See what the math says it takes to reach 100x

What's in the database

Two datasets, one query-credit balance

• 6 timeframes: M1, M5, M15, H1, H4, and D1.
• 10 major FX pairs covered: EUR/USD, GBP/USD, USD/JPY, AUD/USD, USD/CHF, USD/CAD, NZD/USD, EUR/GBP, GBP/JPY, and EUR/JPY.
• Strategies include: RSI, MACD, Bollinger Bands, Ichimoku, Stochastic, Parabolic SAR, Williams %R, CCI, Awesome Oscillator, Bull Bear Power, Momentum, Ultimate Oscillator, Keltner Channels, and Advance/Decline Ratio, alongside multiple settings of SMA and EMA crossovers.
• Exact risk settings: Each result row includes the exact stop-loss and take-profit settings used for that signal or crossover setup.
• Historical dataset: 635,000+ result rows simulated from 1 January 2019 through 31 December 2025 for long-term strategy comparison.
• Quarterly dataset: Beginning in 2026, each completed calendar quarter is backtested independently using the same strategy families, pairs, and timeframes, tagged with a quarter ID for the QTR Query page, then appended after processing.

Both datasets share the same query-credit balance.

How it works

Three steps from question to ranked answer

1. 1

   Pick a strategy

   Indicators, MA Crossover, or EMA Crossover. Each strategy has its own results table with the right columns for that family.

2. 2

   Filter

   Narrow by pair, timeframe, indicator (for indicator strategies), the minimum-trades threshold, and the Monte Carlo filter that keeps only setups clearing their simulated survival thresholds.

3. 3

   Sort and choose a row size

   Sort by total gain, win rate, Sharpe, Sortino, or reward-to-risk. View 100, 200, or 500 rows per query.

A look inside

ForexIPS™

This is a non-interactive sample of the Query page filters. It shows the controls subscribers use to narrow and rank results — here preset to Indicators on EUR/USD at the H4 timeframe, hiding unprofitable setups. The Monte Carlo filter further narrows the database to setups that clear their simulated survival thresholds.

Scroll horizontally to see all columns.

Methodology

How the data was built

Every row in the database is produced under the same conservative defaults.

• One-bar shift on every indicator.Each signal on bar i is computed using only bar i−1 and earlier, so the simulation does not see information that would not have been visible at decision time.
• Stop-loss assumed first on M1 intrabar ties. When the stop and target both fall inside the same minute bar, the engine assumes the stop printed first. That is the more conservative outcome, by design.
• Recorded fill order on M5 and slower. Higher timeframes carry a per-bar high_first flag, so the engine knows whether the bar's high or low printed first instead of guessing.
• Net of commission. Every gain subtracts a 5 pip per-trade commission before the outcome is stored, so the figure is not a frictionless one. Every loss also has a 5 pip commission charged.
• Entries on the next bar's open. Signals fire at bar close and execute at the open of the following bar, a one-bar delay that mirrors how a real trader would respond.
• The full parameter grid is included.Every stop-loss × take-profit × pair × timeframe combination is in the dataset, including the losers, so the underlying distribution is visible alongside the top of the list.