Synthetic Dataset for Heston Model Calibration

该数据集包含了为训练、验证和测试神经网络定价欧式期权而生成的合成Heston模型输入参数。数据集采用了随机拉丁超立方抽样方法生成，以确保输入参数空间的全面覆盖。它包含了θ、κ、σ、ρ和v0等参数的不同范围，以便在使用深度学习技术校准随机波动率模型的任务中发挥重要作用。

This dataset comprises synthetic input parameters for the Heston model, generated for training, validating, and testing neural networks for European option pricing. It was created using random Latin hypercube sampling to ensure comprehensive coverage of the input parameter space. The dataset includes varying ranges of parameters such as θ, κ, σ, ρ, and v0, and plays a critical role in tasks involving the calibration of stochastic volatility models with deep learning techniques.