Risk-Neutral Market Simulation
This work provides a domain-specific tool for financial modeling, offering an incremental improvement in market simulation techniques.
The authors tackled the problem of simulating risk-neutral spot and equity option markets for a single underlying by developing a martingale-based simulator that eliminates conditional drifts and closely matches historical data, achieving high fidelity as measured by Kullback-Leibler divergence.
We develop a risk-neutral spot and equity option market simulator for a single underlying, under which the joint market process is a martingale. We leverage an efficient low-dimensional representation of the market which preserves no static arbitrage, and employ neural spline flows to simulate samples which are free from conditional drifts and are highly realistic in the sense that among all possible risk-neutral simulators, the obtained risk-neutral simulator is the closest to the historical data with respect to the Kullback-Leibler divergence. Numerical experiments demonstrate the effectiveness and highlight both drift removal and fidelity of the calibrated simulator.