LMF Seminars
Autumn 2026 @ Imperial (Oct-Dec)
Date: Thursday, October 8, 2026
Time: 4-5pm
Location: Room HXLY 140, Huxley Building, Imperial College London
Speaker: Caroline Hillairet (ENSAE-CREST, IP Paris)
Title: Multivariate Self-Exciting Processes with Dependencies and application to cyber loss processes
Abstract: We introduce the class of multidimensional self-exciting processes with dependencies (MSPD), which is a unifying writing for a large class of processes: counting, loss, intensity, and also shifted processes. The framework takes into account dynamic dependencies between the frequency and the severity components of the risk, and therefore induces theoretical challenges in the computations of risk valuations. We present a general method for calculating different quantities related to these MSPDs, which combines the Poisson imbedding, the pseudo-chaotic expansion and Malliavin calculus. The methodology is illustrated on cyber loss process and the computation of cyber stress scenarios, based on the accumulation of claims or vulnerabilities.
Date: Thursday, October 8, 2026
Time: 5-6pm
Location: Room HXLY 140, Huxley Building, Imperial College London
Speaker: Martin Herdegen (University of Stuttgart)
Title: Optimal Investment and Consumption in Financial Markets with Integrated Variance Clocks
Abstract: We study the infinite-horizon optimal investment and consumption problem in a general class of continuous financial markets, where uncertainty is driven by a continuous non-decreasing stochastic clock representing accumulated variance. This framework encompasses classical Markovian and non-Markovian stochastic volatility models as well as singular realized-variance models in which no spot volatility process exists. We characterize the value process and optimal investment and consumption strategies in terms of a non-linear infinite-horizon backward stochastic differential equation driven jointly by calendar time and the stochastic clock. We develop a general well-posedness theory for this new class of IVC-BSDEs based on the method of sub- and supersolutions, establishing existence, uniqueness, and stability under natural conditions that might be of independent interest beyond the financial application at hand. We are moreover able to identify the sign of the $Z$-component of the solution using Malliavin calculus. We then apply our results to Volterra Heston models with locally integrable kernels, covering both rough and hyper-rough regimes. Exploiting the affine structure of the model, we verify the optimality of the candidate strategies in incomplete markets and obtain an explicit representation of the solution in the complete market case. Owing to the generality of the framework and the weak assumptions imposed on the stochastic clock, our results unify and extend several existing results for optimal investment and consumption, including classical Markovian stochastic volatility models. The talk is based on joint work with Eduardo Abi Jaber, Florian Gutekunst and David Hobson.
Date: Thursday, October 22, 2026
Time: 4-5pm
Location: Room HXLY 140, Huxley Building, Imperial College London
Speaker: Yihan Zhou (Adam Smith Business School, University of Glasgow)
Title: TBA
Abstract: TBA
Date: Thursday, October 22, 2026
Time: 5-6pm
Location: Room HXLY 140, Huxley Building, Imperial College London
Speaker: TBA
Title: TBA
Abstract: TBA
Date: Thursday, November 5, 2026
Time: 4-5pm
Location: Room HXLY 140, Huxley Building, Imperial College London
Speaker: Roxana Dumitrescu (ENSAE Paris)
Title: TBA
Abstract: TBA
Date: Thursday, November 5, 2026
Time: 5-6pm
Location: Room HXLY 140, Huxley Building, Imperial College London
Speaker: Alvaro Cartea (University of Oxford)
Title: AI Bubbles with Large Language Models
Abstract: AI agents participate in both rational and irrational bubbles. In a sequential bubble game, AI agents generate speculative trades even though there is a unique no-trade equilibrium. Increasing reasoning capacity reduces this speculation. Chain-of-thought analysis shows that AI agents speculate because they form incorrect beliefs through simplified views of the market. AI agents also condition on the labels of their counterparties, so mispricing can arise from whom an agent believes it faces, and not only from how well it reasons through the strategic problem. When the environment further admits a speculative bubble equilibrium, AI agents recognize this multiplicity and coordinate on the speculative equilibrium. Our results suggest that the relationship between AI sophistication and market efficiency is not monotonic: greater sophistication need not eliminate bubbles or improve efficiency.
Date: Thursday, November 19, 2026
Time: 4-5pm
Location: Room HXLY 140, Huxley Building, Imperial College London
Speaker: Milena Vuletic (QRT)
Title: TBA
Abstract: TBA
Date: Thursday, November 19, 2026
Time: 5-6pm
Location: Room HXLY 140, Huxley Building, Imperial College London
Speaker: Julien Guyon (École des Ponts)
Title: TBA
Abstract: TBA
Date: Thursday, December 3, 2026
Time: 4-5pm
Location: Room HXLY 140, Huxley Building, Imperial College London
Speaker: Mogens Steffensen (University of Copenhagen)
Title: TBA
Abstract: TBA
Date: Thursday, December 3, 2026
Time: 5-6pm
Location: Room HXLY 140, Huxley Building, Imperial College London
Speaker: Giorgio Ferrari (Bielefeld University)
Title: TBA
Abstract: TBA
