Forex calls
A daily read on 21 currency pairs. Each pair gets one score from -100 to +100 built from trend, the interest-rate gap between the two central banks, how fast each bank is moving, and value against the five-year average. Above +25 the call is bullish for the first currency, below -25 bearish, in between neutral. Open any row for the reasons, the risk levels and how the model would have done before. How the calls are made.
Today at a glance
Updated each night after the markets close. The last price of the day can be a partial day. A call is research, not advice: see the limits below.
Currency strength
How each major currency moved against the other seven, averaged across the pairs below. Green bars mean the currency gained, red that it lost.
Calls that changed in the past 10 days
US dollar
| Pair | Price | Call | Score |
|---|---|---|---|
| US Dollar Index (DXY) | 101.837 | Bullish | +35 |
Majors
Crosses
Emerging
Does it work? The honest answer
We replayed the model from 2010 to today across 20 pairs, using only the data available on each day, one position per instrument, rebalanced monthly, with trading costs and the interest earned or paid on each position . Pooled and equal-weighted:
| Strategy | Return a year | Risk (volatility) | Return per unit of risk |
|---|---|---|---|
| Follow the model's calls | +0.9% | 2.8% | 0.32 |
| Always long the first currency of each pair | +0.8% | 2.7% | 0.28 |
*A t-value of about 2 or more is the usual bar for calling a result statistically reliable; below that, luck cannot be ruled out. The model's edge here is small and not statistically proven. The split into an early half (2010 to 2017) and a later half (2018 onwards) is on the method page, together with what each ingredient contributed. Hypothetical results, before taxes, using fund prices for energy and farm goods; not a promise and not advice.
Risk warning. These are educational research views built from prices, interest rates and positioning data, not personal advice and not an invitation to trade. Forex and commodity trading, especially with leverage, carries a high risk of losing money quickly, and the large majority of retail accounts that trade leveraged products lose money. Past behaviour of a model does not predict the future.