Strategy Comparison - Which Trading Setup Works Best for You?
You have multiple trading strategies.
But which one actually makes you money?
You think you know—but do you really?
Let's find out using data, not gut feeling.
The Multi-Strategy Problem
Common Scenario
Trader: "I trade breakouts, pullbacks, and mean reversion"
Question: "Which works best?"
Answer: "Umm... they all work... sometimes?"
Problem: No data. Just hope.
Why This Matters
Trading multiple strategies without comparison:
- Wasting time on losers
- Under-utilizing winners
- No clear focus
- Inconsistent results
With proper comparison:
- Identify best performers
- Eliminate losers
- Focus effort efficiently
- Maximize returns
What to Compare
Category 1: Different Setups
Example:
- Strategy A: Breakout trading
- Strategy B: Pullback entries
- Strategy C: Mean reversion
Question: Which has highest win rate? Best R:R? Most consistent?
Category 2: Same Setup, Different Conditions
Example: Breakout trading in:
- Condition A: Trending markets
- Condition B: Ranging markets
- Condition C: High volatility markets
Question: When does my setup work best?
Category 3: Same Setup, Different Timeframes
Example: Moving average crossover on:
- Timeframe A: 5-minute chart
- Timeframe B: 15-minute chart
- Timeframe C: Daily chart
Question: Which timeframe suits me?
Category 4: Same Setup, Different Instruments
Example: Pullback strategy on:
- Instrument A: NIFTY futures
- Instrument B: Bank NIFTY futures
- Instrument C: Stock options
Question: Where's my edge strongest?
Category 5: Entry Variations
Example: Breakout entry at:
- Entry A: Immediate break
- Entry B: Pullback after break
- Entry C: Confirmation candle
Question: Which entry timing is optimal?
Key Metrics to Compare
Metric #1: Win Rate
Definition: Percentage of winning trades
Formula: (Winning Trades / Total Trades) × 100
Example Comparison:
Strategy A (Breakouts): 58%
Strategy B (Pullbacks): 64%
Strategy C (Mean Reversion): 51%
Winner: Strategy B (highest win rate)
But: Win rate alone doesn't tell full story...
Metric #2: Average Win vs Average Loss
Why it matters: High win rate with small wins can still lose money
Example:
Strategy A:
- Win Rate: 70%
- Avg Win: ₹2,000
- Avg Loss: ₹5,000
Math:
- 7 wins × ₹2,000 = ₹14,000
- 3 losses × ₹5,000 = -₹15,000
- Net: -₹1,000 (losing despite 70% win rate!)
Strategy B:
- Win Rate: 50%
- Avg Win: ₹5,000
- Avg Loss: ₹2,500
Math:
- 5 wins × ₹5,000 = ₹25,000
- 5 losses × ₹2,500 = -₹12,500
- Net: +₹12,500 (profitable with 50% win rate!)
Lesson: Average win/loss matters more than win rate.
Metric #3: Profit Factor
Definition: Gross profit / Gross loss
Formula: Total Winning ₹ / Total Losing ₹
Interpretation:
- PF < 1.0: Losing system
- PF = 1.0: Break-even
- PF 1.0-1.5: Marginal
- PF 1.5-2.0: Good
- PF 2.0-3.0: Very good
- PF > 3.0: Excellent (verify it's real)
Example Comparison:
Strategy A: PF 1.2 (marginal)
Strategy B: PF 2.4 (very good)
Strategy C: PF 0.9 (losing)
Winner: Strategy B
Action: Stop using Strategy C
Metric #4: Expectancy
Definition: Average amount you expect to win/lose per trade
Formula: (Win Rate × Avg Win) - (Loss Rate × Avg Loss)
Example:
Strategy A:
- Win Rate: 60%
- Avg Win: ₹4,000
- Loss Rate: 40%
- Avg Loss: ₹2,000
Expectancy: (0.6 × ₹4,000) - (0.4 × ₹2,000) = ₹2,400 - ₹800 = +₹1,600/trade
Strategy B:
- Win Rate: 55%
- Avg Win: ₹3,000
- Loss Rate: 45%
- Avg Loss: ₹2,500
Expectancy: (0.55 × ₹3,000) - (0.45 × ₹2,500) = ₹1,650 - ₹1,125 = +₹525/trade
Winner: Strategy A (higher expectancy per trade)
Metric #5: Maximum Drawdown
Definition: Largest peak-to-trough decline
Why it matters: Tells you worst-case scenario
Example:
Strategy A: Max DD 12%
Strategy B: Max DD 8%
Strategy C: Max DD 22%
Winner: Strategy B (lowest drawdown = less risk)
Psychology: Can you handle 22% drawdown? If not, avoid Strategy C even if profitable.
Metric #6: Sharpe Ratio
Definition: Risk-adjusted return
Formula: (Return - Risk-Free Rate) / Standard Deviation
Simplified: Higher Sharpe = Better risk-adjusted returns
Example:
Strategy A: Sharpe 1.2
Strategy B: Sharpe 1.8
Strategy C: Sharpe 0.7
Winner: Strategy B (best risk-adjusted returns)
Metric #7: Consistency
Measure: % of profitable months
Example:
Strategy A: 7/12 months profitable (58%)
Strategy B: 9/12 months profitable (75%)
Strategy C: 5/12 months profitable (42%)
Winner: Strategy B (most consistent)
Psychology: Consistent strategies are easier to stick with.
Metric #8: Trade Frequency
How many trades per month/year?
Example:
Strategy A: 45 trades/month (high frequency)
Strategy B: 12 trades/month (moderate)
Strategy C: 3 trades/month (low frequency)
Consider:
- Higher frequency = More opportunities, more stress
- Lower frequency = Fewer opportunities, less stress
- Match to your lifestyle
How to Run a Comparison in TradeLyser
Step 1: Tag Your Strategies
For all past trades:
- Go to Journal
- Select trades
- Add strategy tag:
- "Breakout-Trending"
- "Pullback-Uptrend"
- "Mean-Reversion"
- Save
For future trades:
- Tag during entry or review
Step 2: Open Strategy Comparison
- TradeLyser → Strategy Book
- Click Compare Strategies
- Select strategies to compare (2-5)
Step 3: Set Time Period
Choose:
- Last 3 months
- Last 6 months
- Last 1 year
- All time
- Custom range
Tip: Use at least 30 trades per strategy for statistical significance.
Step 4: View Comparison Dashboard
TradeLyser shows side-by-side:
| Metric | Strategy A | Strategy B | Strategy C |
|---|---|---|---|
| Trades | 87 | 94 | 45 |
| Win Rate | 62% | 58% | 51% |
| Avg Win | ₹4,200 | ₹5,100 | ₹2,800 |
| Avg Loss | ₹2,100 | ₹2,600 | ₹2,400 |
| Profit Factor | 2.3 | 2.1 | 1.2 |
| Expectancy | ₹1,850 | ₹1,620 | ₹340 |
| Max DD | 9% | 11% | 16% |
| Total P&L | +₹1,61,000 | +₹1,52,000 | +₹15,300 |
Step 5: Analyze Visually
Charts available:
- Equity curve (cumulative P&L over time)
- Win rate by month
- Average R:R comparison
- Drawdown comparison
- Trade distribution
Look for:
- Which curve is smoothest? (consistency)
- Which grows fastest? (profitability)
- Which has smallest dips? (risk management)
Step 6: Deep Dive
Click any strategy for details:
Market Conditions:
- Works best in: Trending up
- Works worst in: Choppy/ranging
- Optimal VIX: < 15
Time of Day:
- Best hours: 9:30-11:00 AM
- Worst hours: 2:00-3:30 PM
Instruments:
- Best on: Large cap stocks
- Worst on: Small cap stocks
Entry Quality:
- A+ setups: 72% WR
- B setups: 54% WR
- C setups: 38% WR
Step 7: Make Decisions
Based on data:
Strategy A: ⭐ Primary strategy (best metrics) Strategy B: ⭐ Secondary (good alternative) Strategy C: ❌ Stop using (marginally profitable)
Real Comparison: Case Study
Rahul's Three Strategies
Background:
- Trading for 2 years
- Using 3 different approaches
- Feels inconsistent
- Wants to focus
Strategies:
- Morning Gap Trading
- Afternoon Breakouts
- EOD Swing Entries
The Comparison
Data: 18 months, 342 total trades
Results:
| Metric | Gap Trading | Afternoon BO | EOD Swing |
|---|---|---|---|
| Trades | 147 | 128 | 67 |
| Win Rate | 68% | 42% | 64% |
| Avg Win | ₹3,800 | ₹6,200 | ₹8,100 |
| Avg Loss | ₹1,900 | ₹4,800 | ₹3,600 |
| Profit Factor | 2.8 | 1.1 | 2.4 |
| Expectancy | ₹1,820 | -₹220 | ₹2,884 |
| Max DD | 7% | 18% | 11% |
| Total P&L | +₹2,67,500 | -₹28,200 | +₹1,93,200 |
Key Discoveries
1. Afternoon Breakouts: LOSING Strategy
- Despite occasional big wins (₹6,200 avg)
- Win rate too low (42%)
- Losses too large (₹4,800 avg)
- Negative expectancy: -₹220/trade
Action: STOP using this strategy
2. Morning Gap Trading: BEST Strategy
- Highest profit factor (2.8)
- Great win rate (68%)
- Controlled losses (₹1,900)
- Positive expectancy: ₹1,820/trade
- Most total profit: ₹2.67L
Action: Make this PRIMARY strategy
3. EOD Swing: GOOD Secondary
- Highest expectancy (₹2,884/trade)
- But lowest frequency (67 trades vs 147)
- Good for diversification
- Different timeframe = non-correlated
Action: Keep as SECONDARY strategy
Rahul's New Plan
Before:
- 3 strategies, equal focus
- Net: +₹4.32L (with one loser dragging down)
After (6 months):
- Strategy 1 (Morning Gaps): 80% focus
- Strategy 2 (EOD Swing): 20% focus
- Strategy 3 (Afternoon): ELIMINATED
- Net: +₹3.87L in 6 months (vs ₹4.32L in 18 months)
- 3x faster growth rate
Rahul's words: "I was wasting 40% of my trades on a losing strategy. Comparison showed me the truth. Now I only trade what works."
Advanced Comparison Techniques
A/B Testing Strategy Variations
Test: Does adding volume filter improve results?
Strategy A (Original):
- Breakout above resistance
- No volume requirement
Strategy A-Modified:
- Breakout above resistance
- Volume > 1.5x average
Run both for 30 trades each
Results:
- Original: 58% WR, ₹1,420 expectancy
- Modified: 67% WR, ₹2,180 expectancy
Conclusion: Add volume filter permanently
Market Condition Segmentation
Question: Does Strategy A work in all markets?
Segment by VIX:
- Low volatility (VIX < 15): 71% WR
- Medium volatility (VIX 15-20): 58% WR
- High volatility (VIX > 20): 41% WR
Conclusion: Only trade Strategy A when VIX < 20
Time-of-Day Analysis
Strategy: Breakout Trading
Performance by hour:
9:15-10:00 AM: 64% WR, +₹87,000
10:00-11:00 AM: 68% WR, +₹1,23,000 ⭐
11:00-12:00 PM: 57% WR, +₹34,000
12:00-1:00 PM: 49% WR, +₹8,000
1:00-2:00 PM: 45% WR, -₹12,000
2:00-3:00 PM: 38% WR, -₹34,000
3:00-3:30 PM: 42% WR, -₹18,000
Conclusion: Only trade 9:15 AM - 12:00 PM
Instrument-Specific Performance
Strategy: Momentum trading
Results by instrument:
- NIFTY 50 stocks: 64% WR, PF 2.3
- Mid-cap stocks: 51% WR, PF 1.4
- Small-cap stocks: 43% WR, PF 0.9
Conclusion: Stick to NIFTY 50 stocks
Common Comparison Mistakes
Mistake #1: Too Small Sample Size
Wrong: "I tested Strategy A for 5 trades, it lost, so it's bad"
Right: Minimum 30 trades per strategy for valid comparison
Mistake #2: Different Time Periods
Wrong:
- Strategy A: Jan-Mar (bull market)
- Strategy B: Jul-Sep (bear market)
Right: Compare same time period (same market conditions)
Mistake #3: Ignoring Risk
Wrong: "Strategy A made ₹5L, Strategy B made ₹3L, so A is better"
Missing:
- Strategy A: 25% max drawdown
- Strategy B: 8% max drawdown
Right: Strategy B might be better (risk-adjusted)
Mistake #4: Survivorship Bias
Wrong: Only comparing strategies you're still using (successful ones)
Right: Include abandoned strategies to learn why they failed
Mistake #5: Curve Fitting
Wrong: Over-optimizing until backtest is perfect
Right: Simple rules that work across different periods
Decision Framework
When to Keep a Strategy
✅ Keep if:
- Positive expectancy (>₹500/trade)
- Profit factor > 1.5
- Max drawdown tolerable
- Fits your schedule/psychology
- Enough trade opportunities
When to Modify a Strategy
⚠️ Modify if:
- Close to breakeven
- Good win rate but small wins
- Or good R:R but low win rate
- Works in some conditions, not others
Action: Test variations, filter trades
When to Eliminate a Strategy
❌ Eliminate if:
- Negative expectancy
- Profit factor < 1.2
- Inconsistent (random results)
- Max drawdown too large
- Too stressful to execute
Action: Stop immediately, reallocate time
The Portfolio Approach
Don't rely on one strategy.
Build a strategy portfolio:
Strategy 1 (60% allocation): Best performer, primary focus
Strategy 2 (30% allocation): Good performer, different market condition
Strategy 3 (10% allocation): Testing/development
Benefits:
- Diversification
- Always have something working
- Continuous improvement
- Reduced risk
The Bottom Line
You can't improve what you don't measure.
You can't choose without comparing.
Guessing which strategy works = Gambling
Knowing which strategy works = Trading
Run the comparison. Make data-driven decisions.
Take Action Now
Today:
- Tag your last 50 trades by strategy
- Run your first comparison in TradeLyser
- Identify your best and worst performers
This Week:
- Deep dive into why winners win
- Understand why losers lose
- Decide: keep, modify, or eliminate each
This Month:
- Focus 80% effort on top strategy
- Test improvements to secondary strategy
- Eliminate bottom performer
- Compare results vs previous month
👉 Run Strategy Comparison in TradeLyser
👉 Download: Strategy Comparison Template
👉 Next: Start My Day & Finish My Day Routines
What's your most profitable trading strategy? Have you compared it to others? Share below.