CUATS

Cambridge University
Algorithmic Trading Society

CUATS Quant Conference 

25 February 2022

 

We are excited to be organising our inaugural quant conference! 

 

This event will feature four experts discussing the latest research in the world of algortihmic trading.  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, namely:

 

 

- Universe Selection/Alpha Generation

 

Applications of Machine Learning to Target Alpha in Financial Markets  Fredrik Giertz Jonsson, Executive Director of Strategic Indices Structuring, J.P. Morgan

 

- Portfolio Construction

 

Portfolio Construction and the Long-Only Constraint  Ashley Lester, Head of Systematic Investments, Schroders

 

- Execution

 

Applying Advanced Technologies to Equity Trading  Andreas Petrides, Head of Foundational Research, Quantitative Execution Strategies, Goldman Sachs and Andi Reci, Quantitative Researcher, Quantitative Execution Strategies, Goldman Sachs

 

- Risk Management

 

Covariance Matrices and Risk Control: Random Matrix Theory and Beyond  Jean-Philippe Bouchaud, Chairman and Head of Research, Capital Fund 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 networking reception to follow.   Refreshments and merchandise will be provided.  Ticket bookings can be made here:

 

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

 

https://cuats_conference1.eventbrite.co.uk  (General Admission)

 

Please take a look at the Conference Agenda below, which includes the speakers' bios and abstracts of their talks. 

 

We look forward to seeing you at the CUATS Quant Conference 2022 on Friday, 25 Februrary, 2022 - the first in what is hopefully an annually occurring event!

Agenda

Topic

Speaker

13:30 - 14:00

Registration

Registration

14:00 - 14:05

Opening Remarks

Farouk Hadeed, President, CUATS

14:05 - 14:45

KEYNOTE ON UNIVERSE SELECTION AND ALPHA GENERATION

Applications of Machine Learning to Target Alpha in Financial Markets

Machine Learning offers tools than can be used to capture markets patterns otherwise inaccessible though classical quantitative methods, patterns that are unrelated to classical risk premia factors. When used properly, ML has the ability to solve many of the potential issues involved in designing investment strategies through classical means, where backtest overfitting and hindsight bias may often cloud decision making.

In this talk, Fredrik will walk through his experience in using ML with particular focus on the theoretical motivation, the practical problems and several case studies.

Fredrik Giertz Jonsson, Executive Director of Strategic Indices Structuring, Equity Derivatives Structuring group, J.P. Morgan

 

Fredrik Giertz Johnsson is an experienced Quantitative Analyst with expertise in Machine Learning and Financial Modeling. He works within the Investable Index Division of J.P. Morgan and is  focused on growing and developing quantitative strategies that use machine learning techniques for the invesment bank. He has several years' experience in managing quantitative strategies, from alternative risk to more advanced strategies using machine learning technology.  Giertz Johnsson joined J.P. Morgan in 2020 from the Third Swedish National Pension Fund (AP3), where he was a risk analyst, quantitative analyst, and senior manager of quantitative strategies in Stockholm. He holds a Master of Science Degree in Mathematics and Statistics from KTH Royal Institute of Technology in Sweden.

14:45 - 15:30

KEYNOTE ON PORTFOLIO CONSTRUCTION

Portfolio Construction and the Long-Only Constraint

The long-only constraint is arguably the most pervasive real-world constraint on mean-variance optimisation faced by investors.  Yet its implications for portfolio construction remain relatively little explored.  In this talk Ashley will demonstrate the key challenge the constraint creates; question the importance of shorting in portfolio construction; and illustrate some counter-intuitive implications of the constraint for optimisation

Ashley Lester, Head of Systematic Investments, Schroders

 

Ashley Lester is the Head of Multi-Asset Research at Schroders, which involves responsiblity for factor investing strategies (both long-only and long-short), risk premium allocation modelling and the development of proprietary portfolio construction tools.  Ashley is Chair of the Strategic Investment Group Multi-Asset (SIGMA) and the Model Review Group. He joined Schroders in 2015 and is based in London. Ashley was the Head of Fixed Income and Multi Asset Research at MSCI from 2013 to 2015, which involved responsibility for fixed income, alternatives and risk methodology in the widely used Barra and RiskMetrics platforms. He was Managing Director and Head of Market Risk Methodology at Morgan Stanley from 2007 to 2013, which involved responsibility for all market risk models used by Morgan Stanley globally to calculate both regulatory capital and economic capital.  Major projects included Basel 2.5 and CCAR. He was a Visiting Assistant Professor of Economics and Finance at Columbia Business School from 2007 to 2007. He was an Assistant Professor of Economics at Brown University from 2005 to 2007.  He obtained his PhD in Economics from M.I.T; Bachelor of Economics (Honours Class I and University Medal) in Economics from the University of Sydney.

15:30 - 16:00

Break with Refreshments

Break with Refreshments

16:00 - 16:45

KEYNOTE ON EXECUTION

Applying Advanced Technologies to Equity Trading

Advances in technology have made it possible for a large amount of information to be consumed in real time and for the algorithms that drive trading to adapt their strategies with little latency. Further, the proliferation of alternative datasets and APIs which can provide real time updates of the data has opened the gate to a host of different strategies you can employ intraday. This presentation focuses on how we make use of these advances, the knowledge of how the market microstructure changes during the day and the cross-sectional relationships between stocks in designing signals and algorithms which help our clients reduce their transaction costs. We give a high level overview of the type of signals we employ and how we use them in different parts of the trade order life: from intraday scheduling to the actual placement logic in the Limit Order Book. 

Andreas Petrides, Head of Foundational Research, Quantitative Execution Services, Securities Division, Goldman Sachs

Andi Reci, Executive Director, Quantitative Execution Services, Securities Division, Goldman Sachs

 

Andreas Petrides is Head of Foundational Research in Quantitative Execution Services at Goldman Sachs, focusing on signal research for execution algorithms.  Andreas received a PhD in Information Engineering from the University of Cambridge, working on the interface of stochastic control theory and Bayesian machine learning.  He also holds BA and MEng degrees in Electrical and Information Sciences from Trinity College, University of Cambridge, where he was the recipient of the G-Research and TTP awards.

Andi Reci is a Quantiative Researcher in Quantitative Execution Services at Goldman Sachs.  He holds a PhD in Chemical Engineering from the University of Cambridge, Trinity College, where he was a Gates Scholar and recipient of the Danckwets-Pergamon Prize for best dissertation in a field connected to chemical engineering.

16:45 - 17:30

KEYNOTE ON RISK MANAGEMENT

Covariance Matrices and Risk Control : Random Matrix Theory and Beyond
The crucial primary input of any quantitative risk control is the asset covariance matrix. Unfortunately, its determination is plagued with difficulties. Even in a stationary world, large empirical covariance matrices exhibit strong biases, which are compounded by real (sometimes sudden) changes in the correlation structure. My talk will summarize and illustrate recent ideas around these themes, some inspired by Random Matrix Theory.

Jean-Philippe Bouchaud, Chairman and Head of Research, Capital Fund Management

 

Jean-Philippe Bouchaud is a French physicist. He is co-founder and Chairman of Capital Fund Management (CFM), which manages a large set of quantitative strategies that trade liquid instruments across global markets including futures, equities, bonds, options, foreign exchange and various derivatives within a rigorous risk framework. He is also adjunct professor at École Normale Supérieure and co-director of the CFM-Imperial Institute of Quantitative Finance at Imperial College London. He is a member of the French Academy of Sciences, and held the Bettencourt Innovation Chair at Collège de France in 2020.

 

17:30 - 17:35

Closing Remarks

Farouk Hadeed, President, CUATS

17:35 - 18:45

Networking Reception

Networking Reception

Contact Us

 

If you have any questions or suggestions, feel free to reach out to us

Address:

Cambridge University Algorithmic Trading Society

SU Building, 17 Mill Lane

Cambridge, CB2 1RX

United Kingdom

 

E-mail:

president@cuats.co.uk

Name  
E-mail  
Message  

Contact Us

Get API key from Google and insert it to plugin properties to enable maps on your website.

If you have any questions or suggestions, feel free to reach out to us!

 

E-Mail: ____@cuats.co.uk

 

Post Box

Cambridge University Algorithmic Trading Society

SU Building, 17 Mill Lane

Cambridge, CB2 1RX

 

 

Privacy Policy

 

© Cambridge University Algorithmic Trading Society

800

12

7

60+

10

Years of History

Hours of Coding Lessons

Major Sponsors

Societal and intersocetal events

Active Members

CUATS in stats

Meet the Committee

Farouk Hadeed

President

Farouk is the president of the society

Christos Antonopoulos

Vice President

Christos is a second year enginneering student in Homerton College

Alex ...

Description

Description

Name..

Role

Description

About us 

 

The Cambridge University Algorithmic Trading Society (CUATS) is the first student society in Cambridge to promote the understanding of algorithms and their applications in financial trading. CUATS aims to provide interdisciplinary education of algorithm development and the basics of financial investment strategies. In the forms of workshops, networking sessions and tutorials (code writing of your own investment strategies), we wish to provide our members the necessary skills and the many opportunities to pursue a career in the financial industry as well as in the big data industry.

Vision

 

The Cambridge University Algorithmic Trading Society  is the first student society in Cambridge to promote the understanding of algorithms and their applications in financial trading. CUATS aims to provide interdisciplinary education of algorithm development and the basics of financial investment strategies. In the forms of workshops, networking sessions and tutorials (code writing of your own investment strategies), we wish to provide our members the necessary skills and the many opportunities to pursue a career in the financial industry as well as in the big data industry.

Mission

 

The Cambridge University Algorithmic Trading Society (CUATS) is the first student society in Cambridge to promote the understanding of algorithms and their applications in financial trading. CUATS aims to provide interdisciplinary education of algorithm development and the basics of financial investment strategies. In the forms of workshops, networking sessions and tutorials (code writing of your own investment strategies), we wish to provide our members the necessary skills and the many opportunities to pursue a career in the financial industry as well as in the big data industry.