How to fix your perfect strategy that crashed in live trading.
Most funds throw it away. Smart money fixes the execution.
Step 1: Diagnose the Real Problem
Your algorithm isn't broken.
Your execution framework is.
The core logic that generated alpha in backtests still exists.
Real-world friction is destroying the edge before trades complete.
Don't scrap the strategy. Retrofit it for reality.
Step 2: Widen Your Entry Triggers
Add 2-3 basis points beyond your backtest signal.
Why this works:
- Accounts for execution lag
- Compensates for market movement during order processing
- Ensures favorable fills when conditions shift
Test different basis point ranges until live performance aligns with backtest expectations.
Step 3: Replace Market Orders with Adaptive Limits
Market orders are execution suicide in live trading.
Here's the fix:
- Set limit 1 basis point inside current best bid/ask
- Increment toward market price every 200 milliseconds until filled
- Walk the book instead of hitting it
This protects your edge while ensuring fills.
Step 4: Build Position Sizing That Scales with Liquidity
Your backtest didn't account for market impact.
The solution:
- Cap live positions at 5% of average daily volume
- Adjust based on your AUM
- Don't let your own trades move the market against you
Size kills more strategies than signals ever will.
Step 5: Add Execution Quality Monitoring
Build kill switches before strategies drain capital.
Set up alerts when:
- Live fills run 15+ basis points worse than backtest assumptions
- Execution quality degrades consistently
- Slippage exceeds acceptable thresholds
Halt trading and recalibrate when thresholds are breached.
Step 6: Implement the Patience Protocol
Reduce trade frequency by 30-50%.
Only take your highest conviction signals.
Why this works:
- Better execution on fewer trades
- Reduced transaction costs
- Higher signal-to-noise ratio
Quality beats quantity in live markets.
Step 7: Recalibrate Your Expectations
Your 45% backtest return might deliver 25% live after friction costs.
That's still alpha worth capturing.
Don't chase perfection:
- Expect profitable reality, not backtest glory
- Factor in real-world costs from day one
- Measure success against realistic benchmarks
Step 8: Monitor and Iterate
Track these metrics weekly:
- Live vs backtest performance gap
- Average execution quality
- Position sizing effectiveness
- Signal conviction vs outcomes
Continuously optimize based on live market feedback.
What Not to Do
Don't:
- Throw away strategies after first live failure
- Increase position sizes to "make up" losses
- Ignore execution quality metrics
- Chase every signal your backtest flagged
Most failures are execution problems, not strategy problems.
The Reality Check
Markets move faster than ever.
Execution gaps cost more than bad signals.
The funds that survive understand: → Execution is strategy.
Why This Framework Works
At autotradelab, we've used this approach to salvage many strategies that initially failed live.
The pattern is always the same:
- Good logic buried under execution problems
- Simple fixes that preserve the edge
- Realistic expectations that deliver consistent alpha
Our systems automatically implement many of these fixes at the infrastructure level.
The Bottom Line
Don't throw away good logic because of bad execution.
Fix the plumbing, keep the engine.
Because the difference between backtest glory and live profits isn't your math.
→ It's following this framework.