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Datasets:
leiyv
/
marketdata

Tasks:
Time Series Forecasting
Size:
10M<n<100M
Tags:
financial
prediction-market
polymarket
time-series
License:
Dataset card Files
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YAML Metadata Warning: The task_categories "regression" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

Polymarket时间序列预测数据集

数据集描述

这是一个从Polymarket提取的时间序列预测数据集，用于训练WaveNet模型预测未来市场走势。

数据集统计

  • 总样本数: 6,780,504
  • 特征维度: 1,500 (100个时间段 × 15个因子)
  • 标签维度: 10 (预测未来10个时间段)
  • 文件大小: ~12.36 GB
  • 格式: Parquet

特征描述

每个样本包含：

  • 特征: 100个历史时间段的15个因子特征 (1,500维)
  • 标签: 未来10个时间段的response_zscore (10维)
  • 市场ID: 标识数据来源的市场

15个因子

  1. price_std_zscore - 价格标准差
  2. price_trend_zscore - 价格趋势
  3. price_skew_zscore - 价格偏度
  4. price_range_zscore - 价格范围
  5. vol_sum_abs_zscore - 成交量总和
  6. vol_std_zscore - 成交量标准差
  7. vol_flow_zscore - 成交量流
  8. vwap_zscore - 成交量加权平均价
  9. weighted_volatility_zscore - 加权波动率
  10. vol_price_corr_zscore - 量价相关性
  11. energy_zscore - 能量
  12. flow_ratio_zscore - 流动比率
  13. imbalance_intensity_zscore - 不平衡强度
  14. vwap_diff_prev_zscore - VWAP差分
  15. vwap_slope_ma5_zscore - VWAP斜率

数据分割

  • 训练集: 80%
  • 验证集: 10%
  • 测试集: 10%

使用方法

使用Hugging Face Datasets 

from datasets import load_dataset

dataset = load_dataset("chaoleiyv/marketdata", split="train")

直接使用Parquet文件 

import pandas as pd

df = pd.read_parquet("ml_dataset.parquet")

数据集结构 

ml_dataset/
├── ml_dataset.parquet  # 完整数据集（Parquet格式）
└── README.md           # 数据集说明

引用

如果使用本数据集，请引用：

@dataset{polymarket_ml_dataset,
  title={Polymarket时间序列预测数据集},
  author={chaoleiyv},
  year={2025},
  url={https://huggingface.co/datasets/chaoleiyv/marketdata}
}

许可证

MIT License

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