
Podcast: Lipton and De Prado on Covid-19 and optimal trading strategies
Top quants discuss collaboration and their worries about the economic recovery

This podcast features two veteran quants, Alex Lipton, chief technical officer at SilaMoney and connection science fellow at MIT, and Marcos Lopez de Prado, co-founder and chief investment officer of True Positive Technologies and professor at Cornell University in New York.
The pair began collaborating recently. While reading de Prado’s book on quantitative investments, Lipton saw the possibility of solving an open question in that volume using a technique called heat potentials. “I got in touch with Marcos and we decided to work on that,” recalls Lipton. When Covid struck, they decided to work together to model the pandemic too.
The results of their first collaboration are presented in a paper published by Risk.net this month. In it, they provide a closed-form solution to finding the optimal thresholds for profit taking and setting stop losses in a mean-reverting market – a problem familiar to market-makers and execution traders. “Whether you are a liquidity provider or a liquidity consumer, the question of when to exit a position is a critical one,” explains de Prado.
Lipton and de Prado were dissatisfied with the way the problem was addressed in the existing literature and sought to create a solution that was both realistic and practical. They did so using heat potentials, a concept borrowed from physics, which allows them to calculate the boundaries of an optimal trading strategy.
Their epidemiological model on Covid-19, published in April, sprang more from a sense of “civic duty”, as they put it. Lipton was already familiar with standard epidemiological models, such as SEIR (susceptible, exposed, infectious and recovered). He previously studied them because he thought they could be adapted to solve a completely different problem – explaining variables in the market capitalisation of cryptocurrencies.
This effort was also motivated partly by dissatisfaction with existing models and a desire to develop a more realistic framework. Their model, called K-SEIR, assumes the distribution of the population is multi-modal, with distinct groups that are very differently affected by the virus.
Furthermore, in a rare case of quantitative finance influencing other fields, “we consider the rate of infection, R0, as an implicit variable, just like implied volatility in Black-Scholes”, says Lipton.
The pair also explain their gloomy outlook on the economic recovery from the pandemic and the value of nowcasting – which they touched on in a recent Risk.net article – in the current environment.
“There’s uncertainty coming back, as observed in the volatility level and in bids and offers levels,” says de Prado, adding that nowcasting is well suited to situations such as the current one, where there is a wealth of information.
“The economy right now is in a rather dire situation,” says Lipton. “Pandemics unfortunately come with periodicity.” The next time this happens, “we need to be much better prepared”.
INDEX
00:00 Intro
03:45 Optimal trading strategies in mean-reverting markets
07:10 Heat potentials
11:05 Model assumptions
14:25 Results and comparison to existing methods
18:25 The Covid-19 model and the flaws of the standard approaches
28:30 The multi-modal distribution of the population and the unreliability of available data
33:55 What the model tells you
36:35 Application to policy and investment decisions
39:50 Outlook on the economic and financial recovery
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.
You may share this content using our article tools. Printing this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
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. Copying this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@risk.net
More on Cutting Edge
Information geometry of risks and returns
An innovative product design framework and its geometric interpretation is introduced
Podcast: Jan Rosenzweig on fat tails and LDI portfolios
An optimised portfolio can look very different when extreme moves are given more weight
Fat tails and optimal LDI portfolios
A portfolio optimisation technique for pension funds and insurance portfolios is presented
A model for small basket equities financing
A haircut model for equity baskets based on credit and equity indexes is introduced
The carbon equivalence principle: methods for project finance
A method to price the environmental impact of financial products is proposed
Podcast: Barzykin and Guéant on FX market-making
Industry quant teams up with academics to build better risk tools for FX markets
Funding, wealth transfer and financial stability in the post-Libor era
Adjusting RFR with a funding premium may aid economic growth and stability
Dealing with multi-currency inventory risk in FX cash markets
A market-making model that considers correlation, transaction costs and market impact is presented