2 citations · 2 across the 5 of their papers we have counts for
6 papers
Amortized Optimization for Calibrating Stochastic Social Simulators
Muyao Zhong, Peng Yang
Stochastic simulators need suitable parameter values to reproduce observed behaviour in complex systems. Searching for these values through repeated simulations makes frequent reca…
EvoMarket: A High-Fidelity and Scalable Financial Market Simulator
Muyao Zhong, Zhenhua Yang, Yuxiang Liu +2
High-fidelity, scalable market simulation is a key instrument for mechanism evaluation, stress testing, and counterfactual policy analysis. Yet existing simulators rarely achieve \…
Calibrating Agent-Based Financial Markets Simulators with Pretrainable Automatic Posterior Transformation-Based Surrogates
Boquan Jiang, Zhenhua Yang, Chenkai Wang +3
Calibrating Agent-Based Models (ABMs) is an important optimization problem for simulating the complex social systems, where the goal is to identify the optimal parameter of a given…
Representation Learning of Limit Order Book: A Comprehensive Study and Benchmarking
Muyao Zhong, Yushi Lin, Peng Yang
The Limit Order Book (LOB), the mostly fundamental data of the financial market, provides a fine-grained view of market dynamics while poses significant challenges in dealing with…
SimLOB: Learning Representations of Limited Order Book for Financial Market Simulation
Yuanzhe Li, Yue Wu, Muyao Zhong +2
Financial market simulation (FMS) serves as a promising tool for understanding market anomalies and the underlying trading behaviors. To ensure high-fidelity simulations, it is cru…
Pointer Networks Trained Better via Evolutionary Algorithms
Muyao Zhong, Shengcai Liu, Bingdong Li +3
Pointer Network (PtrNet) is a specific neural network for solving Combinatorial Optimization Problems (COPs). While PtrNets offer real-time feed-forward inference for complex COPs…