Futures Trend Algo Strategy
Budget: ₹5,000 – ₹10,000 INR
I need a robust, fully-coded trend-following algorithm tailored for index and commodity futures. The goal is to automate short (sell-side) entries and exits, complete with risk management and position sizing logic, so I can deploy it straight into my brokerage platform without manual intervention.
Core requirements
• The strategy must be 100 % trend-following—no mean-reversion or arbitrage logic.
• Results should be reproducible on minute-level historical data and live tick data.
• All parameters (look-back, stop-loss, trail, position size) should be externally configurable so I can fine-tune them later.
Deliverables
1. Clean, well-commented source code in a widely-used language for futures trading (Python, Pine Script, or similar—advise on best fit).
2. A back-test covering at least five years of continuous futures data, with summary metrics (CAGR, max drawdown, Sharpe, win/loss).
3. Forward-test demo or paper-trading proof to confirm the strategy behaves the same live.
4. Brief hand-off guide so I can tweak inputs and roll the code to new contracts myself.
Acceptance criteria
– Net profitability and drawdown numbers must match your back-test within a 5 % tolerance when I run the code on my own machine.
– No repainting or look-ahead bias.
– Execution latency under 500 ms on typical retail hardware.
Timing
I’m ready to start today and I need a first functional version ASAP, with a complete, tested hand-off as soon as practical.
If you have a proven record building futures trend algos, let’s get this running.
Core requirements
• The strategy must be 100 % trend-following—no mean-reversion or arbitrage logic.
• Results should be reproducible on minute-level historical data and live tick data.
• All parameters (look-back, stop-loss, trail, position size) should be externally configurable so I can fine-tune them later.
Deliverables
1. Clean, well-commented source code in a widely-used language for futures trading (Python, Pine Script, or similar—advise on best fit).
2. A back-test covering at least five years of continuous futures data, with summary metrics (CAGR, max drawdown, Sharpe, win/loss).
3. Forward-test demo or paper-trading proof to confirm the strategy behaves the same live.
4. Brief hand-off guide so I can tweak inputs and roll the code to new contracts myself.
Acceptance criteria
– Net profitability and drawdown numbers must match your back-test within a 5 % tolerance when I run the code on my own machine.
– No repainting or look-ahead bias.
– Execution latency under 500 ms on typical retail hardware.
Timing
I’m ready to start today and I need a first functional version ASAP, with a complete, tested hand-off as soon as practical.
If you have a proven record building futures trend algos, let’s get this running.