Deep Calibration of Market Simulations using Neural Density Estimators and Embedding Networks-Reference-Cited by-同舟云学术

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Deep Calibration of Market Simulations using Neural Density Estimators and Embedding Networks

Published:2023-11-25 Issue: Volume: Page:
ISSN:
Container-title:4th ACM International Conference on AI in Finance
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Author:

Stillman Namid R¹^ORCID,Baggott Rory¹^ORCID,Lyon Justin¹^ORCID,Zhang Jianfei²^ORCID,Zhu Dingqui²^ORCID,Chen Tao²^ORCID,Vytelingum Perukrishnen¹^ORCID

Affiliation:

1. Simudyne Limited, United Kingdom

2. Hong Kong Exchanges and Clearing Limited, Hong Kong

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3604237.3626881

Reference42 articles.

1. ABIDES-gym

2. Robert L Axtell and J Doyne Farmer . 2022. Agent-based modeling in economics and finance: past, present, and future. Journal of Economic Literature ( 2022 ). Robert L Axtell and J Doyne Farmer. 2022. Agent-based modeling in economics and finance: past, present, and future. Journal of Economic Literature (2022).

3. Efficient Calibration of Multi-Agent Simulation Models from Output Series with Bayesian Optimization

4. Jean-Philippe Bouchaud and Marc Potters . 2001. More stylized facts of financial markets: leverage effect and downside correlations. Physica A: Statistical Mechanics and its Applications 299, 1-2 ( 2001 ), 60–70. Jean-Philippe Bouchaud and Marc Potters. 2001. More stylized facts of financial markets: leverage effect and downside correlations. Physica A: Statistical Mechanics and its Applications 299, 1-2 (2001), 60–70.

5. Simulation-based inference in particle physics

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