CharlieYPeng/CAST-stock-panels

CAST Stock Panels

Datasets for CAST: A Cross-Asset State-Space Trading System for Drawdown Control in Stock Markets (IEEE ICDM 2026).

• Paper: arXiv:2609.14205
• Code: github.com/FanBroWell/CAST
• Project page: fanbrowell.github.io/CAST

Overview

Four panels of 30 stocks each, daily close prices from January 2005 to April 2025:

Config	Description	Trading days
NASDAQ	U.S. large-cap	5,114
CSI300	Chinese A-share large-cap	4,955
TPX100	Japanese blue-chips	5,022
Global30	Cross-currency basket	5,291

Each config is a wide table: one Date column and 30 price columns named by ticker. There are no missing values.

Global30 mixes currencies (USD, EUR, JPY, GBP, HKD/CNY). In the paper its prices are normalized to the first-day value before backtesting. The other three panels are used as raw prices.

The ticker list and selection method for each panel are in data/<config>.json.

Usage

from datasets import load_dataset

ds = load_dataset("CharlieYPeng/CAST-stock-panels", "NASDAQ", split="train")
df = ds.to_pandas().set_index("Date")

Source and terms

Prices were collected from public market data (Yahoo Finance). They are provided for research and reproducibility only. Use of the underlying price data is subject to the original data provider's terms.

Citation

@misc{peng2026cast,
  title = {{CAST}: A Cross-Asset State-Space Trading System for Drawdown Control in Stock Markets},
  author = {Peng, Yu and Khushi, Matloob and Poon, Josiah},
  year = {2026},
  eprint = {2609.14205},
  archivePrefix = {arXiv},
  primaryClass = {cs.CE},
  doi = {10.48550/arXiv.2609.14205},
  url = {https://arxiv.org/abs/2609.14205},
  note = {Accepted at IEEE International Conference on Data Mining (ICDM 2026)}
}