New papers 2021 and 2022

At Risk.net Cutting Edge’s section:

Liquidity stress-testing using optimal portfolio liquidation by Mike Weber, Bastien Baldacci and Iuliia Manziuk

Optimal turnover, liquidity and autocorrelation by Bastien Baldacci, Jerome Benveniste and Gordon Ritter

Deep calibration of the quadratic rough Heston model by Mathieu Rosenbaum and Jianfei Zhang

An approximate solution for options market-making in high dimension by Bastien Baldacci, Joffrey Derchu and Iuliia Manziuk

New papers – 2nd half of 2020

  • Optimal auction duration: A price formation viewpoint by Paul Jusselin, Thibaut Mastrolia, Mathieu Rosenbaum
    • We consider an auction market in which market makers fill the order book during a given time period while some other investors send market orders. We define the clearing price of the auction as the price maximizing the exchanged volume at the clearing time according to the supply and demand of each market participants. Then we derive in a semi-explicit form the error made between this clearing price and the efficient price as a function of the auction duration. We study the impact of the behavior of market takers on this error. To do so we consider the case of naive market takers and that of rational market takers playing a Nash equilibrium to minimize their transaction costs. We compute the optimal duration of the auctions for 77 stocks traded on Euronext and compare the quality of price formation process under this optimal value to the case of a continuous limit order book. Continuous limit order books are found to be usually sub-optimal. However, in term of our metric, they only moderately impair the quality of price formation process. Order of magnitude of optimal auction durations is from 2 to 10 minutes.
  • A note on Almgren-Chriss optimal execution problem with geometric Brownian motion by Bastien Baldacci, Jerome Benveniste
    • We solve explicitly the Almgren-Chriss optimal liquidation problem where the stock price process follows a geometric Brownian motion. Our technique is to work in terms of cash and to use functional analysis tools. We show that this framework extends readily to the case of a stochastic drift for the price process and the liquidation of a portfolio.
  • Algorithmic market making for options by Bastien Baldacci, Philippe Bergault, Olivier Guéant  (published in Quantitative Finance)
    • In this article, we tackle the problem of a market maker in charge of a book of options on a single liquid underlying asset. By using an approximation of the portfolio in terms of its vega, we show that the seemingly high-dimensional stochastic optimal control problem of an option market maker is in fact tractable. More precisely, when volatility is modeled using a classical stochastic volatility model — e.g. the Heston model — the problem faced by an option market maker is characterized by a low-dimensional functional equation that can be solved numerically using a Euler scheme along with interpolation techniques, even for large portfolios. In order to illustrate our findings, numerical examples are provided.
  • Adaptive trading strategies across liquidity pools by Bastien Baldacci, Iuliia Manziuk
    • In this article, we tackle the problem of a market maker in charge of a book of options on a single liquid underlying asset. By using an approximation of the portfolio in terms of its vega, we show that the seemingly high-dimensional stochastic optimal control problem of an option market maker is in fact tractable. More precisely, when volatility is modeled using a classical stochastic volatility model — e.g. the Heston model — the problem faced by an option market maker is characterized by a low-dimensional functional equation that can be solved numerically using a Euler scheme along with interpolation techniques, even for large portfolios. In order to illustrate our findings, numerical examples are provided.
  • An approximate solution for options market-making in high dimension by Bastien Baldacci, Joffrey Derchu, Iuliia Manziuk
    • Managing a book of options on several underlying involves controlling positions of several thousands of financial assets. It is one of the most challenging financial problems involving both pricing and microstructural modeling. An options market maker has to manage both long- and short-dated options having very different dynamics. In particular, short-dated options inventories cannot be managed as a part of an aggregated inventory, which prevents the use of dimensionality reduction techniques such as a factorial approach or first-order Greeks approximation. In this paper, we show that a simple analytical approximation of the solution of the market maker’s problem provides significantly higher flexibility than the existing algorithms designing options market making strategies.
  • AHEAD : Ad-Hoc Electronic Auction Design by Joffrey Derchu, Philippe Guillot, Thibaut Mastrolia, Mathieu Rosenbaum
    • We introduce a new matching design for financial transactions in an electronic market. In this mechanism, called ad-hoc electronic auction design (AHEAD), market participants can trade between themselves at a fixed price and trigger an auction when they are no longer satisfied with this fixed price. In this context, we prove that a Nash equilibrium is obtained between market participants. Furthermore, we are able to assess quantitatively the relevance of ad-hoc auctions and to compare them with periodic auctions and continuous limit order books. We show that from the investors’ viewpoint, the microstructure of the asset is usually significantly improved when using AHEAD.

A note on Almgren-Chriss optimal execution problem with geometric Brownian motion

Published on arxiv:

A note on Almgren-Chriss optimal execution problem with geometric Brownian motion

Abstract: We solve explicitly the Almgren-Chriss optimal liquidation problem where the stock price process follows a geometric Brownian motion. Our technique is to work in terms of cash and to use functional analysis tools. We show that this framework extends readily to the case of a stochastic drift for the price process and the liquidation of a portfolio.

Mathieu Rosenbaum – 2020 Louis Bachelier Prize Winner

From the announcement:

The 2020 Louis Bachelier Prize is awarded to Professor Mathieu Rosenbaum (École Polytechnique, Paris).

Professor Rosenbaum is internationally recognised as one of the foremost experts in stochastic modelling in finance. Rosenbaum’s research, focused on stochastic processes and their applications in finance, impresses through the breadth of topics it has covered and the depth of results obtained on each topic. His research spans theoretical topics in probability and statistics as well as market microstructure, statistical modelling of high frequency financial data and volatility modelling. His highly visible international profile and remarkable scientific achievements make him an excellent candidate for the 2020 Louis Bachelier Prize.

On bid and ask side-specific tick sizes

Published on arxiv:

On bid and ask side-specific tick sizes

Abstract: The tick size, which is the smallest increment between two consecutive prices for a given asset, is a key parameter of market microstructure. In particular, the behavior of high frequency market makers is highly related to its value. We take the point of view of an exchange and investigate the relevance of having different tick sizes on the bid and ask sides of the order book. Using an approach based on the model with uncertainty zones, we show that when side-specific tick sizes are suitably chosen, it enables the exchange to improve the quality of liquidity provision.

The quadratic rough Heston model and the joint S&P 500/Vix smile calibration problem

The quadratic rough Heston model and the joint S&P 500/VIX smile calibration problem (arXiv link) was published on the Cutting Edge section of Risk.net:

Risk – Cutting Edge – The quadratic rough Heston model and the joint S&P 500/VIX smile calibration problem

Authors: Jim Gatheral, Paul Jusselin, Mathieu Rosenbaum

Abstract: Fitting simultaneously SPX and VIX smiles is known to be one of the most challenging problems in volatility modeling. A long-standing conjecture due to Julien Guyon is that it may not be possible to calibrate jointly these two quantities with a model with continuous sample-paths. We present the quadratic rough Heston model as a counterexample to this conjecture. The key idea is the combination of rough volatility together with a price-feedback (Zumbach) effect.