Large-Scale Simulation of Multi-Asset Ising Financial Markets
We perform a large-scale simulation of an Ising-based financial market model that includes 300 asset time series. The financial system simulated by the model shows a fat-tailed return distribution and volatility clustering and exhibits unstable periods indicated by the volatility index measured as the average of absolute-returns. Moreover, we determine that the cumulative risk fraction, which measures the system risk, changes at high volatility periods. We also calculate the inverse participation ratio (IPR) and its higher-power version, IPR6, from the absolute-return cross-correlation matrix. Finally, we show that the IPR and IPR6 also change at high volatility periods.
Code (0)
등록된 구현이 없습니다.
Tasks
ClusteringTime SeriesTime Series AnalysisSimilar Papers 제목 키워드 기반
Large Scale Probabilistic Simulation of Renewables Production
We develop a probabilistic framework for joint simulation of short-term electricity generation from renewable assets. In this paper we describe a method for producing hourly day-ahead scenarios of generated power at grid…
ClusteringUncertainty QuantificationAsset Harvester: Extracting 3D Assets from Autonomous Driving Logs for Simulation
Closed-loop simulation is a core component of autonomous vehicle (AV) development, enabling scalable testing, training, and safety validation before real-world deployment. Neural scene reconstruction converts driving log…
Autonomous DrivingManiTwin: Scaling Data-Generation-Ready Digital Object Dataset to 100K
Learning in simulation provides a useful foundation for scaling robotic manipulation capabilities. However, this paradigm often suffers from a lack of data-generation-ready digital assets, in both scale and diversity. In…
EmbodiedGen V2: An Agentic, Simulation-Ready 3D World Engine for Embodied AI
We present EmbodiedGen V2, a generative 3D world engine for building executable policy-ready environments for embodied intelligence. Sim-ready 3D asset generation has advanced rapidly, yet assembling such assets into pol…
Reinforcement LearningExperimental Analysis of Deep Hedging Using Artificial Market Simulations for Underlying Asset Simulators
Derivative hedging and pricing are important and continuously studied topics in financial markets. Recently, deep hedging has been proposed as a promising approach that uses deep learning to approximate the optimal hedgi…