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London vs New York: A Controlled Session Backtest

Research protocol · Reviewed 24 Aug 2026

London and New York can produce different conditions, but “which session wins” has no stable answer without a pair, setup, dates, clock definition, and execution model. The useful experiment isolates the session while holding the trading rule constant.

Same rule, two clocks

FIELD 32

Match exposure before comparing London and New York

Give each session the same setup definition, sample dates, maximum trades per day, and cost model. Report overlap trades separately and align daylight-saving changes. Otherwise the session label may be standing in for different volatility, news, or opportunity counts.

  1. Define both windows in UTC for every test date.
  2. Pair observations by day or market regime.
  3. Report trades per session and skipped signals.
  4. Reserve a later period to confirm the difference.

A fair session comparison changes the clock and nothing else.

Design a matched comparison

Choose one pair and one mechanical entry rule. Test both windows on the same calendar days where possible, keep risk and exit logic fixed, and tag the London–New York overlap rather than assigning it casually to one side.

What a useful result includes

Report opportunity count, trades taken, net expectancy, drawdown, time in trade, and uncertainty by year or quarter. A later holdout period should decide whether an apparent session difference persisted.

Related

Beginner exploration

Three questions to help you use this page

Open each answer for a plain-language way to read London vs New York: A Controlled Session Backtest, test it carefully and decide what to explore next.

What does “London vs New York: A Controlled Session Backtest” mean for a beginner?

This page focuses on “London vs New York: A Controlled Session Backtest”.A controlled protocol for comparing London and New York forex sessions using matched rules, UTC windows, costs, opportunity counts, and holdout data.For “London vs New York: A Controlled Session Backtest”, a beginner should identify what the research note measures, assumes or teaches before acting on its conclusion.Treat this page's account of “London vs New York: A Controlled Session Backtest” as a learning reference rather than a prediction, signal or promise of future performance.

How should a beginner use this page to explore “London vs New York: A Controlled Session Backtest”?

For “London vs New York: A Controlled Session Backtest”, identify the exact experiment or observation the article reports before borrowing its conclusion.While exploring “London vs New York: A Controlled Session Backtest”, check whether the result came from measured data, an illustrative example or a personal workflow.Keep your “London vs New York: A Controlled Session Backtest” record honest: write down the condition that would make the lesson fail on a different pair or period.Before leaving “London vs New York: A Controlled Session Backtest”, re-test the idea independently instead of treating one article as a universal trading rule.

How can AI help explore “London vs New York: A Controlled Session Backtest” responsibly?

Turn one idea from “London vs New York: A Controlled Session Backtest” into a rule with explicit inputs, dates, costs and pass-or-fail conditions.Ask AI to expose missing assumptions in that “London vs New York: A Controlled Session Backtest” test, not to guess the next market move.Use the FXAbsolute AI Backtesting Lab to inspect calculations connected to “London vs New York: A Controlled Session Backtest” and the assumptions behind them.Reproduce any important “London vs New York: A Controlled Session Backtest” result and reserve unseen data before deciding that an apparent pattern is useful.

Continue your exploration of London vs New York: A Controlled Session Backtest with the beginner AI prompt guide, or inspect public calculations in the AI Backtesting Lab.