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09/04/2023
ATMS: Algorithmic Trading-Guided Market Simulation
The effective construction of an Algorithmic Trading (AT) strategy often...
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07/04/2023
On the Constrained Time-Series Generation Problem
Synthetic time series are often used in practical applications to augmen...
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07/03/2023
MADS: Modulated Auto-Decoding SIREN for time series imputation
Time series imputation remains a significant challenge across many field...
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06/22/2023
Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustness
Limit order books are a fundamental and widespread market mechanism. Thi...
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06/12/2023
Deep Gaussian Mixture Ensembles
This work introduces a novel probabilistic deep learning technique calle...
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02/23/2023
K-SHAP: Policy Clustering Algorithm for Anonymous State-Action Pairs
Learning agent behaviors from observational data has shown to improve ou...
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11/17/2022
DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift
In electronic trading markets, limit order books (LOBs) provide informat...
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09/26/2022
Learning to simulate realistic limit order book markets from data as a World Agent
Multi-agent market simulators usually require careful calibration to emu...
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09/22/2022
StyleTime: Style Transfer for Synthetic Time Series Generation
Neural style transfer is a powerful computer vision technique that can i...
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08/11/2022
HyperTime: Implicit Neural Representation for Time Series
Implicit neural representations (INRs) have recently emerged as a powerf...
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12/03/2021
Efficient Calibration of Multi-Agent Market Simulators from Time Series with Bayesian Optimization
Multi-agent market simulation is commonly used to create an environment ...
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10/27/2021
ABIDES-Gym: Gym Environments for Multi-Agent Discrete Event Simulation and Application to Financial Markets
Model-free Reinforcement Learning (RL) requires the ability to sample tr...
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10/25/2021
Towards Realistic Market Simulations: a Generative Adversarial Networks Approach
Simulated environments are increasingly used by trading firms and invest...
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08/02/2021
Learning who is in the market from time series: market participant discovery through adversarial calibration of multi-agent simulators
In electronic trading markets often only the price or volume time series...
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05/27/2021
Calibrating Over-Parametrized Simulation Models: A Framework via Eligibility Set
Stochastic simulation aims to compute output performance for complex mod...
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12/10/2019
Get Real: Realism Metrics for Robust Limit Order Book Market Simulations
Machine learning (especially reinforcement learning) methods for trading...
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06/05/2019