# Fundamental Trader

Trades news events based on the difference between actual and forecast economic data.

Canonical: https://prismaticalgos.com/compendium/algo/1492-fundamental-trader
Record ID: 1492
Catalog rank: 2006 (reading order, not performance)
Snapshot: 2026-10-31 15:46 UTC
Family: Time, Session & Seasonality (F)
Source: https://www.mql5.com/en/code/8491
Evidence label (unverified): forward_results

## Scope and limitations

These are machine-extracted research records, not verified trading systems. Catalog rank measures specification detail and claimed evidence, not profitability. The catalog extraction pipeline did not independently backtest these records. Its separate selected testing ledger does not validate the wider corpus. Rules, labels and parameters can be incomplete or wrong; consult the original source and its reuse terms.

No endorsement, ownership claim or source-code reuse permission is implied.

## Extraction warnings

Opacity warnings: OPAQUE ENTRY: every entry condition reads a value out of something the source never defined -- a custom-indicator buffer, an iCustom() call, or an author-named score. The rule names the signal without specifying it, so it cannot be reproduced bar-for-bar from this record.
Build warnings: MT4_ONLY: the captured source is MQL4 / written for MetaTrader 4. It needs porting (order functions, indicator handles) before it runs on MT5.

## Recorded profile

- symbols: EURUSD, USDJPY, GBPUSD, USDCHF, AUDUSD, USDCAD, NZDUSD
- timeframes: any
- sessions: any
- market_regime: any

## Indicators

No indicator stack recorded.

## Recorded long-entry rules

- StringToDouble(stActual) > StringToDouble(stForecast)

## Recorded short-entry rules

- StringToDouble(stActual) < StringToDouble(stForecast)

## Recorded exit rules

- wait_time before closing order if enable_close_time is true

## Recorded filters

- Not specified.

## Risk controls

- Stop loss: 3 pips
- Take profit: 3 times the risk
- Position sizing: lot_p based on percent difference between actual and forecast data