Strategy Comparison Playbook
Use this workflow to shortlist strategies, compare edge quality, and decide which ones earn a spot in your plan. Adapt it for weekly or monthly reviews.
1. Prepare your brief
- State the objective (e.g., “Add a BTC intraday mean reversion system” or “Replace underperforming swing strategy”).
- List constraints: capital bucket, max drawdown, preferred intervals, liquidation rules.
- Decide which dataset to start with: V2 for breadth, V1 to confirm live execution.
- Open the Analytics view plus this playbook, the evaluation guide, and your trading journal.
2. Screen and shortlist
- Build a saved filter — Set timeframe, min trades, pairs, and intervals. Bookmark the resulting URL.
- Sort by score, PF, and PnL — Capture the top 5–10 candidates that satisfy your minimum data depth.
- Diversity check — Ensure factor tags (First/Second) cover distinct ideas so you avoid correlation.
- Export snapshot — Download the summary CSV and attach it to your journal entry or team note.
Tip:
Use spreadsheet conditional formatting on the CSV to highlight metrics that beat your thresholds.
Filters snapshot
- Timeframe: 6 months
- Min trades: 200
- Pairs: BTC_USDT, ETH_USDT
CSV highlight
| Strategy | Score | PF |
|---|---|---|
| Momentum Pulse | 92 | 1.85 |
| Supertrend Confirmed | 88 | 1.58 |
3. Deep-dive evaluation
- Trades panel review — Look for clustering of losses, widening spreads, or changing volatility.
- Timeline inspection — Identify stress periods. Was performance resilient in bear markets or during high volatility spikes?
- Sim vs live cross-check — Compare V1 and V2 stats. Large performance gaps may imply execution risk; flag for smaller sizing.
- Risk alignment — Plug daily profit and drawdown estimates into your risk worksheet to confirm capital fit.
- Document findings — Add key metrics, observed behaviours, and open questions to your journal entry.
4. Build a comparison scorecard
Use a simple table (example below) to rank candidates by the factors that matter most to you.
| Strategy | Pair / Interval | PF & Score | Risk notes | Decision |
|---|---|---|---|---|
| EMA Trend Lite | ETH_USDT / 1h | Score 84 · PF 1.7 | Low slippage; stable since Q2 | Pilot (micro) |
| Supertrend Confirmed | BTC_USDT / 15m | Score 78 · PF 1.4 | Variance spike Mar 2024 | Hold for now |
Copy the structure into Notion, Sheets, or your preferred journal. Adjust columns to match your risk policy.
5. Make and log the decision
- Confirm the strategy meets score, PF, and trade count thresholds agreed with your team.
- Assign start size (paper, micro, or capital %) and set entry criteria.
- Create re-evaluation triggers: score drop, PF decay, or drawdown limit.
- Record the decision, rationale, and next review date in your trading log.
Reminder:
Do not scale capital until the strategy proves itself in paper or micro trading under live conditions.
Journal excerpt — Momentum Pulse
- Rationale: PF 1.85, stable since Q2, aligns with BTC swing mandate.
- Allocation: 2% notional, micro size for first 4 weeks.
- Review trigger: Score < 80 or PF < 1.4 over last 50 trades.
- Next review: 2025-04-15 weekly committee.
6. Run ongoing retrospectives
- Schedule reviews — Weekly for active portfolios, monthly for long-term holds.
- Re-run filters — Reapply saved Analytics filters and compare new metrics to your baseline snapshot.
- Update journal — Log any deviations, market context, and actions taken (pause, reduce size, double-check data).