Editing Alpha Research5 (section)

=== Layer 3: Setup Quality Detection ===

'''Purpose:''' Score and grade trade setups using 5-factor weighted system

'''File:''' <code>src/components/setup_quality_detection.py</code>

'''5-Factor Scoring System:'''
<pre>
+-------------------------+--------+------------------------------------------+
| Factor                  | Weight | Description                              |
+-------------------------+--------+------------------------------------------+
| Timeframe Alignment     | 30%    | How many timeframes agree on direction   |
| Trend Strength          | 20%    | MA slope, price momentum                 |
| Entry Quality           | 15%    | Clean candle, near MA, not extended      |
| Key Level Proximity     | 20%    | Near support/resistance levels           |
| Risk/Reward Ratio       | 15%    | Potential reward vs risk                 |
+-------------------------+--------+------------------------------------------+
                           = 100%
</pre>

'''Grade Classification:'''
<pre>
Score >= 90  -->  A+ Grade  (Best setups, full position)
Score >= 80  -->  A Grade   (Excellent, 80% position)
Score >= 70  -->  B Grade   (Good, 60% position)
Score >= 60  -->  C Grade   (Average, 40% position)
Score >= 50  -->  D Grade   (Below average, 20% position)
Score <  50  -->  F Grade   (Poor, NO TRADE)
</pre>

'''Penalty System:'''
<pre>
Penalties Applied:
- Creeper Move detected: -50 points
- MA Struggle (price fighting MA): -30 points
- Missing Two-Day Trend: -30 points
- Phase Mismatch: -25 points
- Far from Key Level: -50 points
- Far from MA: -40 points

Bonuses Applied:
+ Railroad Trend (strong alignment): +15 points
+ At Key Level: +10 points
+ Clean Entry Candle: +10 points
</pre>

'''Institutional Fight Detection:'''
<pre>
IF 4H direction != Daily direction THEN
    Apply 0.7x multiplier to final score
    (Institutions may be fighting retail)
</pre>

'''Output:''' <code>SetupQualityResult</code>
* <code>grade</code>: A+ / A / B / C / D / F
* <code>score</code>: 0 - 100
* <code>factor_scores</code>: Individual factor breakdown
* <code>position_size</code>: Recommended lots
* <code>risk_percent</code>: Account risk percentage
* <code>can_auto_trade</code>: Boolean

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