Strategy Comparison

Why Symbol-Specific Optimization Matters

Not all Volatility Box strategies work equally well on every symbol. AAPL might show a 67% win rate with Daily Conservative Blind Breach settings but only achieve 48% success with Hourly Aggressive Gap Fill. TSLA could show the opposite performance pattern due to differences in volatility characteristics and price behavior.

Systematically testing all 4 strategy types (Blind Breach, ORB Confluence, Gap Fill, At The Edge) per symbol reveals which approach actually makes money on each stock. This eliminates guesswork and improves your overall win rate and expectancy.

The Four Strategy Profiles

Each of the four validated VB strategies has distinct characteristics that suit different symbol personalities and market conditions.

Blind Breach represents the highest-frequency approach, generating 60-100+ signals annually on active symbols. It enters immediately on every VB cloud breach without additional filters. This pure volatility mean-reversion play works well on symbols that oscillate within defined volatility bands, such as large-cap dividend stocks.

ORB Confluence generates the fewest signals at 8-15 per year but delivers the highest win rates (68-75%). It requires both Opening Range Breakout stretch targets AND VB breach to coincide, creating double confirmation. This selective approach suits patient traders who prefer fewer high-probability trades.

Gap Fill falls in the middle frequency range with 15-25 signals annually. It combines gap statistics with VB breaches to capture setups where unfilled gaps create magnetic pull zones aligned with volatility exhaustion levels.

At The Edge generates 20-35 signals per year by entering only when price has blown past VB clouds entirely into the outer stop region. This counter-trend exhaustion strategy offers skewed reward-to-risk ratios of 1:2 or 1:3 when extreme moves reverse.

The Backtester strategy dropdown shows all four available strategies you can test on any symbol.

Testing All Strategies on One Symbol

Begin strategy comparison by selecting your most-traded symbol and testing all four strategies using the same model type. Start with Daily Conservative for consistency over the standard 450-day validation period.

Run separate backtests for Blind Breach, ORB Confluence, Gap Fill, and At The Edge. Record win rate, expectancy, total trades, max drawdown, and recovery factor for each in a comparison spreadsheet.

Example AAPL strategy comparison over 450 days using Daily Conservative model:

• Blind Breach: 87 trades, 54% win rate, +$38 expectancy, 18% max drawdown
• ORB Confluence: 14 trades, 72% win rate, +$94 expectancy, 11% max drawdown
• Gap Fill: 6 trades, 48% win rate, -$12 expectancy, 32% max drawdown
• At The Edge: 24 trades, 51% win rate, +$45 expectancy, 24% max drawdown

This comparison reveals ORB Confluence as the clear winner with highest expectancy (+$94), highest win rate (72%), and lowest drawdown (11%).

The Backtester summary shows all key metrics at a glance, making it easy to identify your best-performing strategy.

Strategy Ranking Methodology

Rank strategies using a systematic three-tier hierarchy that prioritizes long-term profitability while maintaining statistical confidence.

Primary criterion: Expectancy. The strategy with the highest dollar profit per trade gets top priority. You’re trading to maximize wealth accumulation, not to maximize signal frequency.

Secondary criterion: Win rate. If two strategies have similar expectancy values (within $15 per trade), choose the higher win rate for improved psychological comfort during losing streaks.

Tertiary criterion: Trade count. Ensure the winning strategy generated at least 30 trades during the 450-day test period for statistical confidence.

Applying this to the AAPL example: ORB Confluence wins on expectancy (+$94 vs next-best +$45), making it the top choice despite lower trade frequency. Blind Breach ranks second with acceptable +$38 expectancy. Gap Fill fails entirely with negative expectancy and earns immediate removal from consideration.

Model Type Optimization

Beyond strategy selection, model type choice (Daily vs Hourly, Aggressive vs Conservative) dramatically impacts performance. After identifying your best strategy on Daily Conservative, test it across all four model combinations.

Testing ORB Confluence across all AAPL model types:

• Daily Aggressive: 22 trades, 68% win rate, +$82 expectancy
• Daily Conservative: 14 trades, 72% win rate, +$94 expectancy (winner)
• Hourly Aggressive: 42 trades, 58% win rate, +$48 expectancy
• Hourly Conservative: 28 trades, 61% win rate, +$58 expectancy

This confirms Daily Conservative is optimal for AAPL with highest expectancy and win rate. Both hourly models significantly underperform, proving this symbol responds better to daily volatility calculations.

The Model and Level dropdowns let you test different timeframe and sensitivity combinations for each strategy.

Cross-Symbol Strategy Comparison

After optimizing strategy and model on your first symbol, repeat the process across your 10-15 core trading symbols. Create a master comparison table with columns for Symbol, Best Strategy, Best Model, Win Rate, Expectancy, and Trades/Year.

Example cross-symbol comparison showing optimal strategy for each stock:

• AAPL: ORB Confluence, Daily Conservative, 72% win rate, +$94 expectancy
• MSFT: At The Edge, Daily Conservative, 61% win rate, +$108 expectancy
• NVDA: Blind Breach, Daily Aggressive, 58% win rate, +$86 expectancy
• TSLA: At The Edge, Hourly Aggressive, 51% win rate, +$142 expectancy
• GOOGL: ORB Confluence, Daily Conservative, 64% win rate, +$118 expectancy

Notice the pattern: most mega-caps favor Daily Conservative with selective strategies. NVDA prefers Daily Aggressive Blind Breach for higher frequency. TSLA uniquely requires Hourly Aggressive to capture its intraday volatility.

Optimized Portfolio Construction

Instead of trading every signal in the Scanner, construct an optimized portfolio of 5-10 symbols with validated strategies. Rank your full watchlist by expectancy after testing all symbols.

Example optimized 5-symbol portfolio ranked by expectancy:

1. TSLA At The Edge Hourly Aggressive (+$142 expectancy, 68 trades/year)
2. GOOGL ORB Confluence Daily Conservative (+$118 expectancy, 12 trades/year)
3. MSFT At The Edge Daily Conservative (+$108 expectancy, 18 trades/year)
4. AAPL ORB Confluence Daily Conservative (+$94 expectancy, 14 trades/year)
5. NVDA Blind Breach Daily Aggressive (+$86 expectancy, 42 trades/year)

Trade only these five specific symbol/strategy combinations while ignoring everything else. This focused approach eliminates low-expectancy setups and concentrates on statistically proven winners.

Quarterly Strategy Reassessment

Optimal strategies can shift as market regimes change. Implement a quarterly review where you re-run backtests on your core symbols using the most recent rolling 450 days of data.

Compare current results to the previous quarter. If a different strategy now shows materially higher expectancy (20%+ improvement), switch to it while monitoring performance.

Example quarterly reassessment for NVDA:

• Q4 2024: Blind Breach Daily Aggressive was best with +$86 expectancy
• Q1 2025: Market volatility increased 40%. Blind Breach expectancy dropped to +$52. At The Edge Daily Conservative increased to +$124.

The action: switch from Blind Breach to At The Edge for NVDA in Q1, adapting to changed market conditions.

Strategy Performance by Market Regime

Filter backtest results by market regime to understand which strategies work best in specific conditions. Define regime types by VIX level (below 15 = low, 15-25 = moderate, above 25 = high) and trend direction (SPY above 50 EMA = bull, below = bear).

Testing AAPL ORB Confluence across different regimes:

• Bull/Low Vol: 6 trades, 83% win rate, +$128 expectancy (excellent)
• Bull/Moderate Vol: 18 trades, 72% win rate, +$94 expectancy (strong)
• Bull/High Vol: 8 trades, 58% win rate, +$64 expectancy (acceptable)
• Bear/Any Vol: 4 trades, 48% win rate, +$18 expectancy (marginal)

This reveals ORB Confluence works best during bull markets. Consider reducing position size by 50% or skipping the strategy when SPY is below its 50 EMA.

Common Optimization Mistakes

Traders frequently make errors during strategy optimization that lead to poor results.

Mistake #1: Curve-fitting to recent data. Testing only the last 90-180 days and choosing strategies that worked during that specific period. These strategies often fail when conditions shift.

Mistake #2: Ignoring sample size. Choosing a strategy based on 8 trades showing 75% win rate. The tiny sample makes that percentage statistically meaningless.

Mistake #3: Optimizing for win rate instead of expectancy. Selecting a 68% win rate strategy with +$42 expectancy over a 54% strategy with +$96 expectancy. This leaves money on the table.

Mistake #4: Never reassessing. Running optimization once and trading the same strategies for years despite market regime shifts.

Mistake #5: Over-diversifying. Trading all 4 strategies across 20 symbols creates 80 potential signals that scatter attention and dilute your edge.

Next Steps

Build your strategy comparison table by selecting your 10 most-traded symbols. Run complete 450-day backtests testing all 4 strategies on each symbol using Daily Conservative as the standard model.

Record win rate, expectancy, trade count, max drawdown, and recovery factor for each combination. Rank each symbol’s strategies by expectancy first, identifying the single best approach per stock.

Select the top 5 symbol/strategy combinations by expectancy across your entire watchlist. Create Scanner filter presets so you only see signals matching your validated combinations. Trade exclusively these optimized edges for the next quarter and track results against backtest expectations.