Redeemer Quant Algo

Redeemer Quant Algo — Strategy Description

Redeemer Quant Algo is a rules-based EMA trend and swing-structure strategy built for educational and research purposes. It operates on a clearly defined framework that evaluates trend direction, sets risk from market structure, and adapts position size through a controlled recovery sequence. The system is designed to demonstrate how disciplined logic can be applied to futures markets without discretionary decision-making.

1. Multi-Timeframe EMA Trend Confirmation

The strategy evaluates directional bias using a fast and slow EMA (default 9 & 21) on the chart timeframe and the same pair on a higher-timeframe filter (default 60-minute).
Long trades are taken only when both EMAs align bullish across multiple timeframes.
Short trades require full bearish alignment.

This dual-layer confirmation helps avoid counter-trend conditions and filters out low-probability setups.

2. Swing-Based Risk Definition + 1R Partial Profit

Risk is defined using recent swing highs or lows from the selected swing length. From this distance, the system calculates a true 1R target.
A partial exit (default 50%) is taken at 1R.
The remaining runner is managed using a trailing EMA to allow participation in extended moves while maintaining disciplined risk control.

This combination of fixed-risk structure and managed runners reflects a realistic, systematic trade-management approach.

3. Loss-Streak-Based Position Sizing

Redeemer uses a rule-driven, capped position-sizing adjustment based on the outcome of the most recent closed trade.
After a profitable leg, position size returns to the default.
After a losing leg, size increases in predefined steps.
After consecutive losses, size increases again up to a user-defined maximum.

This is not martingale; sizing changes are stepped, limited, and intended for research only. Users should adjust all sizing according to personal risk tolerance.

Trade Execution Logic Overview

Detect EMA crossover.

Validate trend alignment using the higher-timeframe filter.

Apply ATR filtering to avoid low-volatility setups.

Set stop at the most recent swing point.

Establish a 1R partial target.

Manage runners using EMA-based trailing logic.

This produces a structured trend-following model with consistent swing-based risk.

Default Properties / Backtesting Considerations

Default settings include:
• Base position size of 2 contracts (or units).
• Stop-loss placement at swing highs/lows.
• Partial exits at 1:1 reward-to-risk.
• ATR filter enabled.
• No pyramiding.
• Recommended use of realistic commissions and slippage.

The strategy is for research and demonstration purposes only and is not financial advice.

Important Notes

• This script is not for sale, and I am not a vendor.
• Shared for learning, transparency, and community discussion.
• Users should test various timeframes and symbols and adjust risk responsibly.
• Past performance does not guarantee future results.
• Forward-test with paper trading before considering live use.

How to Use:

Apply the script to any chart.
Confirm EMA alignment on both chart and HTF.
Check swing-based stop placement and ensure risk fits your account size.
Adjust EMA lengths or ATR threshold as needed for volatility.
Enable commissions and slippage for realistic backtesting.