams is the remuneration of players and coaches. Yet an investment made today in a given team yields an uncertain income in the future, as team profitability depends on the (uncertain) performance of each player and the synchronization among players - both influenced by the coach. We present a formal theoretical model that assesses athletes' valuation, accounting for the abovementioned factors. The optimal compensation schedule is determined empirically by regressing expected performance measures of each player with the aggregate team performance. Once the optimal schedule has been determined, the expected rate of return for the owner is earned at the lowest possible risk.
{"title":"The Valuation of Athletes as Risky Investments: A Theoretical Model","authors":"Haim Kedar-Levy, Michael Bar Eli","doi":"10.1123/JSM.22.1.50","DOIUrl":"https://doi.org/10.1123/JSM.22.1.50","url":null,"abstract":"The desire to hire the best athletes and coaches in order to maximize team performance necessitates generous compensation contracts, which in turn increase the risk of financial distress or even bankruptcy for team owners. Indeed, one of the largest expense items in the budget of professional sport teams is the remuneration of players and coaches. Yet an investment made today in a given team yields an uncertain income in the future, as team profitability depends on the (uncertain) performance of each player and the synchronization among players - both influenced by the coach. We present a formal theoretical model that assesses athletes' valuation, accounting for the abovementioned factors. The optimal compensation schedule is determined empirically by regressing expected performance measures of each player with the aggregate team performance. Once the optimal schedule has been determined, the expected rate of return for the owner is earned at the lowest possible risk.","PeriodicalId":447775,"journal":{"name":"Capital Markets: Market Microstructure","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131159181","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}
Liquidity providers on the NYSE make faster quote adjustments towards equilibrium spreads and depths than they do on NASDAQ. Liquidity providers in both markets make faster spread and depth adjustments for stocks with more frequent trading, greater return volatility, higher prices, smaller market capitalizations, and smaller trade sizes. We find that stocks with greater information-based trading and in more competitive trading environments exhibit faster quote adjustments. The speed of quote adjustment is faster after decimalization in both markets. These results are robust and not driven by differences in stock attributes between the two markets or time periods. Overall, our results indicate that stock attributes, market structure, and tick size exert a significant impact on the speed of quote adjustment.
{"title":"The Dynamics of Quote Adjustments","authors":"Kee H. Chung, Chairat Chuwonganant, Jing Jiang","doi":"10.2139/ssrn.1078800","DOIUrl":"https://doi.org/10.2139/ssrn.1078800","url":null,"abstract":"Liquidity providers on the NYSE make faster quote adjustments towards equilibrium spreads and depths than they do on NASDAQ. Liquidity providers in both markets make faster spread and depth adjustments for stocks with more frequent trading, greater return volatility, higher prices, smaller market capitalizations, and smaller trade sizes. We find that stocks with greater information-based trading and in more competitive trading environments exhibit faster quote adjustments. The speed of quote adjustment is faster after decimalization in both markets. These results are robust and not driven by differences in stock attributes between the two markets or time periods. Overall, our results indicate that stock attributes, market structure, and tick size exert a significant impact on the speed of quote adjustment.","PeriodicalId":447775,"journal":{"name":"Capital Markets: Market Microstructure","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125202887","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 shows that the market reaction to a trade depends on the identity of the broker initiating the trade, controlling for the known determinants of the permanent price impact. I combine microstructure data with investor trading records to reconstruct brokers' customer bases and to examine broker heterogeneity. I find that informed traders are more likely to trade through certain types of brokers and that the market uses all trade characteristics jointly to make inferences about the probability that a trade originates from an informed trader. The permanent price impact of a trade is decreasing in the household-intensity of a broker, indicating that the market perceives households to be trading less frequently on private information. Trade characteristics also matter when they deviate from the historical norm: an unusual trade from a retail broker generates a higher price impact than what it would generate if the trade originated from an institutional broker.
{"title":"Does it Matter Who Trades? Broker Identities and the Information Content of Stock Trades","authors":"Juhani T. Linnainmaa","doi":"10.2139/ssrn.972777","DOIUrl":"https://doi.org/10.2139/ssrn.972777","url":null,"abstract":"This paper shows that the market reaction to a trade depends on the identity of the broker initiating the trade, controlling for the known determinants of the permanent price impact. I combine microstructure data with investor trading records to reconstruct brokers' customer bases and to examine broker heterogeneity. I find that informed traders are more likely to trade through certain types of brokers and that the market uses all trade characteristics jointly to make inferences about the probability that a trade originates from an informed trader. The permanent price impact of a trade is decreasing in the household-intensity of a broker, indicating that the market perceives households to be trading less frequently on private information. Trade characteristics also matter when they deviate from the historical norm: an unusual trade from a retail broker generates a higher price impact than what it would generate if the trade originated from an institutional broker.","PeriodicalId":447775,"journal":{"name":"Capital Markets: Market Microstructure","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123179696","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 report charts the history of the Quantitative Methods in Finance (QMF) conference from its beginning in 1993 to the 15th conference in 2007. It lists alphabetically the 1037 speakers who presented at all 15 conferences and the titles of their papers.
{"title":"The History of the Quantitative Methods in Finance Conference Series 1992-2007","authors":"C. Chiarella, E. Platen","doi":"10.2139/SSRN.1106031","DOIUrl":"https://doi.org/10.2139/SSRN.1106031","url":null,"abstract":"This report charts the history of the Quantitative Methods in Finance (QMF) conference from its beginning in 1993 to the 15th conference in 2007. It lists alphabetically the 1037 speakers who presented at all 15 conferences and the titles of their papers.","PeriodicalId":447775,"journal":{"name":"Capital Markets: Market Microstructure","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116799285","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 propose a unified framework for estimating integrated variances and covariances based on simple OLS regressions, allowing for a general market microstructure noise specification. We show that our estimators can outperform, in terms of the root mean squared error criterion, the most recent and commonly applied estimators, such as the realized kernels of Barndorff-Nielsen, Hansen, Lunde & Shephard (2006), the two-scales realized variance of Zhang, Mykland & Ait-Sahalia (2005), the Hayashi & Yoshida (2005) covariance estimator, and the realized variance and covariance with the optimal sampling frequency derived in Bandi & Russell (2005a) and Bandi & Russell (2005b). For a realistic trading scenario, the efficiency gains resulting from our approach are in the range of 35% to 50%.
{"title":"Estimating High-Frequency Based (Co-) Variances: A Unified Approach","authors":"Ingmar Nolte, Valeri Voev","doi":"10.2139/ssrn.1003201","DOIUrl":"https://doi.org/10.2139/ssrn.1003201","url":null,"abstract":"We propose a unified framework for estimating integrated variances and covariances based on simple OLS regressions, allowing for a general market microstructure noise specification. We show that our estimators can outperform, in terms of the root mean squared error criterion, the most recent and commonly applied estimators, such as the realized kernels of Barndorff-Nielsen, Hansen, Lunde & Shephard (2006), the two-scales realized variance of Zhang, Mykland & Ait-Sahalia (2005), the Hayashi & Yoshida (2005) covariance estimator, and the realized variance and covariance with the optimal sampling frequency derived in Bandi & Russell (2005a) and Bandi & Russell (2005b). For a realistic trading scenario, the efficiency gains resulting from our approach are in the range of 35% to 50%.","PeriodicalId":447775,"journal":{"name":"Capital Markets: Market Microstructure","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124564220","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}
The GM and Ford downgrade to junk status during May 2005 caused a wide-spread sell-off in their corporate bonds. Using a novel dataset, we document that this sell-off appears to have generated significant liquidity risk for market-makers, as evidenced in the significant imbalance in their quotes towards sales. We also document that simultaneously, there was excess co-movement in the fixed-income securities of all industries, not just in those of auto firms. In particular, using credit-default swaps (CDS) data, we find a substantial increase in the co-movement between innovations in the CDS spreads of GM and Ford and those of firms in all other industries, the increase being greatest during the period surrounding the actual downgrade and reversing sharply thereafter. We show that a measure of liquidity risk faced by corporate bond market-makers - specifically, the imbalance towards sales in the volume and frequency of quotes on GM and Ford bonds - explains a significant portion of this excess co-movement. Additional robustness checks suggest that this relationship between the liquidity risk faced by market-makers and the correlation risk for other securities in which they make markets was likely causal. Overall, the evidence is supportive of theoretical models which imply that funding liquidity risk faced by financial intermediaries is a determinant of market prices during stress times.
{"title":"Liquidity Risk and Correlation Risk: A Clinical Study of the General Motors and Ford Downgrade of May 2005","authors":"V. Acharya, S. Schaefer, Yili Zhang","doi":"10.2139/ssrn.1074783","DOIUrl":"https://doi.org/10.2139/ssrn.1074783","url":null,"abstract":"The GM and Ford downgrade to junk status during May 2005 caused a wide-spread sell-off in their corporate bonds. Using a novel dataset, we document that this sell-off appears to have generated significant liquidity risk for market-makers, as evidenced in the significant imbalance in their quotes towards sales. We also document that simultaneously, there was excess co-movement in the fixed-income securities of all industries, not just in those of auto firms. In particular, using credit-default swaps (CDS) data, we find a substantial increase in the co-movement between innovations in the CDS spreads of GM and Ford and those of firms in all other industries, the increase being greatest during the period surrounding the actual downgrade and reversing sharply thereafter. We show that a measure of liquidity risk faced by corporate bond market-makers - specifically, the imbalance towards sales in the volume and frequency of quotes on GM and Ford bonds - explains a significant portion of this excess co-movement. Additional robustness checks suggest that this relationship between the liquidity risk faced by market-makers and the correlation risk for other securities in which they make markets was likely causal. Overall, the evidence is supportive of theoretical models which imply that funding liquidity risk faced by financial intermediaries is a determinant of market prices during stress times.","PeriodicalId":447775,"journal":{"name":"Capital Markets: Market Microstructure","volume":"52 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131451468","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}
Paul Irvine, M. Goldstein, Eugene Kandel, Z. Wiener
The institutional brokerage industry faces an ever-increasing pressure to lower trading costs, which has already driven down average commissions and shifted volume toward low-cost execution venues. However, traditional full-service brokers that bundle execution with services remain a force and their commissions are still considerably higher than the marginal cost of trade execution. We hypothesize that commissions constitute a convenient way of charging a prearranged fixed fee for long-term access to a broker's premium services. We derive testable predictions based on this hypothesis and test them on a large sample of institutional trades from 1999 to 2003. We find that institutions negotiate commissions infrequently, and thus commissions vary little with trade characteristics. Institutions also concentrate their order flow with a relatively small set of brokers, with smaller institutions concentrating their trading more than large institutions and paying higher per-share commissions. These results are stable over time, are consistent with our predictions, and cannot be explained by cost-minimization alone. Finally, we discuss the evolution of the institutional brokerage market within the proposed framework and make informal predictions about future developments in the industry. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.
{"title":"Brokerage Commissions and Institutional Trading Patterns","authors":"Paul Irvine, M. Goldstein, Eugene Kandel, Z. Wiener","doi":"10.2139/ssrn.528288","DOIUrl":"https://doi.org/10.2139/ssrn.528288","url":null,"abstract":"The institutional brokerage industry faces an ever-increasing pressure to lower trading costs, which has already driven down average commissions and shifted volume toward low-cost execution venues. However, traditional full-service brokers that bundle execution with services remain a force and their commissions are still considerably higher than the marginal cost of trade execution. We hypothesize that commissions constitute a convenient way of charging a prearranged fixed fee for long-term access to a broker's premium services. We derive testable predictions based on this hypothesis and test them on a large sample of institutional trades from 1999 to 2003. We find that institutions negotiate commissions infrequently, and thus commissions vary little with trade characteristics. Institutions also concentrate their order flow with a relatively small set of brokers, with smaller institutions concentrating their trading more than large institutions and paying higher per-share commissions. These results are stable over time, are consistent with our predictions, and cannot be explained by cost-minimization alone. Finally, we discuss the evolution of the institutional brokerage market within the proposed framework and make informal predictions about future developments in the industry. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.","PeriodicalId":447775,"journal":{"name":"Capital Markets: Market Microstructure","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122895198","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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