Pub Date : 2016-12-31DOI: 10.3905/JOT.2017.12.1.073
Marie S. Konstance
Many U.S. equity traders underestimate the value of venue analysis and assume that any issues will appear in their current TCA results. However, problems may not clearly bubble up in a post-trade report. This article provides an overview of some of the potential issues in broker venue strategy and suggests a general framework for beginning an effective analysis. The payoff from this effort can provide greater reassurance that traders are using effective algorithms or perhaps allow them to tweak their existing strategies to perform more effectively.
{"title":"Approaching Venue Analysis","authors":"Marie S. Konstance","doi":"10.3905/JOT.2017.12.1.073","DOIUrl":"https://doi.org/10.3905/JOT.2017.12.1.073","url":null,"abstract":"Many U.S. equity traders underestimate the value of venue analysis and assume that any issues will appear in their current TCA results. However, problems may not clearly bubble up in a post-trade report. This article provides an overview of some of the potential issues in broker venue strategy and suggests a general framework for beginning an effective analysis. The payoff from this effort can provide greater reassurance that traders are using effective algorithms or perhaps allow them to tweak their existing strategies to perform more effectively.","PeriodicalId":254660,"journal":{"name":"The Journal of Trading","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133004860","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}
Pub Date : 2016-09-30DOI: 10.3905/jot.2016.11.4.077
Paul Besson, Stéphanie Pelin, Matthieu Lasnier
Traders have always empirically estimated the short-term dynamic of the market. Contrary to popular belief, building a quantitative estimate of the next trade is not some sort of “Holy Grail” only accessible to the darkest high-frequency traders. In fact, this knowledge is easily understandable by anyone who observes the data attentively. Thanks to our tick database, we find that order book imbalances allow us to make reliable forecasts regarding the side (bid/ask) of the next trade; in short, on average, aggressive trades will mainly target the smallest limit (in size). We also find that aggressive trades will consume a larger share when the smaller limit is hit rather than the larger limit. Using this insight regarding the next trade enables us to estimate the risk induced by a passive posting and thereby helps to decide whether or not to cross the spread using objective criteria based on the Sharpe ratio. Similar rules can be applied to trading algorithms to help eliminate many unnecessary aggressive trades and thus significantly increase trading performances.
{"title":"To Cross or Not to Cross the Spread: That Is the Question","authors":"Paul Besson, Stéphanie Pelin, Matthieu Lasnier","doi":"10.3905/jot.2016.11.4.077","DOIUrl":"https://doi.org/10.3905/jot.2016.11.4.077","url":null,"abstract":"Traders have always empirically estimated the short-term dynamic of the market. Contrary to popular belief, building a quantitative estimate of the next trade is not some sort of “Holy Grail” only accessible to the darkest high-frequency traders. In fact, this knowledge is easily understandable by anyone who observes the data attentively. Thanks to our tick database, we find that order book imbalances allow us to make reliable forecasts regarding the side (bid/ask) of the next trade; in short, on average, aggressive trades will mainly target the smallest limit (in size). We also find that aggressive trades will consume a larger share when the smaller limit is hit rather than the larger limit. Using this insight regarding the next trade enables us to estimate the risk induced by a passive posting and thereby helps to decide whether or not to cross the spread using objective criteria based on the Sharpe ratio. Similar rules can be applied to trading algorithms to help eliminate many unnecessary aggressive trades and thus significantly increase trading performances.","PeriodicalId":254660,"journal":{"name":"The Journal of Trading","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131375635","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}
Pub Date : 2016-09-30DOI: 10.3905/jot.2016.11.4.033
Gerasimos G. Rompotis
This article examines how the recent crisis in the Chinese stock market affected U.S.-listed ETFs, which track broad market or sector indexes covering the Chinese market as well as U.S.-listed ETFs covering broad indexes of the U.S. market. The period under examination spans from mid-June 2014, i.e., one calendar year before the burst of the crisis on June 12, 2015, to the end of October 2015. Our analysis shows that the performance of both ETF groups examined—the China-oriented and the U.S.-oriented funds—was severely affected over the period of the crisis peak, spanning from June 12, 2015, to August 25, 2015. Volatility in the ETF market surged dramatically over the same period. Our analysis reveals that the linkages between the Chinese stock market and the U.S. ETF market became stronger after the burst of the crisis. However, a significant volatility transmission from the Chinese stock market to the U.S. ETF market is found both before and after the burst of the crisis.
{"title":"The Effects of the Chinese Stock Crisis on the U.S.Exchange-Traded Funds Market","authors":"Gerasimos G. Rompotis","doi":"10.3905/jot.2016.11.4.033","DOIUrl":"https://doi.org/10.3905/jot.2016.11.4.033","url":null,"abstract":"This article examines how the recent crisis in the Chinese stock market affected U.S.-listed ETFs, which track broad market or sector indexes covering the Chinese market as well as U.S.-listed ETFs covering broad indexes of the U.S. market. The period under examination spans from mid-June 2014, i.e., one calendar year before the burst of the crisis on June 12, 2015, to the end of October 2015. Our analysis shows that the performance of both ETF groups examined—the China-oriented and the U.S.-oriented funds—was severely affected over the period of the crisis peak, spanning from June 12, 2015, to August 25, 2015. Volatility in the ETF market surged dramatically over the same period. Our analysis reveals that the linkages between the Chinese stock market and the U.S. ETF market became stronger after the burst of the crisis. However, a significant volatility transmission from the Chinese stock market to the U.S. ETF market is found both before and after the burst of the crisis.","PeriodicalId":254660,"journal":{"name":"The Journal of Trading","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132750570","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}
Pub Date : 2016-09-30DOI: 10.3905/jot.2016.11.4.006
Ramon Tol
An apples-to-apples comparison of transition pre-trade analyses is not straightforward, if indeed possible. Due to fiduciary responsibilities, transition clients are inclined to provide transition managers with only high-level pre-trade portfolio characteristics instead of the actual underlying holdings to avoid information leakage. Providing portfolio characteristics leaves room for different interpretations by transition managers on the exact underlying assets involved in the transition. This issue is a major concern that causes noise in comparing pre-trades. This article presents several suggestions for reducing noise in pre-trade comparison while improving the client’s understanding of pre-trades (and comparisons.)
{"title":"Noise and How to Reduce It in Transition Management Pre-Trade Comparisons","authors":"Ramon Tol","doi":"10.3905/jot.2016.11.4.006","DOIUrl":"https://doi.org/10.3905/jot.2016.11.4.006","url":null,"abstract":"An apples-to-apples comparison of transition pre-trade analyses is not straightforward, if indeed possible. Due to fiduciary responsibilities, transition clients are inclined to provide transition managers with only high-level pre-trade portfolio characteristics instead of the actual underlying holdings to avoid information leakage. Providing portfolio characteristics leaves room for different interpretations by transition managers on the exact underlying assets involved in the transition. This issue is a major concern that causes noise in comparing pre-trades. This article presents several suggestions for reducing noise in pre-trade comparison while improving the client’s understanding of pre-trades (and comparisons.)","PeriodicalId":254660,"journal":{"name":"The Journal of Trading","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121685291","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}
Pub Date : 2016-09-30DOI: 10.3905/jot.2016.11.4.014
G. Meissner
This article gives an overview of and analyzes the most popular correlation trading strategies in financial practice. Six correlation strategies are discussed: 1) empirical correlation trading, 2) pairs trading, 3) multiasset options, 4) structured products, 5) correlation swaps, and 6) dispersion trading. Additionally, this article briefly focuses on trading correlation and outlines the risk managing properties of correlation products.
{"title":"Correlation Trading Strategies: Opportunities and Limitations","authors":"G. Meissner","doi":"10.3905/jot.2016.11.4.014","DOIUrl":"https://doi.org/10.3905/jot.2016.11.4.014","url":null,"abstract":"This article gives an overview of and analyzes the most popular correlation trading strategies in financial practice. Six correlation strategies are discussed: 1) empirical correlation trading, 2) pairs trading, 3) multiasset options, 4) structured products, 5) correlation swaps, and 6) dispersion trading. Additionally, this article briefly focuses on trading correlation and outlines the risk managing properties of correlation products.","PeriodicalId":254660,"journal":{"name":"The Journal of Trading","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132592037","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}
Pub Date : 2016-09-30DOI: 10.3905/jot.2016.11.4.001
Brian R. Bruce
{"title":"Editor’s Letter","authors":"Brian R. Bruce","doi":"10.3905/jot.2016.11.4.001","DOIUrl":"https://doi.org/10.3905/jot.2016.11.4.001","url":null,"abstract":"","PeriodicalId":254660,"journal":{"name":"The Journal of Trading","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114589137","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}
Pub Date : 2016-09-30DOI: 10.3905/jot.2016.11.4.056
Suchi Mishra, R. Daigler, R. Holowczak
The transition from manual to electronic markets in options paved the way for pricing efficiencies and improved liquidity from options high-frequency market making (HFMM). We find that HFMM reduces option bid–ask spreads, although with differences across both option and firm characteristics. Depth increases with the number of market maker quote revisions, conflicting with extant high-frequency research in other markets. The largest absolute change for spreads (depth) is for mid-size (large) companies. However, the change to penny quotes for options caused HFMM to have less of an effect on both spreads and depth, showing that penny quoting exacerbates the pricing efficiency generated by more frequent quote revisions.
{"title":"The Effect of High-Frequency Market Making on Option Market Liquidity","authors":"Suchi Mishra, R. Daigler, R. Holowczak","doi":"10.3905/jot.2016.11.4.056","DOIUrl":"https://doi.org/10.3905/jot.2016.11.4.056","url":null,"abstract":"The transition from manual to electronic markets in options paved the way for pricing efficiencies and improved liquidity from options high-frequency market making (HFMM). We find that HFMM reduces option bid–ask spreads, although with differences across both option and firm characteristics. Depth increases with the number of market maker quote revisions, conflicting with extant high-frequency research in other markets. The largest absolute change for spreads (depth) is for mid-size (large) companies. However, the change to penny quotes for options caused HFMM to have less of an effect on both spreads and depth, showing that penny quoting exacerbates the pricing efficiency generated by more frequent quote revisions.","PeriodicalId":254660,"journal":{"name":"The Journal of Trading","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122072391","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}
Pub Date : 2016-07-05DOI: 10.3905/jot.2017.12.1.005
Mohammad Sogir Hossain Khandoker, Rafiqul Bhuyan, Ranjit Singh
Implementation shortfall, originally proposed by Perold and later expanded by Wagner and Edwards and Kissell, can adversely affect portfolio performance if it is not properly managed through implementation strategy as a result of price impact, timing cost, and inability to complete total transactions. The authors further classify implementation shortfall to give traders a better understanding of opportunity cost and a method to control any or all of these costs while executing trades. They suggest that after thorough back testing, market price trend analysis, and pretrade analysis, setting price limits efficiently will ensure that the first trading–related and residual trading–related opportunity cost will be as low as possible for the trader, thus lowering overall implementation shortfall.
{"title":"Implementation Shortfall in Transaction Cost Analysis: A Further Extension","authors":"Mohammad Sogir Hossain Khandoker, Rafiqul Bhuyan, Ranjit Singh","doi":"10.3905/jot.2017.12.1.005","DOIUrl":"https://doi.org/10.3905/jot.2017.12.1.005","url":null,"abstract":"Implementation shortfall, originally proposed by Perold and later expanded by Wagner and Edwards and Kissell, can adversely affect portfolio performance if it is not properly managed through implementation strategy as a result of price impact, timing cost, and inability to complete total transactions. The authors further classify implementation shortfall to give traders a better understanding of opportunity cost and a method to control any or all of these costs while executing trades. They suggest that after thorough back testing, market price trend analysis, and pretrade analysis, setting price limits efficiently will ensure that the first trading–related and residual trading–related opportunity cost will be as low as possible for the trader, thus lowering overall implementation shortfall.","PeriodicalId":254660,"journal":{"name":"The Journal of Trading","volume":"211 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115489412","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}
Pub Date : 2016-06-30DOI: 10.3905/jot.2016.11.3.041
Wenjun Xie, Rong Qi Liew, Yuan Wu, Xi Zou
Pairs trading is a well-known speculative investment strategy, with the distance method the most commonly implemented variation. However, the profitability of this approach has decreased in recent years. This article seeks to generalize the pairs trading strategy using a copula technique to explicitly capture the marginal distributions as well as the dependency structure between the stock returns. With a better understanding of the joint distribution of the two stocks, practitioners could gain preferential entry positions and have more trading opportunities. The overall empirical results verify the proposed strategy’s ability to generate higher profits compared with the conventional distance method.
{"title":"Pairs Trading with Copulas","authors":"Wenjun Xie, Rong Qi Liew, Yuan Wu, Xi Zou","doi":"10.3905/jot.2016.11.3.041","DOIUrl":"https://doi.org/10.3905/jot.2016.11.3.041","url":null,"abstract":"Pairs trading is a well-known speculative investment strategy, with the distance method the most commonly implemented variation. However, the profitability of this approach has decreased in recent years. This article seeks to generalize the pairs trading strategy using a copula technique to explicitly capture the marginal distributions as well as the dependency structure between the stock returns. With a better understanding of the joint distribution of the two stocks, practitioners could gain preferential entry positions and have more trading opportunities. The overall empirical results verify the proposed strategy’s ability to generate higher profits compared with the conventional distance method.","PeriodicalId":254660,"journal":{"name":"The Journal of Trading","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131767311","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}
Pub Date : 2016-06-30DOI: 10.3905/jot.2016.11.3.001
Brian R. Bruce
DaviD anTin CEO Dave BliDe Publisher We open the Summer issue with Blocher, Cooper, Seddon, and Van Vliet’s examination of every NASDAQ ITCH feed message for the S&P 500 Index stocks for 2012. Their f indings shed light on the behavior of high-frequency trades surrounding high levels of cancellation activity. Li studies how stock prices incorporate information in after-hours trading and f inds slow price adjustment that persists under various levels of investor inattention, limited arbitrage capital, and short-sale constraints. Madhavan, Laipply, and Sobczyk illustrate how investors and traders can use intraday estimates as a complement to existing data (such as end-of-day net asset value) to better understand the underlying bond portfolio value during the trading day and for transaction cost analysis. Xie, Liew, Wu, and Zou apply the pairs trading strategy using a copula technique to explicitly capture the marginal distributions as well as the dependency structure between the stock returns. They propose that with a better understanding of the joint distribution of the two stocks, practitioners could gain preferential entry positions and have more trading opportunities. Next, Jha demonstrates a simple tactical trade timing strategy that allows a long-horizon manager to take advantage of short-horizon alphas without incurring additional transaction costs. Zhang, Tang, Prombutr, and Le present findings from their investigation of pre-event trading behaviors and investment returns surrounding Value Line’s Timeliness rank-change announcements. We conclude the issue with Kashyap’s utilization of a fundamentally different model of trading costs to look at the effect of the opening of the Hong Kong–Shanghai Connect, which links the stock exchanges in the two cities. As always, we welcome your submissions. We value your comments and suggestions, so please email us at journals@investmentresearch.org.
我们以Blocher, Cooper, Seddon和Van Vliet对2012年标准普尔500指数股票的纳斯达克ITCH feed消息的检查作为夏季问题的开始。他们的发现揭示了围绕高水平取消活动的高频交易行为。李研究了股票价格如何在盘后交易中纳入信息，并发现在不同程度的投资者不注意、有限的套利资本和卖空限制下，价格调整持续缓慢。Madhavan、Laipply和Sobczyk说明了投资者和交易者如何使用日内估值作为现有数据(如日末资产净值)的补充，以更好地了解交易日内潜在债券投资组合的价值，并进行交易成本分析。Xie, Liew, Wu, and Zou运用配对交易策略，使用copula技术来明确捕获边际分布以及股票收益之间的依赖结构。他们提出，通过更好地了解两股的共同分布，从业者可以获得优先的入场位置，并有更多的交易机会。接下来，Jha演示了一个简单的战术交易时机策略，该策略允许长线经理在不产生额外交易成本的情况下利用短线阿尔法。Zhang、Tang、Prombutr和Le对围绕Value Line的及时性排名变动公告的事前交易行为和投资回报进行了调查。我们用卡什亚普使用一个完全不同的交易成本模型来总结这个问题，以观察连接两个城市证券交易所的沪港通开通的影响。一如既往，我们欢迎您的投稿。我们非常重视您的意见和建议，所以请给我们发邮件至journals@investmentresearch.org。
{"title":"Editor’s Letter","authors":"Brian R. Bruce","doi":"10.3905/jot.2016.11.3.001","DOIUrl":"https://doi.org/10.3905/jot.2016.11.3.001","url":null,"abstract":"DaviD anTin CEO Dave BliDe Publisher We open the Summer issue with Blocher, Cooper, Seddon, and Van Vliet’s examination of every NASDAQ ITCH feed message for the S&P 500 Index stocks for 2012. Their f indings shed light on the behavior of high-frequency trades surrounding high levels of cancellation activity. Li studies how stock prices incorporate information in after-hours trading and f inds slow price adjustment that persists under various levels of investor inattention, limited arbitrage capital, and short-sale constraints. Madhavan, Laipply, and Sobczyk illustrate how investors and traders can use intraday estimates as a complement to existing data (such as end-of-day net asset value) to better understand the underlying bond portfolio value during the trading day and for transaction cost analysis. Xie, Liew, Wu, and Zou apply the pairs trading strategy using a copula technique to explicitly capture the marginal distributions as well as the dependency structure between the stock returns. They propose that with a better understanding of the joint distribution of the two stocks, practitioners could gain preferential entry positions and have more trading opportunities. Next, Jha demonstrates a simple tactical trade timing strategy that allows a long-horizon manager to take advantage of short-horizon alphas without incurring additional transaction costs. Zhang, Tang, Prombutr, and Le present findings from their investigation of pre-event trading behaviors and investment returns surrounding Value Line’s Timeliness rank-change announcements. We conclude the issue with Kashyap’s utilization of a fundamentally different model of trading costs to look at the effect of the opening of the Hong Kong–Shanghai Connect, which links the stock exchanges in the two cities. As always, we welcome your submissions. We value your comments and suggestions, so please email us at journals@investmentresearch.org.","PeriodicalId":254660,"journal":{"name":"The Journal of Trading","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129874472","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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