Podcast: Barzykin and Guéant on FX market-making
Industry quant teams up with academics to build better risk tools for FX markets
Foreign exchange is the largest financial market in the world. It is also among the least well understood. Much of the academic literature focuses on the dealer-to-client market and assumes banks simply quote prices and wait for clients to trade. The reality is far more complex, leading a trio of researchers to take a stab at designing better models for the market.
“In our two papers, we build models in which market-makers skew their quotes, but they can also unwind in the inter-bank segment of the market. So we have the dealer-to-dealer and the dealer-to-client markets,” says Olivier Guéant, professor of applied mathematics at Université Paris 1 Panthéon-Sorbonne.
Trading over-the-counter with other dealers greatly mitigates execution uncertainty, which is crucial for risk management. But it also means dealers face transaction costs and market impact, which must be factored into models. “Our model provides a framework for optimal risk management under these conditions,” explains Alexander Barzykin, director of global FX and commodities at HSBC.
Guéant and Barzykin are our guests on this episode of Quantcast. The discussion focuses on two papers they co-authored with Philippe Bergault, assistant professor at Université Paris Dauphine-PSL, which were recently published in Risk.net.
The first of these works, published in August 2022, presents a market-making model for baskets of currency pairs. The framework can be used for determining the optimal level of externalisation, or hedging in the open market, and by extension, the level of risk that can be held in the portfolio and offset with client trades, or internalised .
The second paper, published in March 2023, builds on the previous work to develop a portfolio-level, multi-currency model that allows the user to determine optimal prices and hedging rates as functions of their inventory, risk aversion and market-driven parameters.
That took some tricks and ad hoc solutions. First, monetary amounts were converted to USD. That may sound trivial, but it significantly simplified the calculations. Second, they had to deal with the curse of dimensionality, a product of a partial integral differential equation in the formulation. Luckily, Guéant and Bergault had previously developed a solution that reduced the problem to a linear quadratic control problem, which turned out to be applicable to this case.
Guéant sees clear benefits in a portfolio-level approach: “The consequence for clients of the market-maker using a portfolio-level model is that they should experience better prices and less market footprint because there is less externalisation.”
Guéant and Barzykin also discuss their long collaboration, which is likely to continue with further extensions of their model – though they are confident the current version is now ready for use. Meanwhile, the model has caught the attention of the IEF/SCOR Foundation for Science, which recognised Guéant as best young researcher in finance and insurance on March 21.
Index
00:00 Introduction
03:46 Inventory risk, internalisation and externalisation
08:45 The currency-pairs approach
10:55 The multi-currency, portfolio-level approach
22:43 Applicability and results of the multi-currency model
32:02 Risk management using the model
35:25 Collaboration between industry and academia
42:10 The next version of the model
To hear the full interview, listen in the player above, or download. Future podcasts in our Quantcast series will be uploaded to Risk.net. You can also visit the main page here to access all tracks, or go to the iTunes store, Spotify or Google Podcasts to listen and subscribe.
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@risk.net or view our subscription options here: http://subscriptions.risk.net/subscribe
You are currently unable to print this content. Please contact info@risk.net to find out more.
You are currently unable to copy this content. Please contact info@risk.net to find out more.
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@risk.net
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@risk.net
More on Cutting Edge
Choosing trading strategies using importance sampling
The sampling technique is more efficient than A-B testing at comparing decision rules
A comparison of FX fixing methodologies
FX fixing outcomes are mostly driven by length of calculation window
Quantum cognition machine learning: financial forecasting
A new paradigm for training machine learning algorithms based on quantum cognition is presented
Backtesting correlated quantities
A technique to decorrelate samples and reach higher discriminatory power is presented
A hard exit threshold strategy for market-makers
A closed-form solution to derive optimal stop-loss and profit-taking levels is presented
Pricing share buy-backs: an alternative to optimal control
A new method applies optimised heuristic strategies to maximise share buy-back contracts’ value
CVA sensitivities, hedging and risk
A probabilistic machine learning approach to CVA calculations is proposed
Podcast: Alvaro Cartea on collusion within trading algos
Oxford-Man Institute director worries ML-based trading could have anti-competitive effects