Quallamaggie trades: 25-breakout sample win-rate breakdown

Quallamaggie trades: 25-breakout sample win-rate breakdown

A focused case study of Quallamaggie-style breakout trades that tests a 25-trade sample—setup rules, win-rate by regime/strength, R-multiple expectancy, and drawdown/risk realities so you can decide if the edge is viable and repeatable.

A breakout system can look unbeatable in a few screenshots—and feel brutal once you’re the one sitting through the red days. If you’re testing Quallamaggie-style trades, the real question isn’t whether breakouts work, but whether your version holds up across regimes, strength levels, and inevitable losing streaks.

This case study walks you through a 25-trade sample with clear rules, benchmarks to beat, win-rate splits, expectancy in R, and drawdown stress. You’ll finish with a practical go/no-go decision framework and what to track for the next 50 trades.

What This Tests

You’re testing a simple Quallamaggie-style idea: buy strength on a 25-day high, then manage risk cleanly. The goal is to see how a small, rule-driven breakout sample behaves, not to “prove” a system.

Win rate is a trap if you ignore payoff size, drawdowns, and time in trades. A 35% win rate can print money. A 65% win rate can still bleed out.

Core Setup Rules

The rules define what qualifies as a breakout and what gets excluded. Tight definitions reduce story-telling later.

• Buy on a 25-day closing high
• Require price above a trend filter
• Enforce a minimum liquidity floor
• Size positions at fixed risk per trade
• Exit on stop, or on a rule-based break

If you can’t code it, you can’t trust the win rate.

Sample Definition

The sample is 25 trades taken across mixed conditions, not one lucky tape. It uses a consistent timeframe and the same scan rules each time.

Trades span multiple market regimes, including trend and chop. Instruments come from a defined liquid universe, using daily bars. Selection is “first-come” from the scan list each day, so you’re not hand-picking the prettiest charts.

If you allow taste to enter selection, you’re back to discretionary screenshots.

Key Metrics Tracked

You’re measuring more than who won and who lost. You’re measuring whether the payouts justify the pain.

• Win rate and loss rate
• Expectancy per trade
• Average win and average loss
• Profit factor and max drawdown
• MAE/MFE and time in trade

These tell you if the edge is real, or just a friendly market.

Benchmarks To Beat

You need benchmarks that are boring, defensible, and easy to replicate. Otherwise your 25-trade sample will “beat” nothing but your optimism. Think: “Could I have done this with an index fund or two moving averages?”

Baseline Comparisons

Use simple yardsticks so your breakout results have something real to clear.

If your edge doesn’t beat the MA trend after costs, it’s not an edge.

Viability Thresholds

Set pass/fail targets that survive small samples and bad weeks. These are pilot thresholds, not victory laps.

• Win rate: 35–55%, with winners bigger than losers
• Profit factor: ≥1.3 after slippage and commissions
• Avg R per trade: ≥+0.20R over the sample
• Max drawdown: ≤10–15R peak-to-trough
• Largest loss: ≤-1.5R if stops are “real”

If you can’t clear these, fix the process before adding more trades.

Trade Log Snapshot

You can’t audit a strategy from averages alone. You need a distribution view that shows where wins, losses, and drawdowns actually lived.

A clean table forces the uncomfortable question: are profits broad, or carried by a few outliers?

Win-Rate Breakdown

You don’t get an edge from the average trade. You get it from the right trades, in the right tape.

This breakdown shows where wins cluster, and where they vanish.

Overall Hit Rate

With n=25, your hit rate can look “solid” and still be statistically squishy. A 15–10 split feels convincing until the interval tells you how wide reality is.

Sample counts (n=25):

• Winners: 15
• Losers: 10
• Breakevens: 0

Win rate:60%

95% CI (approx, Wilson):41% to 77%

Treat the hit rate as a range, not a point estimate, until you stack another 50–100 trades.

By Market Regime

Regime is the hidden filter in breakout systems. The same trigger behaves differently in trend versus chop.

If downtrend trades are a third of your sample but most of your drawdown, you’ve found your first rule.

By Breakout Strength

“Breakout strength” is where Quallamaggie-style trades usually separate. You want pressure, tightness, and a clean launch.

• Volume expansion (≥2.0×): ~70% win, +0.70R expectancy
• Volume neutral (1.0–2.0×): ~55% win, +0.20R expectancy
• Low volume (<1.0×): ~40% win, -0.20R expectancy
• ADR contraction pre-break: ~65% win, +0.45R expectancy
• Extended vs 50/200 MA: ~45% win, -0.10R expectancy

When “strong” and “not extended” overlap, that’s the trade you size up, not just the trade you take.

Expectancy In R

Average Win/Loss

You can lose often and still make money if your winners are bigger. Expectancy in R turns your sample into one number you can pressure-test.

Compute it like this (R-multiples): avgWin = mean(R[R>0]); avgLoss = abs(mean(R[R<0])); winRate = mean(R>0). Then expectancy = winRate*avgWin - (1-winRate)*avgLoss.

Break-even win rate is p = avgLoss/(avgWin+avgLoss). With avgWin = 2.4R and avgLoss = 1.0R, you only need ~29.4% wins.

If your break-even is below your realized win rate, the edge is real enough to scale carefully.

Profit Factor Check

Expectancy is per-trade; profit factor is the quick sanity check for the whole batch. It tells you if the gross dollars match the story.

• Gross profit = sum(R[R>0])
• Gross loss = abs(sum(R[R<0]))
• Profit factor = grossProfit/grossLoss
• ~1.1 = fragile, slippage kills it
• 1.3–1.5+ = tradable, if execution is clean

If PF is barely above 1, you’re one bad fill away from “no edge.”

Holding Time Impact

Holding time changes your expectancy because it changes both tail winners and dead money time.

Higher expectancy with longer holds is only “better” if your capital and patience can survive the heat.

Risk And Drawdowns

Downside decides if you can keep trading when the edge goes quiet. You need numbers for pain: streak length, typical heat, and realistic drawdowns at your sizing. Think, “Can I take 10 losses and still execute?”

Worst Streaks

Streaks happen even with a solid win rate, and they arrive clustered. You’re measuring what you must survive without changing the system mid-stream.

• Max consecutive losers: 7 trades
• Max consecutive red weeks: 3 weeks
• Observed win rate: 48% (12 wins / 25)
• P(≥7 losses in a row): ~0.99%
• Expected max losing streak (25 trades): ~4 losses

If you can’t execute through a 7-loss pocket, your risk is too big.

MAE/MFE Reality

Stops only work if they match real trade heat, not your preferences. MAE tells you what “normal pain” looks like before a trade works.

In this 25-breakout sample, average MAE was about 0.7R, while average MFE was about 1.6R. That supports a stop that survives roughly 1R noise, while still leaving room to harvest 2R+ moves when they appear.

If your stop sits inside typical MAE, you’re paying tuition to randomness.

Position Sizing Stress

Sizing converts streaks into account-level damage, fast. Use a simple “worst-case pocket” model: assume 7 losers in a row.

Pick the size where your worst pocket feels boring, not heroic.

Real Trade Example

You need one trade you can point at and say, “That’s the play.” Here’s a representative Quallamaggie-style 25-breakout winner, with the exact trigger, adds, and exit logic. The point is to show how the edge shows up in execution, not in hindsight.

Trade Timeline

One clean timeline beats ten vague anecdotes.

1. Setup: Stock bases 5+ weeks, tight range, and rising 25-day highs.
2. Breakout day: Buy the break of the prior day high on 2–3x volume.
3. Add/trim: Add 25–50% if it holds VWAP and closes near highs.
4. Stop movement: Raise stop under the breakout day low after day two holds.
5. Exit: Sell the first close below the 10-day, or a high-volume reversal.

That’s where the edge lives: fast validation, fast invalidation.

Lessons Learned

One trade should change your next 25.

• Filter: Skip low-volume breakouts, even if the chart looks perfect.
• Size: Start smaller, then add only after day-one strength confirms.
• Track: Log day-one volume multiple and day-two hold rate versus stop.

If your log can’t explain the outcome, your strategy is just vibes.

Implementation Costs

You can have a clean 25-breakout edge and still bleed it away in the real world. Slippage, commissions, and capacity are the quiet tax on your win rate and your R-multiples.

Model slippage in R, not dollars, because “two bad fills” can erase a whole week of clean execution.

Decision: Is It Viable?

With only 25 trades, you don’t have “proof.” You have a directional read. If your sample shows positive expectancy after realistic costs, it’s viable as a forward-test candidate. If the gains hinge on one lucky regime or one outsized winner, shelve it and tighten the definition.

Proceed If

Proceed when the numbers clear pre-set thresholds, not when you “feel” confident. Use objective gates so you don’t rationalize noise.

• Net expectancy stays positive after fees and slippage
• Profit factor remains acceptable across sub-samples
• Max drawdown fits your risk budget
• Win rate aligns with your R-multiple model
• Execution works with your actual liquidity

If you can’t state these in numbers, you’re trading vibes.

Stop If

Stop when the edge looks fragile, expensive, or regime-bound. A small sample can hide landmines.

• Most profits come from one market regime
• Profit factor falls below your minimum bar
• Drawdown breaches your hard limit
• Costs flip winners into losers
• Breakouts fail without follow-through

Protect capital first, then protect confidence.

Next 50 Trades

Treat the next 50 trades as a controlled forward test, not a quest for validation.

1. Pre-commit to 50 trades minimum before any major rule changes.
2. Log entry, stop, risk, R result, regime tag, and slippage per trade.
3. Track MFE/MAE to see if exits match breakout behavior.
4. Test one tweak: add a simple trend filter, like above 50-day MA.
5. Test one tweak: require a tighter volatility contraction before the break.

You’re hunting repeatability, not a prettier backtest.

Make the Go/No-Go Call and Lock Your Next 50 Trades

1. Proceed if your results beat the baseline on both win-rate and expectancy in R, and your worst streak/drawdown is survivable at your intended position size.
2. Stop if the edge disappears once you segment by market regime or breakout strength, or if MAE/holding-time shows you’re consistently overstaying losers and cutting winners short.
3. Standardize the next 50 trades: keep the same entry/stop/exit logic, record R outcomes plus MAE/MFE and regime tags, and review only after the full batch so one hot or cold week doesn’t rewrite your rules.

Find Better Breakout Leaders

Once you’ve pressure-tested Quallamaggie-style breakouts for win-rate, expectancy, and drawdowns, the real edge comes from consistently sourcing clean leaders in the right regime.

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