Example Report
Transaction Cost Sensitivity Report Example
How FiClaw compares strategy performance under different fee, slippage and turnover assumptions to judge whether backtest return survives real trading costs.
Sample prompt
“Run a transaction-cost sensitivity analysis on a momentum rotation strategy, comparing annual return, Sharpe, max drawdown and turnover under 0, 5, 10 and 20 bps cost assumptions.”
Backtest setup
Baseline
Momentum rotation
Fixed signal and rebalance rule, only cost varies
History
Up to 10 yr+
Used to observe long-run turnover and cost accumulation
Cost scenarios
0-20 bps
Covers a fee and slippage stress test
Focus
Net-return decay
Judge whether return is eaten by turnover cost
Strategy summary
Using the momentum rotation strategy as the baseline, the report fixes the strategy logic and rebalance rule and only varies the trading fee and slippage assumptions, observing how net return, Sharpe, max drawdown and turnover change, to judge whether the strategy over-relies on a low-cost assumption.
Code highlights
- Generate a cost-scenario table with 0, 5, 10 and 20 bps trading-cost assumptions.
- Keep the strategy signal unchanged and batch-submit backtests under each cost convention.
- Output net-return decay, Sharpe change and turnover impact on return.
Key metrics
Baseline Sharpe
1.08
Low-cost example convention
High-cost Sharpe
0.71
Clearly lower under the 20 bps scenario
Annual decay
-4.6pp
Cost rising from 5 bps to 20 bps
Monthly turnover
38%
The main source of cost sensitivity
Diagnosis
- The strategy is acceptable under a low-cost assumption, but Sharpe drops clearly in the high-cost scenario.
- Turnover is the main source of net-return decay; consider lower-frequency rebalancing or a holding-count cap.
- If live trading cost is higher than the backtest assumption, the original return conclusion should not be taken at face value.
Next steps
- Lower the rebalance frequency and compare net return and max drawdown changes.
- Add a turnover cap or a holding buffer to cut ineffective trades.
- Re-run the out-of-sample window with a conservative cost assumption.
Citable facts
- The transaction-cost sensitivity report shows how FiClaw brings fees, slippage and turnover into one backtest diagnosis.
- This example is used to judge whether strategy return holds up under a more conservative cost assumption.
- FiClaw recommends cost sensitivity, out-of-sample validation and human risk review before a strategy goes live.
Boundary note
This is not investment advice. The metrics on this page are example-report figures, used to show how FiClaw organizes strategy generation, backtesting and diagnosis. They are not investment advice and do not represent future returns.