Ian Domowitz (Investment Technology Group, New York)
Tales of Liquidity, Cost, and Volatility in the FX Market
We develop measures of the cost of liquidity in the FX market. This is a necessary step in the construction of pre-trade tools and an essential input to the evaluation of transaction costs on a post-trade basis. We begin by quantifying that cost. The results of our methodology, based on tradable quotes from multiple sources, are examined and applied in several ways. The first involves the question, what is the range of costs associated with equity-linked transactions? A second is to judge the effectiveness of indicative quotes, commonly used in studies, with respect to the level of the quote stream and how it varies over time. We also illustrate the use of cost and volatility analytics by examining trading activity during the 2014 FIFA World Cup, in the same spirit as an equity study by the European Central Bank for the 2010 games.
Ian Domowitz is the CEO of ITG Solutions Network, Inc. and a Managing Director at ITG, Inc. Prior to joining the company in 2001, he served as the Mary Jean and Frank P. Smeal Professor of Finance at Pennsylvania State University and previously was the Household International Research Professor of Economics at Northwestern University. A former member of the NASD’s Bond Market Transparency Committee, he also served as chair of the Economic Advisory Board of the NASD. Mr. Domowitz has held positions with Northwestern’s Kellogg Graduate School of Management, Columbia University, the Commodity Futures Trading Commission, the International Monetary Fund and the World Bank. He is currently a Fellow of the Program in the Law and Economics of Capital Markets at Columbia University.
Doyne Farmer (University of Oxford)
Network Effects and Dynamics of Systemic Risk
Systemic risk in financial markets is transmitted by dynamical feedbacks, often through networks. I will discuss several simple models for the leverage cycle that show how leverage targeting induces systemic risk. In one model we show that it produces clustered volatility and fat tails similar to those observed in financial markets, in another we show that Basel II plus high leverage is sufficient to cause price dynamics very similar to the Great Moderation and the subsequent crisis. Finally I will discuss preliminary results in a model for how investment crowding transmits contagion.
J. Doyne Farmer is Director of the Complexity Economics program at the Institute for New Economic Thinking at the Oxford Martin School, Professor in the Mathematical Institute at the University of Oxford, and an External Professor at the Santa Fe Institute. His current research is in economics, including agent-based modeling, financial instability and technological progress. He was a founder of Prediction Company, a quantitative automated trading firm that was sold to the United Bank of Switzerland in 2006. His past research includes complex systems, dynamical systems theory, time series analysis and theoretical biology. During the eighties he was an Oppenheimer Fellow and the founder of the Complex Systems Group at Los Alamos National Laboratory. While a graduate student in the 70’s he build the first wearable digital computer, which was successfully used to predict the game of roulette.
Robert Almgren (Quantitative Brokers and NYU)
Electronic Trading in US Treasury Market
The market for US Treasury securities is undergoing a transformation, as electronic and high-speed trading displace traditional dealer roles. Because of the size of this market, and its importance as an interest rate benchmark for many other traded products, its structure has attracted a lot of attention from regulators as well as market participants. We will outline the changes happening in this market, and the quantitative and microstructural issues raised by its unique nature.
Robert Almgren, co-founder and Head of Research at Quantitative Brokers, providing agency algorithmic trade execution and transaction cost measurement in US Treasury notes and bonds, as well as a broad range of futures products. Until 2008, Dr Almgren was a Managing Director and Head of Quantitative Strategies in the Electronic Trading Services group of Bank of America. Before that, he was a professor of mathematics at the University of Chicago and the University of Toronto, directing graduate programs in financial mathematics at both universities. Dr. Almgren holds a Ph.D. in Applied and Computational Mathematics from Princeton University. He has an extensive research record in applied mathematics, including papers on optimal trading, transaction cost measurement, and portfolio construction. He is a Fellow in the Mathematics in Finance Program at New York University, and an adjunct instructor in the Master of Science in Computational Finance at Carnegie Mellon University.
Alvaro Cartea (University College London)
Foreign Exchange Markets with Last Look
We examine the Foreign Exchange (FX) spot price spreads with and without Last Look on the transaction. We assume that brokers are risk-neutral and they quote spreads so that losses to latency arbitrageurs (LAs) are recovered from other traders in the FX market. These losses are reduced if the broker can reject, ex-post, loss-making trades by enforcing the Last Look option which is a feature of some trading venues in FX markets. For a given rejection threshold the risk-neutral broker quotes a spread to the market so that her expected profits are zero. When there is only one venue, we find that the Last Look option reduces quoted spreads. However, if there are two venues we show that the market reaches an equilibrium where traders have no incentive to migrate. The equilibrium can be reached with both venues coexisting, or with only one venue surviving. Moreover, when one venue enforces Last Look and the other one does not, counterintuitively, it may be the case that the Last Look venue quotes larger spreads.
Álvaro Cartea is joining the Department of Mathematics at the University of Oxford in January 2016. Currently, he is a Reader in Financial Mathematics at University College London. Before joining UCL he was Associate Professor of Finance at Universidad Carlos III, Madrid-Spain (2009-2012) and from 2002 until 2009 Álvaro was a Lecturer (with tenure) in the School of Economics, Mathematics and Statistics at Birkbeck-University of London. He was previously JP Morgan Lecturer in Financial Mathematics, Exeter College, University of Oxford. At Birkbeck he founded the Commodities Finance Centre and taught graduate courses in Financial Economics and Financial Mathematics. Álvaro obtained his Doctorate from the University of Oxford in 2003.
Umut Cetin (London School of Economics)
Risk Averse Market Makers and Asymmetric Information
We analyse the equilibrium impact of market makers’ risk aversion on the equilibrium in a speculative market consisting of a risk neutral informed trader and noise traders. The unwillingness of market makers to bear risk causes the informed trader to absorb large shocks in their inventories. The informed trader’s optimal strategy is to drive the market price to its fundamental value while disguising her trades as the ones of an uninformed strategic trader. This results in a mean reverting demand and price reversal. We also find that an increase in risk aversion leads to lower market depth, less efficient prices, stronger price reversal and slower convergence to fundamental value. The endogenous value of private information, however, is non-monotonic in risk aversion. Joint work with A. Danilova.
Umut Çetin obtained his PhD in Applied Mathematics at Cornell University in 2003. After spending a year of post-doctoral studies at Vienna University of Technology within the research team led by Walter Schachermayer he was appointed as Assistant Professor in Statistics at the London School of Economics. He is currently an Associate Professor at the same institution. His primary area of research is market microstructure theory. In a series of joint works with multiple co-authors, Çetin has developed a theory for a certain type of conditioning for Markov Processes, which is essential in establishing the existence of equilibrium in a class of market microstructure models.
Rama Cont (Imperial College London)
Algorithmic Trading and Intraday Market Dynamics
“Optimal execution” algorithms are typically derived assuming an exogenous price process which is unaffected by the trading behavior of market participants. On the other hand, intraday price behavior in electronic markets reveals evidence of the price impact of algorithmic order flow, an extreme example being the ‘Flash Crashes’ repeatedly observed in such markets. We propose a simple model for analyzing the feedback effects which arise in a market where participants attempt to minimize the impact of their trade execution. We show that widely used execution algorithms which aim at reducing market impact of trades can actually lead to unintended synchronization of participants’ order flows, increase their market impact and generate large « self-exciting » intraday swings in volume and volatility. These bursts are shown to occur even in absence of large orders, and lead to a systematic underperformance of ‘optimal execution’ strategies. These results call for a critical assessment of “optimal execution” algorithms and point to a notion of order flow toxicity which is distinct from information asymmetry and adverse selection.
Rama Cont is Professor of Mathematics at Imperial College London, where he holds holds the Chair of Mathematical Finance, Director of the CFM-Imperial Institute of Quantitative Finance, partner at Finance Concepts LLC and Scientific advisor to Norges Bank, the central bank of Norway. His research focuses on stochastic processes and mathematical modeling in finance, in particular the modeling of extreme market risks: market discontinuities, extreme risks, endogenous risk and systemic risk. He has co-authored the highly cited monograph Financial Modelling with Jump Processes (2003) and is the Editor-in-Chief of the Encyclopedia of Quantitative Finance (Wiley 2010). Prof. Cont was awarded the Louis Bachelier Prize by the French Academy of Sciences in 2010 for his research on mathematical modeling in finance.
Ioanid Rosu (HEC Paris)
Fast and Slow Informed Trading
This paper develops a model in which traders receive a stream of private signals, and differ in their information processing speed. In equilibrium, the fast traders (FTs) quickly reveal a large fraction of their information, and generate most of the volume, volatility and profits in the market. If a FT is averse to holding inventory, his optimal strategy changes considerably as his aversion crosses a threshold. He no longer takes long-term bets on the asset value, gets most of his profits in cash, and generates a “hot potato” effect: after trading on information, the FT quickly unloads part of his inventory to slower traders. The results match evidence about high frequency traders.
Ioanid Rosu is currently Associate Professor of Finance at HEC Paris. He received two PhDs, one in mathematics in 1999 and one in financial economics in 2004, both from MIT. His research focuses on the liquidity of financial markets and its effect on asset prices and investor decisions. Recently, he has written several papers on High Frequency Trading and its effect on market quality. His work has appeared in the Journal of Finance, Review of Financial Studies and elsewhere. He is an Associate Editor of the Journal of Financial Markets.
Andrei Kirilenko (Imperial College London)
Latency and Asset Prices
We measure message processing time or latency inside an automated trading platform. We show that latency is a random variable that has a strong predictive power over both volatility and the volatility of volatility of a highly liquid asset over and above changes in message traffic. We argue that in automated markets, processing time contains valuable nontrade information about the price formation process. We recommend that automated trading platforms improve pre-trade price transparency by reporting characteristics of latency to market participants on an ongoing basis along with order book events, transaction prices, and trading volume.
Andrei Kirilenko is a Visiting Professor of Finance at the Brevan Howard Centre for Financial Analysis at the Imperial College Business School. Prior to joining Imperial in August 2015, he was Professor of the Practice of Finance at MIT Sloan and Co-Director of the MIT Center for Finance and Policy. Professor Kirilenko’s work focuses on the intersection of finance, technology and regulation. He is a recognized world expert on high frequency and algorithmic trading. He is also an intellectual leader on the principles of regulation of automated financial markets. Before MIT Sloan, Professor Kirilenko served as chief economist of the U.S. Commodity Futures Trading Commission (CFTC) between December 2010 and December 2012. In his capacity as chief economist, Kirilenko has been instrumental in using modern analytical tools and methods to improve the Commission’s ability to develop and enforce an effective regulatory regime in automated financial markets. In 2010, Kirilenko was the recipient of the CFTC Chairman’s Award for Excellence (highest honor). Prior to joining the CFTC, Kirilenko spent twelve years at the International Monetary Fund working on global capital markets issues. His scholarly work has appeared in a number of peer-refereed journals and received multiple best-paper awards. Kirilenko received his PhD in Economics from the University of Pennsylvania, where he specialized in Finance.
Emmanuel Bacry (Ecole Polytechnique, Paris)
Estimation of Hawkes Kernels of High-Frequency Dynamics
Multivariate Hawkes processes are used to reveal high-frequency dynamics of financial time-series. We use a new modified non-parametric estimation procedure that is able to estimate faithfully power-law decreasing kernels over 7 decades (from 10 micro-seconds up to 100 seconds). We propose an 8-dimensional Hawkes model for all events associated with the first level of some asset order book. Applying our estimation procedure to this model, allows us to uncover the main properties of the coupled dynamics of trade, limit and cancel orders in relationship with the mid-price variations.
Emmanuel Bacry graduated from Ecole Normale Supérieure (Ulm, Paris, France) in 1990. He received the Ph.D. degree in Applied Mathematics from the university of Paris VII (France) in 1992 and obtained the “Habilitation à diriger des recherches” four years later. He is a researcher fellow at the Centre Nationale de Recherche Scientifique (CNRS) and an Associate Professor at the Centre de Mathématiques Appliquées (CMAP) at Ecole Polytechnique, Palaiseau, France. Since 2014, he is the head of the “Big Data and Data Science Initiative” of Ecole Polytechnique. In the last decades, he has focussed his research interest on various subjects including multifractal theory, statistics of random processes, random process in interaction, large dimension and Big Data. He is currently heading a project between Ecole Polytechnique and the Caisse Nationale d’Assurance Maladie (CNAMTS) consisting on data-mining the french public health database which is one of the biggest health database in the world (approximately 1000To). He has been regularly acting as a consultant for many start-ups as well as many large companies such as Deutsche Bank, Société Générale, BNP-Paribas, Chevreux, Havas Media.
Larry Harris (USC Marshall School of Business)
Trade-Throughs and Riskless Principal Trading in Corporate Bond Markets
This study analyzes the costs of trading bonds using previously unexamined quotations data consolidated across several electronic bond trading venues. Much bond market trading is now electronic, but the benefits largely accrue to dealers because their customers often do not trade at the best available prices. The trade through rate is 43%; the riskless principal trade (RPT) rate is above 42%; and 41% of customer trade throughs appear to be RPTs. Average customer transaction costs are 85 bp for retail-size trades and 52 bp for larger trades. Estimated total transaction costs for the year ended March 2015 are above $26 billion, of which about $0.5 billion is due to trade-through value while markups on customer RPTs transfer $0.7 billion to dealers. Small changes in bond market structure could substantially improve bond market quality.
Larry Harris holds the Fred V. Keenan Chair in Finance at the USC Marshall School of Business. His research, teaching, and consulting address regulatory and practitioner issues in trading and investment management. He is the author of Trading and Exchanges: Market Microstructure for Practitioners. Dr. Harris is lead independent director of Interactive Brokers, director of the Selected Funds, research coordinator of the Q-Group, and executive director of the Financial Economists Roundtable. He has served as Chief Economist of the SEC, associate editor of several academic journals, and director of CFA Society Los Angeles. He has also worked for an institutional broker and for a proprietary trading firm. Professor Harris received his Ph.D. in Economics from the University of Chicago in 1982, and is a designated CFA charterholder.
Albert Kyle (University of Maryland’s Robert H. Smith School of Business )
Dimensional Analysis and Market Microstructure Invariance
Physics researchers sometimes obtain powerful results by using dimensional analysis. In the field of finance, dimensional analysis is typically not explicitly used. Application of dimensional analysis to standard asset pricing models confirms known results. Application of dimensional analysis to market microstructure leads to an immediate, simple, powerful, non-obvious way to formulate hypotheses related to market microstructure invariance.
Professor Albert S. (Pete) Kyle has been the Charles E. Smith Chair Professor of Finance at the University of Maryland’s Robert H. Smith School of Business since 2006. Professor Kyle’s research focuses on market microstructure, including topics such as high frequency trading, informed speculative trading, market manipulation, price volatility, the informational content of market prices, market liquidity, and contagion. He is a Fellow of the American Finance Association in (2013) and a Fellow of the Econometric Society (2002) and was a staff member of the Presidential Task Force on Market Mechanisms (Brady Commission, 1987), a consultant to the SEC (Office of Inspector General), CFTC, and U.S. Department of Justice, a member of NASDAQ’s economic advisory board (2004-2007), a member of the FINRA economic advisory board (2010-2014), and a member of the CFTC’s Technology Advisory Committee (2010-2012).
Julien Kockelkoren (Capital Fund Management, Paris)
Market Impact: A Practitioner’s Viewpoint
The subject of market impact, i.e how buying/selling an asset influences its price, has been studied intensively for at least several decades, both in the academic community and the financial industry. In this talk we will focus on the viewpoint of a practitioner, highlighting three reasons why he/she could be interested in market impact. First, and perhaps most evidently, an understanding of market impact is useful for order execution and for transaction cost analysis. We will show some proprietary data to illustrate this. Second, we will give an example of how insight in supply and demand driving prices can yield ideas for possible arbitrage opportunities. Third, market impact is crucial for portfolio construction since it constrains the capacity of any trading system. We will stress the features of market impact that are most important here. Throughout the talk we will draw attention to the subtle relation between market impact and “information”.
Julien Kockelkoren is Head of Directional Strategies at Capital Fund Management. In this role he has responsibility for CFM’s directional portfolios. He joined CFM in 2003 to work on order execution and market impact. Julien was named Head of Execution in 2006 and continued in that role for 9 years. He is the author of several papers in the field of market microstructure. Before joining CFM, Julien was a postdoctoral fellow at the University of California San Diego, working on theoretical biophysics. He obtained his Ph.D. in Theoretical Physics at the Commissariat à l’Energie Atomique (“CEA”) in Saclay (France), working in the field of out-of-equilibrium statistical physics.
Giuseppe di Graziano (Deutsche Bank and Imperial College London)
Trading: how to stop?
Trading stops are often used by traders to risk manage their positions. We show how to derive optimal trading stops for generic algorithmic trading strategies when the P&L of the position is modeled by a) a Markov modulated diffusion b) local linear polynomials. Optimal stop levels are derived by maximizing the expected discounted utility of the P&L. The approach is independent of the signal used to enter the position. We analyze in details a few practical examples and show how to calibrate the model to market data.
Giuseppe is a trader and head of product development for the commodities team at Deutsche Bank AG London. In his current role, Giuseppe is responsible for managing the exotic precious metal book as well as developing algorithmic strategies for clients and algorithmic hedging solutions for the commodities trading desk. He is also a visiting professor at Imperial College London and an adjunct lecturer in financial mathematics at King’s College London. Giuseppe holds a Ph.D. in financial mathematics from the University of Cambridge and a MSc. in financial mathematics from King’s College London.
Round-Table Discussion: Are High-Frequency Traders the Last Resort Market Makers?
Stephen McGoldrick (Director, Market Structure, Deutsche Bank)
Stephen McGoldrick grew up in Scotland. He was awarded a scholarship to study at University of Georgia’s Terry College of Business, then graduated from Edinburgh University with a joint honours LLb (Law and Accounting). Staying in Edinburgh, he entered finance in 1990 as an analyst in NatWest’s Equity Quants team, working on indices then derivative and portfolio risk. Stephen spent 1992-99 as a derivatives broker, with responsibility for developing and selling clearing and the related technology platform, transferring with the team to Deutsche Bank. He moved to eCommerce in 1999, then into equity market connectivity, before taking on his current responsibility for European market structure in 2006. This role has led to involvement in several equity market structure initiatives, consultative groups, setting -up and being long term Board member on the Turquoise MTF, chairing AFME’s Securities Trading Committee, and most recently being appointed Project Director for Plato Partnership. Stephen’s motivation and remit is to improve (or, increasingly, to avoid a decline in) market efficiency. His greatest career achievement is finding a job he loves in The City of London while avoiding having to relocate from Edinburgh, where he lives with his wife, 3 children, 2 ferrets and 2 whippets called Frankie and Charlie.
Mark Hemsley (CEO, BATS Chi-X Europe)
Mark Hemsley is chief executive officer of BATS Chi-X Europe, the largest pan-European equities exchange and the European arm of BATS Global Markets. Under his leadership, BATS Chi-X Europe became a Recognised Investment Exchange (RIE) in May 2013, strengthening the company’s European leadership position in market structure, technology and innovation. He contributes his market structure expertise as a member of the European Securities and Markets Authority (ESMA) Secondary Markets Standing Committee providing consultation on the impact of market structure changes and ESMA policy development. During his tenure at BATS, Mr. Hemsley and his team have received numerous awards, including the Financial News Trading & Technology Awards Honour for Best Stock Exchange or MTF for five consecutive years. Mr. Hemsley has been named to the “FN 100 Most Influential” list, which recognizes key financial executives impacting European financial markets, every year since 2009 and was awarded “Decade of Excellence” by the title in 2015. Before joining BATS, Mr. Hemsley was managing director and chief information officer at LIFFE, running its Market Solutions group. Previously, Mr. Hemsley was a managing director at Deutsche Bank GCI and served at Credit Suisse First Boston and Natwest Capital Markets.
Grégoire Naacke (Head of Operations, World Federation of Exchanges)
Grégoire Naacke joined the World Federation of Exchanges in 2011 to work initially as an economist and is now Head of Operations. He previously worked (from 2002 to 2010) as a consultant for IEM Finance (French independent consulting firm specialized on financial markets organization and savings markets created by Didier Davydoff, former Director at Paris Stock Exchange) and as an Economist at the European Savings Institute (a non for profit organization presided by Jacques de Larosière aiming at promoting research on savings-related topics in Europe). In 2008 he was in parallel Scientific Adviser at the Centre d’Analyse Stratégique, an organization working directly under the direction of the French Prime Minister and whose objective is to assist the government in defining and implementing its economic, social, environmental and cultural policies. Grégoire graduated in Money, Banking and Finance from University Paris 1 Panthéon Sorbonne and is currently preparing for the CIIA (Certified International Investment Analyst).
Edwin Schooling Latter (Head of Market Infrastructure & Policy, Financial Conduct Authority)
Edwin Schooling Latter is Head of Markets Policy at the Financial Conduct Authority, where his responsibilities encompass policy in relation to primary and secondary markets, trading venues, trading conduct and benchmarks. From 2011-2014 Edwin was head of the Financial Market Infrastructure Directorate at the Bank of England, responsible for supervision of CCPs, securities settlement systems, and systemically important payment systems, and for the Bank’s input to policy making on central clearing and OTC derivatives reforms. Prior to his appointment as head of MID, Edwin worked in the Bank’s Financial Stability area for several years, including as secretary to the Bank’s Financial Stability Committee. Edwin was also previously Managing Director of UK payment system, LINK Interchange Network Ltd.
Frank Hatheway (Chief Economist, Nasdaq)
Dr. Frank M. Hatheway is Chief Economist of the NASDAQ OMX Group Inc., and leads the Economics & Statistical Research Department. His team is responsible for a variety of projects and initiatives in the U.S. and Europe to improve market structure, encourage capital formation, and enhance trading efficiency. A regular participant in industry events for both issuers and traders, he has appeared before national agencies around the world and the U.S. Congress to discuss a variety of issues around the equities and derivatives markets. Dr. Hatheway’s background prior to joining NASDAQ OMX combines academics and regulation with industry experience. Frank was a finance professor and has authored academic articles in leading finance journals. He has served as an Economic Fellow and Senior Research Scholar with the U.S. Securities and Exchange Commission, worked as a derivatives trader, and earned his Ph.D. in Economics from Princeton University.