---
license: other
license_name: research-only
license_link: LICENSE
pretty_name: CAST Stock Panels
task_categories:
  - time-series-forecasting
tags:
  - finance
  - stock-market
  - portfolio
  - time-series
  - kalman-filter
size_categories:
  - 1K<n<10K
configs:
  - config_name: NASDAQ
    data_files: data/NASDAQ.parquet
    default: true
  - config_name: CSI300
    data_files: data/CSI300.parquet
  - config_name: TPX100
    data_files: data/TPX100.parquet
  - config_name: Global30
    data_files: data/Global30.parquet
---

# 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](https://arxiv.org/abs/2609.14205)
- Code: [github.com/FanBroWell/CAST](https://github.com/FanBroWell/CAST)
- Project page: [fanbrowell.github.io/CAST](https://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

```python
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

```bibtex
@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)}
}
```