Swarnajeeth/Swarnajeeth
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Forex Daily Price
Daily open, high, low and close of 140 currency pairs against the US dollar, one series per pair. 105 of them run back to 2010 or earlier, 31 to the 1990s or before and 13 to 1970-71 (the majors, gold and silver); 24 start in 2025. Volume is always zero: spot currency trades over the counter.
686,963 rows over 140 symbols, 7 columns, covering 1970-01-04 to 2026-11-01. Refreshed monthly.
Strategies Built on This Data
292 papers in the Papers With Backtest catalogue declare this dataset as an input. 260 of them have been coded and run over their own full history. The median replicated Sharpe ratio is +0.21, and 34% clear a t-statistic of 1.96 on their own sample, against 48% across all 4,837 replications in the library.
Some of the strongest results that lean on it:
| Strategy | Sharpe | t-stat | Tested over |
|---|---|---|---|
| Good Carry, Bad Carry | +1.74 | 10.5 | 36 years |
| Lessons from the Evolution of Foreign Exchange Trading Strategies | +1.24 | 7.3 | 34 years |
| Bitcoin Price Dynamics: The Stark Contrast between P2P and Exchange Trading | +2.03 | 7.2 | 13 years |
| Differential Rates and Transaction Costs A Toolkit for Practitioners, Accountants and Financial Economists | +1.02 | 6.1 | 36 years |
A Sharpe ratio quoted without its t-statistic hides how much of the library cannot be distinguished from zero, which is why both are shown. The figures are in-sample over each strategy's own window and carry no transaction costs.
Why It Matters
This dataset underpins FX trading strategies and macro overlays by:
- Carry and trend strategies: Daily OHLCV supports momentum and carry screens across majors and crosses.
- Macro hedging: FX moves transmit global macro shocks that can hedge or confirm signals in other asset classes.
- Long history: 13 series going back to 1970-71, long enough to cover the end of Bretton Woods, the euro's introduction and three decades of carry.
Load It
Installation/Upgrade:
pip install --upgrade pwb-toolbox
Load the Dataset:
from pwb_toolbox import datasets as pwb_ds
df = pwb_ds.load_dataset("Forex-Daily-Price", symbols=["EURUSD"])
print(df.iloc[0, :])
Example Output:
symbol EURUSD
date 1975-01-02
open 2.6202
high 2.6202
low 2.6202
close 2.6202
volume 0
Columns
| Column Name | Description |
|---|---|
| symbol | Currency pair, base then quote (EURUSD, USDJPY). Each pair appears once, in one direction. load_dataset returns the USD... pairs inverted and renamed, in dollars per unit: ask for USDJPY, receive JPYUSD. |
| date | Trading date (YYYY-MM-DD). |
| open | Opening FX rate for the session. |
| high | Highest FX rate observed during the session. |
| low | Lowest FX rate observed during the session. |
| close | Closing FX rate for the session. |
| volume | Always zero. Spot currency trades over the counter, so there is no consolidated tape to report. |
Access
Browsing the card and the schema is open to anyone. Downloading the files needs an approved request, tied to a subscription: what each plan includes. The same subscription covers the other datasets in this organisation.
Elsewhere
- Dataset page and coverage charts
- The strategy catalogue, 3,806 papers and 4,837 replicated strategies
pwb-toolbox, the loader used in the snippet aboveawesome-systematic-trading, the replicated strategies with their measured Sharpe- Every dataset in this organisation
Papers With Backtest publishes 32 datasets on the Hub and codes the papers that use them. Every strategy in the catalogue is run over its own full history before it is published, which is where the numbers above come from.
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