FX pairs

[Horizon: T+1 Close]

SELL

GBP / ILS GBPILS=X

Forecasting and modeling

Model input: Bank of Israel · representative exchange rate
Chart feed: TradingView / exchange feed
Rates: Bank of Israel, Bank of England | Macro sentiment: GDELT Project

Latest reference level 4.1624

Active-horizon target 4.1482 -0.34%

Raw interval (bands) S1 4.1167
R1 4.2081

Volatility (σ) 7.9% Assessment (Yesterday for Today): 4.1789

Model quality (out-of-sample) 83.8% Out-of-sample sample: 200 sessions

Why this asset matters

GBP/ILS usually trades with less local attention than USD/ILS, yet it can be informative because it combines sterling-specific repricing with shekel dynamics. That makes it useful when readers want to separate broad Israel risk from currency-specific moves tied to the UK rate cycle and global risk sentiment.

What usually moves this asset

GBP/ILS is often influenced by Bank of England expectations, Bank of Israel policy, global dollar conditions, cross-currency volatility and broader risk appetite. Because it can be less liquid than the main dollar pair, sharp local repricing may appear more uneven.

How to read this page

On GBP/ILS, short-term signals should be read with extra attention to volatility and range width. Direction alone can be misleading when liquidity is thinner.

Methodology and dashboard reading (Model Card)

Model architecture:
Random Forest built on price-based returns, trend-distance, rolling volatility and selected macro market features (DXY, oil, VIX). The news layer is currently contextual and may be excluded from forecast updates.

Horizons (Targets):
T+1: Direct forecast for the currently displayed horizon close.
T+30: Direct horizon forecasts for each trading day up to T+30, displayed as a path.
1M-1Y: Structural scenario layer derived from spot, rates, volatility and macro drift, shown separately from the short-horizon ML block.

Validation:
Walk-forward testing on expanding history without future leakage. Retraining is performed inside each evaluation step.

Trading definition of the signal:

Entry: At spot price (snapshot before model calculation). Exit: At active-horizon close.
Divergence: If the technical trend is falling but the signal is BUY, the model has detected a local oversold condition and is trading a rebound (mean reversion).
Execution risk: The signal is not investment advice and does not include sizing. The model does not account for broker spreads, slippage, or carry costs (swap/rollover for FX).
News risk: At extreme risk sentiment (GDELT), raw bands are not calibrated for outliers. The probability of fat tails increases.

1. Current market regime (Technical & Macro View)

Heuristic regime gauges

Neutral

Decline

Heuristic regime display for page context, not a price-return backfill.

Heuristic regime indicators

46.9 (Neutral)

Trend-bias proxyBullish

Macro / carry biasBelow SMA 50/200

Volatility (σ)7.9%

Display heuristics for current regime reading. Not a full classical technical-indicator calculation.

Volatility (σ)7.9%

Macro factors (Percentile Score)

Values are normalized from 0 to 100

Sentiment (GDELT NLP)

Tension indexN/A

StatusData unavailable

Source: GDELT Project API
Coverage: ~400 media / 24h
Updated: 25.10.2026 02:30 UTC
News-tone classification, not a factual confirmation of the event.

2. Deep quantitative analytics

Historical seasonality

This panel is temporarily hidden while historical monthly returns are being rebuilt from the same source-aligned series used by the model.

A real seasonality heatmap will return after monthly returns are recalculated from the same source-aligned history used by the model.

Forward tilt estimate (CIP + ML bias)

No-arbitrage forward estimate and ML premium (horizon τ = 1 month).

Inputs: BoE base rate: 5.25% | BoI policy rate: 4.50% (as of 25.10.2026)
No-arbitrage CIP Forward: F = S × (1 + r_Quote × τ) / (1 + r_Base × τ)
Drift estimate: CIP forward + ML correction (historical bias)

Latest reference level: 4.1624
Drift estimate: 4.1599

UndervaluedOvervalued

Spot deviation from estimate: 0.06% (Threshold ±1.5%)

Model verdict: Fairly valued

3. ML model assessment (Predictive Analytics)

Historical validation: model forecast vs reality

Bands are nominal (raw). Current empirical out-of-sample coverage: 80.5%. The model is still being calibrated.

For historical validation, this chart uses the same source as the model input: Bank of Israel · representative exchange rate. This removes cross-source shift.

Return-space check: predicted vs realized active-horizon move

This view removes the false level-lag effect and shows the predicted change from the previous close.

ML model summary (tree ensemble)

Attention (Divergence): Technical trend and the ML forecast diverge. The tree ensemble detects local inefficiency and points to a short-term rebound (mean reversion) against the current trend.

Analyzing macroeconomic data, the ML model detects a mild bullish (uptrend) regime on the medium-term horizon. The news-sentiment layer is unavailable in this refresh and is excluded from the narrative interpretation. RSI (46.9) confirms the local structure.

Active-horizon signal: SELL
Return to target: -0.34%

Attention (Risk calibration):
Raw interval. Empirical OOS coverage: 80.5%. Calibration is still required (fat tails).

Directional model accuracy estimate 59%

Empirical coverage 80.5%

4. Probabilities and trading signals

Close probability over a 30-trading-day horizon Mode: Normal (Calm)

Estimate of the probability that price closes above or below target levels exactly after 30 trading days (T+30 sessions). Calculated via Gaussian CDF N(μ, σ). Does not account for skewness or fat tails during geopolitical FX shocks.

Close ABOVE level (Upside)

Level R1 (4.2081)12%

Level R2 (4.2705)3%

Close BELOW level (Downside)

Level S1 (4.1167)58%

Level S2 (4.0543)32%

Trading interpretation of the signal:

Instrument: GBPILS=X
Entry: At current session close (04:30).
Exit: At active-horizon close (26.10).
Model: SELL (Expected return: -0.34%)

Signals are produced exclusively by the ML core and are not investment advice.

Attention: The daily forecast (left) is displayed as direct horizon estimates for each trading day up to T+30. The long-horizon block (right) is a structural scenario layer, so the trajectories can diverge.

Short-horizon ML expectations (daily)

Date	ML target	Raw interval (bands)	Signal
26.10.2026 (Mon)	4.1482	[4.1201 - 4.1766]	SELL
27.10.2026 (Tue)	4.1379	[4.0982 - 4.1779]	SELL
28.10.2026 (Wed)	4.1217	[4.0734 - 4.1706]	SELL
29.10.2026 (Thu)	4.1009	[4.0455 - 4.1572]	SELL
30.10.2026 (Fri)	4.1123	[4.0502 - 4.1754]	SELL
02.11.2026 (Mon)	4.1237	[4.0555 - 4.1931]	SELL
03.11.2026 (Tue)	4.1311	[4.0574 - 4.2062]	SELL
04.11.2026 (Wed)	4.1103	[4.0319 - 4.1902]	SELL
05.11.2026 (Thu)	4.1166	[4.0333 - 4.2015]	SELL
06.11.2026 (Fri)	4.1175	[4.0298 - 4.2071]	SELL
09.11.2026 (Mon)	4.0917	[4.0003 - 4.1852]	SELL
10.11.2026 (Tue)	4.1024	[4.0067 - 4.2003]	SELL
11.11.2026 (Wed)	4.1016	[4.0022 - 4.2036]	SELL
12.11.2026 (Thu)	4.1064	[4.0031 - 4.2123]	SELL
13.11.2026 (Fri)	4.0924	[3.9859 - 4.2017]	SELL
16.11.2026 (Mon)	4.1102	[3.9997 - 4.2236]	SELL
17.11.2026 (Tue)	4.1079	[3.9942 - 4.2248]	SELL
18.11.2026 (Wed)	4.1098	[3.9928 - 4.2303]	SELL
19.11.2026 (Thu)	4.1045	[3.9845 - 4.2282]	SELL
20.11.2026 (Fri)	4.0926	[3.9699 - 4.2192]	SELL
23.11.2026 (Mon)	4.1207	[3.9941 - 4.2513]	SELL
24.11.2026 (Tue)	4.1357	[4.0057 - 4.2699]	SELL
25.11.2026 (Wed)	4.1495	[4.0162 - 4.2873]	SELL
26.11.2026 (Thu)	4.1366	[4.0009 - 4.2770]	SELL
27.11.2026 (Fri)	4.1112	[3.9736 - 4.2536]	SELL
30.11.2026 (Mon)	4.1303	[3.9894 - 4.2762]	SELL
01.12.2026 (Tue)	4.0913	[3.9491 - 4.2387]	SELL
02.12.2026 (Wed)	4.0923	[3.9475 - 4.2424]	SELL
03.12.2026 (Thu)	4.0736	[3.9269 - 4.2257]	SELL

Long-horizon structural expectations

Horizon end	ML target	Delta	Raw interval (bands)	Signal
25.01.2027 (1 quarter)	4.0537	-2.61%	[3.8435 - 4.2710]	SELL
25.04.2027 (6 months)	3.9880	-4.19%	[3.6642 - 4.3291]	SELL
25.10.2027 (1 year)	3.8562	-7.36%	[3.3946 - 4.3553]	SELL

Long horizons are shown as a structural scenario layer built from spot, rates, volatility and macro drift. Read them separately from the short-horizon ML forecast.

5. Research sandbox (Illustrative sensitivity)

Stress-test calculator (What-If Analysis)

Illustrates linear sensitivity to shocks (based on heuristic weights). Under stress, the risk corridor widens (volatility).

Geopolitical shock (GDELT): 0

Crisis (-1)Peace (+1)

US Dollar Index shock (DXY): 0%

DXY down (-10%)DXY up (+10%)

Short-horizon ML forecast (up to 30 trading days)

Long-horizon structural scenario (up to 1 year)

6. Interactive chart (TradingView)

Attention: the base model calculation uses Bank of Israel · representative exchange rate. The chart below shows the TradingView feed (FX_IDC:GBPILS), so small quote differences are possible.

Related market pages

FAQ

What makes GBP/ILS different from USD/ILS?

It carries sterling-specific policy and growth repricing on top of shekel dynamics, so its behavior can diverge from the main dollar pair.

How should I read an active-horizon signal on GBP/ILS?

As a short-horizon directional lean that should always be read together with volatility and support/resistance levels.

Why can GBP/ILS look noisier?

Because cross-currency flows and thinner liquidity can create less even short-term pricing.

Why does the page show validation metrics?

Because signal quality should be judged alongside realized coverage and directional hit rate, not by the headline signal alone.