---
license: mit
language:
- en
size_categories:
- 1GB < n < 10GB
tags:
- finance
- portfolio-management
- multi-asset
- benchmark
- LLM
- correlation
---

[![Paper](https://img.shields.io/badge/arXiv-2605.27887-b31b1b)](https://arxiv.org/abs/2605.27887)
[![Code](https://img.shields.io/badge/GitHub-PortBench-blue)](https://github.com/AgenticFinLab/portbench)
[![Homepage](https://img.shields.io/badge/Homepage-portbench.github.io-orange)](https://portbench.github.io/)

# PortBench-RawData

This repository contains the **raw collected data and preprocessed asset files** for [PortBench](https://github.com/AgenticFinLab/portbench). 

The data spans **2015–2025** across **six heterogeneous asset classes**: Equities, Bonds, Commodities, Real Estate, Cryptocurrency, and Cash.

---

## Repository Structure

```
PortBench-RawData/
├── raw_data/                          # Raw collected data (~4.6 GB)
│   ├── fred/                          # FRED macroeconomic indicators (60 series)
│   │   ├── bonds/                     # Yield curve, credit spreads, TIPS
│   │   ├── cash/                      # Fed funds rate, CPI, GDP, employment
│   │   ├── commodities/               # Oil, gold, agriculture spot indices
│   │   └── real_estate/               # Case-Shiller, HPI, REIT indices
│   ├── kaggle/                        # Kaggle supplementary data (~4 GB)
│   │   ├── commodities/               # Commodity futures and spot prices
│   │   ├── cryptocurrency/            # Crypto OHLCV data
│   │   ├── equities/                  # Stock data with news text
│   │   └── real_estate/               # REIT and property data
│   ├── sec/                           # SEC EDGAR filings
│   │   └── equities/                  # 10-K, 10-Q filings for US equities
│   ├── yahoo/                         # Yahoo Finance price data
│   │   ├── bonds/                     # Bond ETF prices and yields
│   │   ├── cash/                      # Money market and treasury ETF data
│   │   ├── commodities/               # Commodity ETF data
│   │   ├── cryptocurrency/            # Crypto ETF and trust data
│   │   ├── equities/                  # 72 tickers (broad-market, sector, factor ETFs)
│   │   └── real_estate/               # REIT ETF data
│   └── metadata.json                  # Dataset metadata summary
│
└── processed/                         # Preprocessed asset data
    ├── equities.csv                   # 126 equity tickers, aligned daily
    ├── bonds.csv                      # 15 bond series, aligned daily
    ├── commodities.csv                # 16 commodity series, aligned daily
    ├── real_estate.csv                # 10 real estate series, aligned daily
    ├── cryptocurrency.csv             # 12 cryptocurrency series, aligned daily
    ├── cash.csv                       # 4 cash equivalent series, aligned daily
    ├── correlation_matrix.csv         # 183×183 Pearson correlation matrix
    ├── asset_class_map.json           # Ticker-to-asset-class mapping
    └── time_ranges.json               # Per-ticker date coverage ranges
```

---

## Data Sources

| Source | Coverage | Content | Tickers/Series |
|--------|----------|---------|----------------|
| [Yahoo Finance](https://finance.yahoo.com/) | 2015–2025 | Daily OHLCV, adjusted close, volume for ETFs and stocks across all 6 asset classes | 72 tickers |
| [FRED](https://fred.stlouisfed.org/) | 2015–2025 | Macroeconomic indicators: yield curve (DGS1–DGS30), TIPS real yields (DFII5/10/30), breakeven inflation (T5YIE/T10YIE), Fed funds rate (DFF/FEDFUNDS), CPI (CPIAUCSL/CPILFESL), GDP, employment (PAYEMS), housing (CSUSHPINSA), VIX | 60 series |
| [Kaggle](https://www.kaggle.com/) | 2015–2025 | Supplementary cryptocurrency OHLCV, commodity futures, equities with news sentiment, real estate data | ~45 datasets |
| [SEC EDGAR](https://www.sec.gov/edgar/) | 2015–2025 | 10-K and 10-Q filings for US equities, parsed text | Equity filings |

---

## Coverage by Asset Class

| Asset Class | Raw Tickers | Processed | Role in Portfolio |
|-------------|------------|-----------|-------------------|
| **Equities** | 127 | 126 | Return engine; diversified via sector/factor ETFs (SPY, QQQ, XLE, XLF, VXUS, etc.) |
| **Bonds** | 15 | 15 | Fixed-income hedging; Treasury, corporate, high-yield (TLT, IEF, HYG, LQD, etc.) |
| **Commodities** | 16 | 16 | Inflation hedge; gold, oil, natural gas, agriculture (GLD, USO, UNG, DBC, etc.) |
| **Real Estate** | 10 | 10 | Diversification; REIT sector ETFs (VNQ, IYR, SCHH, etc.) |
| **Cryptocurrency** | 12 | 12 | High-risk allocation; major + mid-cap (BTC, ETH, SOL, DOGE, etc.) |
| **Cash** | 4 | 4 | Capital preservation; money market, short-term Treasuries (BIL, SGOV, SHV) |

Cross-asset correlations exhibit the key structural property exploited by PortBench's dual-layer scoring: **intra-class correlations are strongly positive** (0.4–0.6+), while **inter-class correlations are near-zero or negative**, meaning true diversification requires cross-class allocation, not just many tickers within one class.

---

## Preprocessing Details

- **Calendar alignment**: All series aligned to a common business-day calendar; gaps ≤5 days forward-filled; longer gaps retained as NaN for pairwise-complete correlation estimation.
- **Market regime labels**: Each asset class labeled as bull/bear/sideways/crisis using MA crossover (50/200-day) + 15% max-drawdown crisis threshold.
- **Data splits**: Train (2015–2022), Validation (2023–2024), Test (2025), with year-end boundaries.
- **Correlation matrix**: 183×183 Pearson correlation matrix computed from daily simple returns over the full training period using pairwise-complete observations; frozen and not re-estimated.

---

## Related Datasets

This repository contains the raw data foundation. See also:

- [PortBench-Market](https://huggingface.co/datasets/AgenticFinLab/PortBench-Market) — The processed market base dataset (`portbench.csv`) with all six asset classes merged at daily frequency, plus visualization figures.
- [PortBench-QA](https://huggingface.co/datasets/AgenticFinLab/PortBench-QA) — 6,269 question-answer pairs across 7 templates (T1–T7) probing correlation-based financial reasoning, with train/val/test splits.

Both are part of the [PortBench collection](https://huggingface.co/collections/AgenticFinLab/portbench).

---

## Citation

```bibtex
@article{zhao2026portbench,
  title={PortBench: A Correlation-Aware, Full-Pipeline Benchmark for LLM-Driven Portfolio Management},
  author={Zhao, Yuxuan and Chen, Sijia and Su, Ningxin},
  journal={arXiv preprint arXiv:2605.27887},
  year={2026}
}
```

---

## License

This dataset is released under the MIT License. Data sourced from Yahoo Finance, FRED, Kaggle, and SEC EDGAR is subject to their respective terms of service.