
arXiv: 2202.13996
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.
FOS: Computer and information sciences, Computer Science - Machine Learning, Computational Finance (q-fin.CP), Machine Learning (stat.ML), Machine Learning (cs.LG), FOS: Economics and business, Quantitative Finance - Computational Finance, Statistics - Machine Learning, Risk Management (q-fin.RM), Quantitative Finance - General Finance, General Finance (q-fin.GN), Quantitative Finance - Risk Management
FOS: Computer and information sciences, Computer Science - Machine Learning, Computational Finance (q-fin.CP), Machine Learning (stat.ML), Machine Learning (cs.LG), FOS: Economics and business, Quantitative Finance - Computational Finance, Statistics - Machine Learning, Risk Management (q-fin.RM), Quantitative Finance - General Finance, General Finance (q-fin.GN), Quantitative Finance - Risk Management
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