PortBench
Collection
PortBench: A Correlation-Aware, Full-Pipeline Benchmark for LLM-Driven Portfolio Management • 2 items • Updated
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PortBench Market Base Dataset
Dataset Description
A ten-year (Jan 2015–Dec 2025) daily financial dataset covering 183 instruments across six heterogeneous asset classes, designed for multi-asset portfolio management research and LLM evaluation.
Asset Coverage
| Asset Class | Instruments | Data Fields | Sources |
|---|---|---|---|
| Equities | 126 | OHLCV + return | Yahoo Finance (ETFs: broad market, sector, factor, international) |
| Bonds | 16 | Close + return (ETFs); yield levels (FRED) | Yahoo Finance, FRED |
| Commodities | 16 | OHLCV + return | Yahoo Finance, Kaggle (spot prices) |
| Real Estate | 10 | OHLCV + return (REITs); housing indices (FRED) | Yahoo Finance, FRED |
| Cryptocurrency | 12 | OHLCV + return | Yahoo Finance, Kaggle (market cap, supply) |
| Cash | 4 | Close + return (money market ETFs); macro indicators (FRED) | Yahoo Finance, FRED |
Additional Features
- Macroeconomic indicators (FRED): Fed funds rate, CPI, unemployment, GDP, yield curve spreads, breakeven inflation, credit spreads, mortgage rates, VIX, and 40+ additional series
- News text: monthly aggregated financial news for equities and cryptocurrency (JSON-encoded columns)
- Cross-asset correlation structures: intra-class and inter-class correlation matrices available as companion artifacts
Dataset Structure
Single CSV file with 4,017 rows (trading days) × 1,087 columns.
Column naming convention: {asset_class}_{ticker}_{field}
date,equities_ACWI_open,equities_ACWI_high,...,bonds_FRED_DGS10,...,cash_FRED_FEDFUNDS,...
2015-01-02,52.34,52.45,...,2.17,...,0.11,...
...
2025-12-31,...
Fields per instrument (where applicable): open, high, low, close, volume, return
Temporal Coverage
- Full range: 2015-01-02 to 2025-12-31
- Frequency: Daily (trading days)
- Three stress windows highlighted: 2015 China Shock (Aug 2015–Feb 2016), 2020 COVID Crash (Feb–May 2020), 2022 Crypto Collapse (May–Dec 2022)
Intended Use
This dataset serves as the foundation for PortBench's dual-layer evaluation. It supports:
- Static QA generation for financial reasoning tasks
- Dynamic five-stage pipeline evaluation with realistic market replay
- Stress testing under historical crisis regimes
- Cross-asset correlation analysis and portfolio optimization research
Point-in-Time (PiT) Constraint
All features strictly respect temporal integrity — no look-ahead bias. Any derived feature uses only information available at or before the corresponding date.
Citation
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