Learning to Manage Investment Portfolios beyond Simple Utility Functions

Our ICAIF 2025 paper — a generative model that learns fund managers’ strategies from holdings, without specifying a utility function.

Imitating Fund Managers using GANs

Analysing investment strategies through factor models and machine learning, this article examines fund classifications, portfolio stability, and strategy replication. It highlights systematic differences across investment styles and explores how neural networks can model fund manager behaviour.

Towards Evology: A Market Ecology Agent-Based Model

A workshop paper introducing Evology — an empirically calibrated agent-based model that treats US equity mutual funds as an ecology of competing strategies.

Evology: an Empirically-Calibrated Market Ecology Agent-Based Model for Trading Strategy Search

A workshop paper using Evology — a calibrated market-ecology agent-based model — as a training environment to search for trading strategies.

A Market-Based Approach to Carbon Pricing

A preprint with Yoshua Bengio and colleagues — using retroactive pricing and prediction markets to correct the Social Cost of Carbon.

How Market Ecology Explains Market Malfunction

Our paper on market ecology is out in PNAS — treating trading strategies as species to explain how markets misprice and destabilise.

Mandelbrot Set: Shallow-Regime Sampling Optimizations

Conservative interior tests for the Mandelbrot set — exact cardioid and period-2 checks plus Monte-Carlo-calibrated period-3 disks — that eliminate ~40% of iteration work with zero false positives.

The COS Method for Option Pricing

The Fourier cosine series expansion method for pricing European options. Derives the COS formula from the characteristic function of the log-price process, covers chi and psi payoff coefficients, truncation range selection, and demonstrates convergence under geometric Brownian motion.

Monte Carlo Methods for Option Pricing

Monte Carlo simulation for pricing European, digital and Asian options under Black-Scholes dynamics. Covers convergence properties, antithetic variates, bump-and-revalue sensitivity estimation, and control variates for variance reduction.