We are excited to be organising our third annual quant conference! 

This event will feature four presentations by experts discussing the latest research in the world of algortihmic trading.  Please scroll down to the Agenda.  The talks also fit neatly within the modular framework of the QuantConnect platform for automated trading we have been using to build our own algorithms in our fortnightly Coding Sessions and Challenge – Coding Competition, namely:

• Universe Selection
• Alpha Generation
• Portfolio Construction/Optimisation
• Execution
• Risk Management

This is a great opportunity to hear some fascinating talks and to meet some of today’s leaders in the quant industry as well as to mingle with like-minded students and graduate practitioners interested in this field. 

The conference will take place in the William Mong Hall at Sidney Sussex College, Cambridge, with a wine and canapes networking reception to follow. 

Refreshments will be provided during the conference. 

Ticket bookings may be made here:

https://cuats_quant_conference_2024.eventbrite.co.uk  (Student Admission)

https://cuats_quant_conference1_2024.eventbrite.co.uk   (General Admission)

Please take a look at the Conference Agenda below, which includes the speakers’ biographies, titles, and abstracts of their talks. 

We look forward to seeing you at the CUATS Quant Conference 2024 on Friday, 1 March, 2024!

Featuring speakers from the following companies

Event Agenda

Time	Topic	Speaker
13:30 – 14:00	Registration	Registration
14:00 – 14:05	Opening Remarks	Farouk Hadeed, President, CUATS
14:05 – 14:45	Optimal Turnover   The steady-state turnover of a trading strategy is of clear interest to practitioners and portfolio managers, as is the steady-state Sharpe ratio. In this article, we show that in a convenient Gaussian process model, the steady-state turnover can be computed explicitly, and obeys a clear relation to the liquidity of the asset and to the autocorrelation of the alpha forecast signals. Indeed, we find that steady-state optimal turnover is given by gamma*sqrt(n+1) where gamma is a liquidity-adjusted notion of risk-aversion, and n is the ratio of mean-reversion speed to gamma. We shall also discuss a generalization of the famous result of Garleanu and Pedersen.	Gordon Ritter, Chief Investment Officer, Ritter Alpha LP   Gordon Ritter is CIO and Founder of Ritter Alpha LP, a registered investment adviser focused on systematically-managed quantitative absolute-return strategies. Concurrently with his CIO responsibilities, he teaches at NYU Courant, Columbia, the University of Chicago, and the Baruch MFE program. He was selected as Buy-Side Quant of the Year for 2019 by Risk. Prior to founding Ritter Alpha, Gordon was a senior portfolio manager at GSA Capital where he designed, built, and managed statistical arbitrage strategies, and directed research in GSA’s New York office. Prior to GSA, Gordon was a Vice President of Highbridge Capital and a core member of the firm’s statistical arbitrage group. Gordon completed his PhD in mathematical physics at Harvard University, He earned his Bachelor’s degree with honors in Mathematics from the University of Chicago.
14:45 – 15:30	Mo’ Dealers, Mo’ Problems   Electronic trading produces plenty of data that can be analysed and used to improve processes. However, it can become a daunting challenge to untangle what’s a real effect and what comes from biases in both behaviour and data collection. For example, a trader asking liquidity providers in competition must be willing to experiment with different amounts of competition to assess what performs better and likewise, a trader selecting an algo from algo provider needs to have sufficient data to understand the true behaviour of the algo. In this talk we will show data from simulation of simple models can help drive education and set the boundaries of experiments. Once the experiments have been conducted causal analysis can be used to reduce the bias in the data. Then once the experiments have been completed, introducing an element of randomisation in the new process can help complete the loop and continue to provide useful data.	David Shelton, Managing Director, Global Head of the FICC Electronic Trading and FX Quantitative Strategies Group at Bank of America   David Shelton is Global Head of the FICC Electronic Trading and FX Quantitative Strategies Group at Bank of America. In this role he is responsible for the implementation of electronic trading models and algorithms used across FICC electronic trading and models used across all the FX businesses including options, transactional FX and local currency trading. Since 1998 David has worked as a quantitative analyst across most of the FICC asset classes. Before that David was a postdoctoral theoretical physicist at the Université de Sherbrooke and Oxford for 2 years, after receiving a DPhil in Theoretical Physics from the University of Oxford in 1996 and a BA Hons in Physics, also from the University of Oxford, in 1993.
15:30 – 16:00	Break with Refreshments	Break with Refreshments
16:00 – 16:45	A Tale of Two Flows    In this talk, I will present empirical evidence supporting a flow-driven view of the market, where the main driver of price changes is trading, even when uninformed. In the first part, I will define active vs. passive investing, and briefly describe the index arbitrage mechanism. In the second part, I will focus on active ETFs and demonstrate how flow-driven trading can enhance funds’ own returns, due to a price impact effect. This phenomenon is particularly relevant when the ETF holds concentrated position on illiquid securities.	Dario Villamaina, Executive Director, Capital Fund Management (CFM)   Dario Villamaina is an executive director at CFM, a French hedge fund based in Paris. His work at CFM focuses on applications of random matrix theory to correlation data analysis. Determining correlations among variables starting from some observations is a common problem in statistics. In these cases, one deals with some estimators of correlation matrices, which are affected by finite sampling.  Dario holds a PhD in Physics from Sapienza University in Rome, Italy. Before joining CFM, he worked as postdoctoral researcher both at the École Normale Supérieure and at the Paris-Sud University. He has taught mathematics and physics in several universities both in Italy and France.
16:45 – 17:30	Finite Sample Bounds on Sharpe Degradation Due to Covariance and Alpha Mis/Estimation   It has long been known that estimation errors in the inputs of mean-variance optimization can severely degrade investment performance: Markowitz met early challenges when implementing MVO at his Arbitrage Management Company in 1968, and with Michaud was one of the early contributors in the literature in 1989. I will frame the problem in terms of Sharpe Ratio Efficiency Loss, give and geometric interpretation, and present some lower bounds to loss of efficiency due to estimation errors in expected returns and covariance matrix.	Giuseppe Paleologo, Head of Risk, Hudson River Trading Giuseppe Paleologo has worked as a line order cook, unpaid altar boy, aspiring poet, failed physicist and adequate mathematician. He is on gardening leave, and will Join Balyasny Asset Management in November 2024 as Head of Quantitative Research. Most recently, he served as the Head of Risk Management at Hudson River Trading, where he was responsible for all aspects of the firm’s risk. Before joining HRT, he was the Head of Enterprise Risk at Millennium, a Director of Equities Quantitative Research at Citadel, and a Director at Axioma (now part of Deutsche Börse). In finance, his agenda comprises only two items: to lose as little money as is reasonable when working in risk, and to make as much money as possible when working in quantitative research. He has written a book aimed at practitioners (“Advanced Portfolio Management, Wiley 2021), which has been well received. In a previous life, he was an applied mathematician in the Mathematical Sciences Department of IBM Research. He holds a Ph.D. in Management Science and Operations Research, a M.S. in Operations Research, a M.S. in Statistics, all from Stanford University, and a M.S. in Physics from the University of Rome.
17:30 – 17:35	Closing Remarks	Farouk Hadeed, President, CUATS
17:35 – 18:45	Networking Reception	Networking Reception

Event Highlights