mlsanityData to 14 Oct 2026

Risk-Neutral Market Simulation

arXiv 2202.13996 ↗First posted 28 Feb 2022q-fin.CP cs.LG q-fin.GNcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 16 of its 27 references that are in the map. First posted on arXiv 28 Feb 2022.

Builds on

16 of 27 references.

References · 16

  1. 2019Normalizing Flows for Probabilistic Modeling and Inferencecited by 1,323
  2. 2019Neural Spline Flowscited by 596
  3. 2020Flows for simultaneous manifold learning and density estimationcited by 118
  4. 2018Deep Hedgingcited by 108
  5. 2019Quant GANs: Deep Generation of Financial Time Seriescited by 108
  6. 2016Normalizing Flows on Riemannian Manifoldscited by 68
  7. 2021Sig-Wasserstein GANs for Time Series Generationcited by 60
  8. 2019Cubic-Spline Flowscited by 35
  9. 2020A Data-driven Market Simulator for Small Data Environmentscited by 35
  10. 2020A generative adversarial network approach to calibration of local stochastic volatility modelscited by 29
  11. 2019Deep Hedging: Learning to Simulate Equity Option Marketscited by 25
  12. 2020Robust pricing and hedging via neural SDEscited by 22
4 more
  1. 2021Arbitrage-free neural-SDE market modelscited by 19
  2. 2021Multi-Asset Spot and Option Market Simulationcited by 17
  3. 2021Deep Hedging: Learning to Remove the Drift under Trading Frictions with Minimal Equivalent Near-Martingale Measurescited by 11
  4. 2022Estimating risks of option books using neural-SDE market modelscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 0; 2025: 0; 2026: 1.

2 papers.

  1. 2026Generating Financial Time Series by Matching Random Convolutional Featurescited by 1
  2. 2023Sig-Splines: universal approximation and convex calibration of time series generative modelscited by 0