See inside every stock. Pro
S&P 5007,663▼ 1.21%Nasdaq26,009▼ 2.60%Dow Jones52,868▲ 0.02%Nasdaq 10028,959▼ 2.90%VIX19.03▲ 14.09%US Dollar101.62▼ 0.16%Gold spot4,093▼ 0.80%WTI100.86▲ 1.40%

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

Bullish4
Neutral8
Bearish9
Latest price date22 Oct 2026
Market CompassRisk-on
US 2-year yield4.65%

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.

Browse the currency pairs

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.

Past week

NZD+1.7%
CAD+1.3%
AUD+1.0%
CHF+0.8%
GBP+0.7%
JPY−0.1%
EUR−0.3%
USD−1.0%

Past month

CHF+1.4%
GBP+1.4%
JPY+0.9%
CAD+0.7%
USD−0.1%
NZD−0.5%
AUD−0.8%
EUR−2.0%

Past 3 months

JPY+4.1%
CAD+0.8%
CHF+0.5%
GBP−0.2%
USD−0.5%
NZD−1.5%
AUD−1.8%
EUR−2.3%

Calls that changed in the past 10 days

US dollar

PairPrice1 monthCallScoreConfidenceIn this callRate gap
US Dollar Index (DXY) 101.617 +0.52% Bullish +31 Medium 36d +1.54 pt

Majors

PairPrice1 monthCallScoreConfidenceIn this callRate gap
EUR/USD 1.123421 Oct 2026 −1.88% Bearish −38 Medium 35d −1.38 pt
GBP/USD 1.3397 +1.20% Bearish −20 Medium 13d −0.13 pt
USD/JPY 156.730 −0.99% Neutral −19 Low neutral 83d +2.63 pt
USD/CHF 0.8200 −0.64% Bullish +45 High 141d +3.88 pt
AUD/USD 0.7017 −0.23% Neutral −2 Low neutral 29d +0.72 pt
NZD/USD 0.570321 Oct 2026 −0.46% Bearish −17 Medium 9d −1.13 pt
USD/CAD 1.4007 −0.68% Neutral +9 Low neutral 0d +1.63 pt

Crosses

PairPrice1 monthCallScoreConfidenceIn this callRate gap
EUR/GBP 0.8370 −2.62% Bearish −39 High 156d −1.25 pt
EUR/JPY 177.657 −1.40% Bearish −31 Medium 42d +1.25 pt
GBP/JPY 210.02 +0.20% Neutral −20 Low neutral 49d +2.50 pt
AUD/JPY 110.030 −1.27% Neutral −13 Low neutral 43d +3.35 pt
EUR/CHF 0.9198 −2.08% Neutral +7 Low neutral 0d +2.50 pt

Emerging

PairPrice1 monthCallScoreConfidenceIn this callRate gap
USD/CNH 6.6725 −0.57% Bearish −30 Low 359d +0.88 pt
USD/INR 94.818 −0.97% Neutral +1 Low neutral 9d −1.63 pt
USD/PKR 276.50 +2.89% Bearish −36 Medium 10d −7.63 pt
USD/MXN 18.6913 +6.62% Bullish +26 Low 3d −2.63 pt
USD/ZAR 16.4886 +0.78% Neutral −12 Low neutral 28d −3.38 pt
USD/TRY 49.623 +1.72% Bullish +36 Medium 664d −33.13 pt
USD/BRL 5.0494 −2.34% Bearish −30 Medium 17d −9.88 pt
USD/KRW 1,325.12 −2.99% Bearish −36 Medium 59d +0.88 pt

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:

StrategyReturn a yearRisk (volatility)Return per unit of riskWorst fallConfidence it is real*
Follow the model's calls+0.9%2.8%0.32−7.5%t = 1.3
Always long the first currency of each pair+0.8%2.7%0.28−7.9%t = 1.2

*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.