CUATS
Cambridge University
Algorithmic Trading Society
A talk titled "Towards Non-Perturbative Models of Market Dynamics" by Igor Halperin, Ph.D., AI Research Associate at Fidelity Investments, on 20 October, 2021 17:00 pm GMT.
Summary:
In this talk, I will present models for financial markets that are inspired by insights from physics and machine learning. I will start with outlining problems with standard models used for derivatives pricing and portfolio optimization such as the celebrated Geometric Brownian Motion (GBM) model, that arise due to their underlying linearity assumptions/approximations. I then present a non-linear extension of the GBM model that offers more appealing long-term dynamics, and show how such dynamics can be obtained if we incorporate both the new money flows into the market, and frictions caused by these flows. These effects are parameterized by two additional parameters, which are used in addition to parameters of the GBM model. While the GBM model can formally be recovered by setting these parameters to zero, some qualitatively important behavior of the resulting model is lost in this limit. This suggests that non-linear models and non-perturbative methods (i.e. those that do not rely on perturbation theory, i.e. do not start with a fictitious ‘friction-free’ limit, but rather keep friction parameters non-zero from the start) may be important for modeling market dynamics. I will then present a more practically oriented version of this approach called the Non-Equilibrium Skew (NES) model, and show how it can be calibrated to market data.
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 on algorithm development and the basics of financial investment strategies.
Members
Yearly Events
Years active
Hours of
Coding Sessions
Speaker Series
We host outstanding, accomplished individuals across academia and industry in a series of talks and seminars held throughout the academic year. Academics discuss their research in quant finance, and industry experts share their experiences in real-life automated trading.
Coding Sessions
Join our bi-weekly Sunday coding sessions where you will be introduced to mathematical concepts behind algorithmic trading, learn basic trading strategies, and how to implement them in code.
These are hands-on sessions so a laptop is required.
Industry-Sponsored Workshops
Join our career networking events with top industry employers to participate in industry-sponsored workshops, and to meet quant traders and recruitment leads.
Fireside Chat Series
To complement our Speaker Series, in November, 2021 we initiated the Fireside Chat Series to highlight the experiences of current students and recent graduates who have completed internships or are working in the quant finance industry.
Conference
CUATS will be hosting its first conference in 2022 bringing together leading experts in the quant fields of alpha generation, portfolio optimisation, execution, and risk management. Full details of the speakers and the programme of talks will be confirmed in Lent term 2022.
Save the date:
Friday, 25 February, 2022
Gala
Join us for our inaugural CUATS Gala in June 2022 - a formal event where members of the society are paired with industry sponsors for dinner. This event promises to be an exceptional opportunity for networking and career advancement. Details and tickets to be announced in Easter term 2022.
Wednesday, 15 June 2022
Committee
The Cambridge University Algorithmic Trading Society (CUATS) 2021/2022 committee is comprised of:
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
Contact Us
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
© Cambridge University Algorithmic Trading Society
800
12
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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.
