Martin D. D. Evans, Peter O’Neill, Dagfinn Rime, J. Saakvitne
We examine the design and effectiveness of the 4pm Fix, the most important benchmark in FX markets, using a unique dataset of trader identified order book data from an inter- dealer venue. We propose and examine new measures of benchmark quality and examine changes to market liquidity and trader behaviour. Benchmark quality, measured as price efficiency and robustness, improves after the lengthening of the fix window to 5 minutes, but comes at the cost of a significant increase in tracking error for users of the benchmark. We also find that quoted spreads and price impact increase following the window lengthening, with HFTs trading more aggressively during the fix.
{"title":"Fixing the Fix? Assessing the Effectiveness of the 4pm Fix Benchmark","authors":"Martin D. D. Evans, Peter O’Neill, Dagfinn Rime, J. Saakvitne","doi":"10.2139/ssrn.3270844","DOIUrl":"https://doi.org/10.2139/ssrn.3270844","url":null,"abstract":"We examine the design and effectiveness of the 4pm Fix, the most important benchmark in FX markets, using a unique dataset of trader identified order book data from an inter- dealer venue. We propose and examine new measures of benchmark quality and examine changes to market liquidity and trader behaviour. Benchmark quality, measured as price efficiency and robustness, improves after the lengthening of the fix window to 5 minutes, but comes at the cost of a significant increase in tracking error for users of the benchmark. We also find that quoted spreads and price impact increase following the window lengthening, with HFTs trading more aggressively during the fix.","PeriodicalId":295985,"journal":{"name":"Financial Conduct Authority Research Paper Series","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127631343","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}
Michael S. Barr, Brian Koziara, Mark D. Flood, A. Hero, H. Jagadish
How can financial data be made more accessible and more secure, as well as more useful to regulators, market participants, and the public? As new data sets are created, opportunities emerge. Vast quantities of financial data may help identify emerging risks, enable market participants and regulators to see and better understand financial networks and interconnections, enhance financial stability, bolster consumer protection, and increase access to the underserved. Data can also increase transparency in the financial system for market participants, regulators and the public. These data sets, however, can raise significant questions about security and privacy; ensuring data quality; protecting against discrimination or privacy intrusions; managing, synthesizing, presenting, and analyzing data in usable form; and sharing data among regulators, researchers, and the public. Moreover, any conflicts among regulators and financial firms over such data could create opportunities for regulatory arbitrage and gaps in understanding risk in the financial system. The Big Data in Finance Conference, co-sponsored by the federal Office of Financial Research and the University of Michigan Center on Finance, Law, and Policy, and held at the University of Michigan Law School on October 27-28, 2016, covered a number of important and timely topics in the worlds of Big Data and finance. This paper highlights several key issues and conference takeaways as originally presented by the contributors and panelists who took part.
{"title":"Big Data in Finance: Highlights from the Big Data in Finance Conference Hosted at the University of Michigan October 27-28, 2016","authors":"Michael S. Barr, Brian Koziara, Mark D. Flood, A. Hero, H. Jagadish","doi":"10.2139/SSRN.3131226","DOIUrl":"https://doi.org/10.2139/SSRN.3131226","url":null,"abstract":"How can financial data be made more accessible and more secure, as well as more useful to regulators, market participants, and the public? As new data sets are created, opportunities emerge. Vast quantities of financial data may help identify emerging risks, enable market participants and regulators to see and better understand financial networks and interconnections, enhance financial stability, bolster consumer protection, and increase access to the underserved. Data can also increase transparency in the financial system for market participants, regulators and the public. These data sets, however, can raise significant questions about security and privacy; ensuring data quality; protecting against discrimination or privacy intrusions; managing, synthesizing, presenting, and analyzing data in usable form; and sharing data among regulators, researchers, and the public. Moreover, any conflicts among regulators and financial firms over such data could create opportunities for regulatory arbitrage and gaps in understanding risk in the financial system. \u0000The Big Data in Finance Conference, co-sponsored by the federal Office of Financial Research and the University of Michigan Center on Finance, Law, and Policy, and held at the University of Michigan Law School on October 27-28, 2016, covered a number of important and timely topics in the worlds of Big Data and finance. This paper highlights several key issues and conference takeaways as originally presented by the contributors and panelists who took part.","PeriodicalId":295985,"journal":{"name":"Financial Conduct Authority Research Paper Series","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123993072","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：