Logic Upgrade: Dynamic Target Raise + Percentage Pricing

main.py

@@ -194,18 +194,21 @@ def generate_advisory(signals, macro, fundamentals, last_private_price):
     avg_ev_rev = np.mean([f['ev_rev'] for f in fundamentals if f['ev_rev'] > 0])
     
     # 1. PRICING LOGIC
-    # Base multiple derived from average peer EV/Rev with a hairut
-    # Rough calc: If market expects x10, IPO discount is usually 10-15%
-    # This is a synthetic range for demo
+    # Revised Logic: Relative Valuation Scaling
     base_price = 30.0 # Anchor (Simplified assumption)
     
-    if avg_mom > 5: base_price += 4.0
-    if avg_vol > 40: base_price -= 3.0
-    if macro['vix'] > 20: base_price -= 3.0
-    if macro['tnx'] > 4.5: base_price -= 2.0
+    # NEW: Percentage-based Momentum Premium/Discount
+    if avg_mom > 5: 
+        base_price *= 1.12  # +12% Premium for Hot Sector
+    elif avg_mom < -5:
+        base_price *= 0.88  # -12% Discount for Cold Sector
+
+    if avg_vol > 40: base_price *= 0.95 # -5% for High Volatility
+    if macro['vix'] > 20: base_price *= 0.90 # -10% for Macro Fear
+    if macro['tnx'] > 4.5: base_price *= 0.95 # -5% for Rates
     
-    low_px = base_price - 2.0
-    high_px = base_price + 2.0
+    low_px = base_price * 0.93 # +/- 7% Range
+    high_px = base_price * 1.07
     
     # 2. MARKET WINDOW LOGIC
     window_status = "OPEN"
@@ -300,12 +303,12 @@ def generate_advisory(signals, macro, fundamentals, last_private_price):
         final_text += " <br><i>Note: Valuation pressured by rising 10yr yields (>4.2%).</i>"
 
     return {
+        'commentary': final_text,
+        'sentiment': window_status,
         'low': round(low_px, 2),
         'high': round(high_px, 2),
-        'sentiment': window_status,
         'color': window_color,
-        'commentary': final_text,
-        'avg_ev_rev': avg_ev_rev,
+        'avg_ev_rev': round(avg_ev_rev, 1),
         'risk_matrix': risk_matrix
     }
 
@@ -313,12 +316,12 @@ def generate_advisory(signals, macro, fundamentals, last_private_price):
 # IPO STRUCTURING LOGIC (Professional)
 # ==============================================================================
 
-def calculate_ipo_structure(implied_price, discount_pct, greenshoe_active, existing_shares_m):
+def calculate_ipo_structure(implied_price, discount_pct, greenshoe_active, existing_shares_m, target_raise_m=250.0):
     """
     Calculates final deal structure based on banking levers.
-    Assumption: Target Capital Raise = $250M (Standard for this segment)
+    Target Capital Raise is now dynamic (default $250M)
     """
-    target_raise = 250.0  # $M
+    target_raise = float(target_raise_m)
     
     # 1. Apply Discount
     discount_factor = (100 - discount_pct) / 100
@@ -373,7 +376,8 @@ async def analyze(request: Request,
                   last_private: str = Form(None),
                   ipo_discount: float = Form(15.0),  # Default 15%
                   greenshoe: bool = Form(False),     # Default Off
-                  primary_shares: float = Form(100.0)): # Default 100M shares
+                  primary_shares: float = Form(100.0), # Default 100M shares
+                  target_raise: float = Form(250.0)): # Default $250M
     
     # 1. Determine Sector
     sector_key = 'SaaS'
@@ -402,7 +406,7 @@ async def analyze(request: Request,
     # 5. IPO Structuring (The Pro Layer)
     # We use the midpoint of the implied range as the base for discounting
     implied_midpoint = (advisory['low'] + advisory['high']) / 2
-    structure = calculate_ipo_structure(implied_midpoint, ipo_discount, greenshoe, primary_shares)
+    structure = calculate_ipo_structure(implied_midpoint, ipo_discount, greenshoe, primary_shares, target_raise)
     
     # Update Advisory with Final Price Context
     final_price = structure['final_price']