BACHELIER FINANCE SOCIETY ONE WORLD SEMINARS (ONLINE)

Started during the pandemic, we want to keep the active spirit of our whole scientific community going and to continue solving financial problems of our times and keep our online seminars going.

We organise an online talk on the last Thursday of a month (with a few exceptions), alternating with the talks set up by the SIAM activity group on financial mathematics and engineering (http://wiki.siam.org/siag-fm/index.php/Current_events).

Find the list of the BFS One World Seminars below.

2024

Date: Thursday, 27 June 2024

Speaker: Alvaro Cartea (University of Oxford)

Title: Spoofing and Manipulating Order Books with Learning Algorithms

Abstract: We propose a dynamic model of the limit order book to derive conditions to test if a trading algorithm will learn to manipulate the order book. Our results show that as a market maker becomes more tolerant to bearing inventory risk, the learning algorithm will find optimal strategies that manipulate the book more frequently. Manipulation occurs to induce mean reversion in inventory to an optimal level and to execute round-trip trades with limit orders at a higher probability than was otherwise likely to occur; spoofing is a special case when the market maker prefers that manipulative limit orders are not filled. The conditions are tested with order book data from Nasdaq and we show that market conditions are conducive for an algorithm to learn to manipulate the order book. Finally, when two market makers use learning algorithms to trade, their algorithms can learn to coordinate their manipulation.

Joint work with Patrick Chang and Gabriel García-Arenas.

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4639959

Thursday, 27 June 2024, 19:00 (GMT +2)

Link to registration:
https://ethz.zoom.us/meeting/register/u50uf-mtrzwjGdGuojyBBJrfPpCqTYEIVo5T

Date: Thursday, 26 September 2024

Speaker: TBA

Title: TBA

Abstract: TBA

Thursday, 26 September 2024, 19:00 (GMT +2)

Link to registration:
will be published in due course

Date: Thursday, 24 October 2024

Speaker: TBA

Title: TBA

Abstract: TBA

Thursday, 24 October 2024, 19:00 (GMT +2)

Link to registration:
will be published in due course

Date: Thursday, 28 November 2024

Speaker: TBA

Title: TBA

Abstract: TBA

Thursday, 28 November 2024, 19:00 (GMT +1)

Link to registration:
will be published in due course

Date: Thursday, 23 May 2024

Speaker: Samuel Cohen (University of Oxford)

Title: Calibration of Hawkes-like processes for LOBs

Abstract: One of the common families of models for high-frequency data is self-exciting processes, such as Hawkes processes. Except in the memoryless case, these processes are generally not Markov, and their calibration to data is delicate and computationally challenging. In this talk we will explore a gradient-descent algorithm for calibration, which allows for a wide variety of models to be considered. We will also apply this to limit-order-book data, and see that some of the classic ‘stylized fact’ of these models may be simply due to artifacts of calibration.

Thursday, 23 May 2024, 19:00 (GMT +2)

Date: Thursday, 25 April 2024

Speaker: Johannes Ruf (LSE)

Title: The numeraire e-variable and reverse information projection

Abstract: We consider testing a composite null hypothesis \(\mathcal{P}\) against a point alternative \(\mathsf{Q}\) using e-variables, which are nonnegative random variables \(X\) such that \(\mathbb{E}_\mathsf{P}[X] \leq 1\) for every \(\mathsf{P} \in \mathcal{P}\). This paper establishes a fundamental result: under no conditions whatsoever on \(\mathcal{P}\) or \(\mathsf{Q}\), there exists a special e-variable \(X^*\) that we call the numeraire, which is strictly positive and satisfies \(\mathbb{E}_\mathsf{Q}[X/X^*] \leq 1\) for every other e-variable \(X\). In particular, \(X^*\) is log-optimal in the sense that \(\mathbb{E}_\mathsf{Q}[\log(X/X^*)] \leq 0\). Moreover, \(X^*\) identifies a particular sub-probability measure \(\mathsf{P}^*\) via the density \(d \mathsf{P}^*/d \mathsf{Q} = 1/X^*\). As a result, \(X^*\) can be seen as a generalized likelihood ratio of \(\mathsf{Q}\) against \(\mathcal{P}\). We show that \(\mathsf{P}^*\) coincides with the reverse information projection (RIPr) when additional assumptions are made that are required for the latter to exist. Thus \(\mathsf{P}^*\) is a natural definition of the RIPr in the absence of any assumptions on \(\mathcal{P}\) or \(\mathsf{Q}\). In addition to the abstract theory, we provide several tools for finding the numeraire and RIPr in concrete cases. We discuss several nonparametric examples where we can indeed identify the numeraire and RIPr, despite not having a reference measure. Our results have interpretations outside of testing in that they yield the optimal Kelly bet against \(\mathcal{P}\) if we believe reality follows \(\mathsf{Q}\).

Joint work with Martin Larsson and Aaditya Ramdas

Thursday, 25 April 2024, 19:00 (GMT +2)

Slides to talk:
slides_ruf_240425

Date: Thursday, 21 March 2024

Speaker: Daniel Lacker (Columbia University)

Title: Non-asymptotic perspectives on mean field approximations and stochastic control

Abstract: The main focus of this talk is the analysis of high-dimensional stochastic control problems in which many agents cooperate to minimize a convex cost functional. Our main results are sharp yet general bounds on the optimality gap between the full-information problem, in which each agent observes the states of all other agents, versus the distributed problem, in which each agent observes only its own state. Being decidedly non-asymptotic, our approach avoids structural constraints like exchangeability which are normally required in order to identify limiting objects, but which rule out network-based models. A protagonist in our approach, dubbed the “independent projection,” is the optimal approximation (in a precise sense) of a given high-dimensional diffusion process by one in which the coordinates are independent. Based in part on joint works with Sumit Mukherjee and Lane Chun Yeung, and with Joe Jackson.

Thursday, 21 March 2024, 19:00 (GMT +1)

Slides to talk:
slides_lacker_240321

Date: Thursday, 22 February 2024

Speaker: Carole Bernard (Grenoble Ecole de Management)

Title: Multivariate Portfolio Choice via Quantiles

Abstract: We first show how the quantile approach used for univariate optimal portfolio choice can be also useful to solve the multivariate case. When the multivariate risk sharing problem (in the absence of a financial market) can be solved explicitly, the multivariate optimal portfolio choice reduces to a one-dimensional problem using the quantile approach. In the general case, we develop a numerical approach to obtain approximate solutions for the multivariate optimal portfolio selection problem. In the case of an optimization of a sum of distortion risk measures (e.g., RVaR) we discuss optimal explicit solutions of the multivariate portfolio choice.

Joint work with Andrea Perchiazzo and Steven Vanduffel

Thursday, 22 February 2024, 19:00 (GMT +1)

Slides to talk:
slides_bernard_240222

Date: Thursday, 25 January 2024

Speaker: Marcel Nutz (Columbia University)

Title: Unwinding Stochastic Order Flow: When to Warehouse Trades

Abstract: We study how to unwind stochastic order flow with minimal transaction costs. Stochastic order flow arises, e.g., in the central risk book (CRB), a centralized trading desk that aggregates order flows within a financial institution. The desk can warehouse in-flow orders, ideally netting them against subsequent opposite orders (internalization), or route them to the market (externalization) and incur costs related to price impact and bid-ask spread. We model and solve this problem for a general class of in-flow processes, enabling us to study in detail how in-flow characteristics affect optimal strategy and core trading metrics. Our model allows for an analytic solution in semi-closed form and is readily implementable numerically. Compared with a standard execution problem where the order size is known upfront, the unwind strategy exhibits an additive adjustment for projected future in-flows. Its sign depends on the autocorrelation of orders; only truth-telling (martingale) flow is unwound myopically. In addition to analytic results, we present extensive simulations for different use cases and regimes, and introduce new metrics of practical interest. (Joint work with Kevin Webster and Long Zhao; preprint available at https://ssrn.com/abstract=4609588)

Thursday, 25 January 2024, 19:00 (GMT +1)

Slides to talk:
slides_nutz_240125


One World Seminars of previous years

2023

2022

2021

2020