diff --git a/HedgeAnalyzer.py b/HedgeAnalyzer.py
index d84277c..33e5aae 100755
--- a/HedgeAnalyzer.py
+++ b/HedgeAnalyzer.py
@@ -32,32 +32,56 @@ CIK = '0001603466'
 query = {
     "query": f'cik:{CIK} formType:"13F-HR"',
     "sort": [{"filedAt": {"order": "desc"}}],
-    "size": 10  # Fetch more to ensure we get distinct periods
+    "size": 100  # Increased to capture more filings
 }
 response = query_api.get_filings(query)
 filings = response.get('filings', [])
 
-# Filter unique periodOfReport and select the two most recent
-filings = sorted(filings, key=lambda x: x['periodOfReport'], reverse=True)
-unique_filings = []
-seen_periods = set()
+# Debug: Print filing details
+print(f"Total filings retrieved: {len(filings)}")
+for i, filing in enumerate(filings[:10]):
+    holdings = filing.get('holdings', [])
+    total_value = sum(h.get('value', 0) for h in holdings) / 1000  # In thousands
+    print(f"Filing {i+1}: Period={filing['periodOfReport']}, FiledAt={filing['filedAt']}, FormType={filing.get('formType', 'N/A')}, HoldingsCount={len(holdings)}, TotalValue=${total_value:,.0f}")
+
+# Group filings by periodOfReport
+from collections import defaultdict
+period_groups = defaultdict(list)
 for filing in filings:
     period = filing['periodOfReport']
-    if period not in seen_periods:
-        unique_filings.append(filing)
-        seen_periods.add(period)
+    holdings = filing.get('holdings', [])
+    total_value = sum(h.get('value', 0) for h in holdings)
+    filing['_total_value'] = total_value  # Temp field
+    period_groups[period].append(filing)
+
+# Select filing with highest value (>= $30B threshold, tiebreak by holdings count)
+unique_filings = []
+for period in sorted(period_groups.keys(), reverse=True):
+    group = period_groups[period]
+    valid_filings = [f for f in group if f['_total_value'] >= 30000000000]  # $30B min
+    if not valid_filings:
+        # Fallback: Highest holdings if no high-value filing
+        valid_filings = [f for f in group if len(f.get('holdings', [])) >= 500]
+    if not valid_filings:
+        continue
+    selected = max(valid_filings, key=lambda f: (f['_total_value'], len(f.get('holdings', []))))
+    unique_filings.append(selected)
     if len(unique_filings) == 2:
         break
 
 if len(unique_filings) < 2:
-    raise Exception(f"Not enough unique filings found: {len(unique_filings)} found")
+    raise Exception(f"Not enough valid filings found: {len(unique_filings)} found")
 
 latest = unique_filings[0]
 prev = unique_filings[1]
 
-# Fetch holdings
+# Debug: Selected filings
 latest_holdings = latest.get('holdings', [])
 prev_holdings = prev.get('holdings', [])
+latest_value = sum(h.get('value', 0) for h in latest_holdings) / 1000
+prev_value = sum(h.get('value', 0) for h in prev_holdings) / 1000
+print(f"Selected latest: Period={latest['periodOfReport']}, FiledAt={latest['filedAt']}, FormType={latest.get('formType', 'N/A')}, HoldingsCount={len(latest_holdings)}, TotalValue=${latest_value:,.0f}")
+print(f"Selected previous: Period={prev['periodOfReport']}, FiledAt={prev['filedAt']}, FormType={prev.get('formType', 'N/A')}, HoldingsCount={len(prev_holdings)}, TotalValue=${prev_value:,.0f}")
 
 if not latest_holdings or not prev_holdings:
     raise Exception("No holdings data found in filings")
@@ -66,6 +90,10 @@ if not latest_holdings or not prev_holdings:
 latest_df = pd.DataFrame(latest_holdings)
 prev_df = pd.DataFrame(prev_holdings)
 
+# Debug: Print DataFrame shapes
+print(f"Latest DataFrame shape: {latest_df.shape}")
+print(f"Previous DataFrame shape: {prev_df.shape}")
+
 # Extract share amount from shrsOrPrnAmt dictionary
 def extract_shares(row):
     if isinstance(row, dict):
@@ -76,7 +104,7 @@ if 'shrsOrPrnAmt' in latest_df.columns:
     latest_df['shrsOrPrnAmt'] = latest_df['shrsOrPrnAmt'].apply(extract_shares)
     prev_df['shrsOrPrnAmt'] = prev_df['shrsOrPrnAmt'].apply(extract_shares)
 
-# Verify required columns (ticker is optional but we'll add it if present)
+# Verify required columns (ticker is optional)
 required_cols = ['cusip', 'nameOfIssuer', 'shrsOrPrnAmt', 'value']
 for col in required_cols:
     if col not in latest_df.columns or col not in prev_df.columns:
@@ -94,11 +122,19 @@ else:
 latest_df['value_formatted'] = latest_df['value'].apply(lambda x: f"${x:,.0f}")
 prev_df['value_formatted'] = prev_df['value'].apply(lambda x: f"${x:,.0f}")
 
+# Sort latest_df by value for Current Portfolio table
+latest_df['value'] = pd.to_numeric(latest_df['value'], errors='coerce')
+latest_df = latest_df.sort_values(by='value', ascending=False)
+
 # Set index for comparison
 key_col = 'cusip'
 latest_df = latest_df.set_index(key_col)
 prev_df = prev_df.set_index(key_col)
 
+# Debug: Print unique CUSIPs
+print(f"Unique CUSIPs in latest_df: {len(latest_df.index.unique())}")
+print(f"Unique CUSIPs in prev_df: {len(prev_df.index.unique())}")
+
 # Additions
 additions = latest_df[~latest_df.index.isin(prev_df.index)]
 
@@ -115,10 +151,8 @@ changes = changes[changes['share_change'].notna()]
 changes = changes[abs(changes['share_change']) / changes['shrsOrPrnAmt_old'].replace(0, 1) > 0.1]
 changes['share_change'] = changes['share_change'].apply(lambda x: f"{x:,.0f}")
 # Add ticker_new for changes
-if 'ticker' in changes.columns:
-    changes['ticker_new'] = changes['ticker_new'].fillna('N/A')
-else:
-    changes['ticker_new'] = 'N/A'
+if 'ticker_new' not in changes.columns:
+    changes['ticker_new'] = changes['ticker'].fillna('N/A')
 
 # HTML table styling
 html_style = """
@@ -147,14 +181,19 @@ def df_to_html(df, columns, title):
     if df.empty:
         return f"<h3>{title} (0)</h3><p>None</p>"
     df_subset = df[columns].reset_index(drop=True)
+    # Limit all tables to top 50 by value
+    if len(df_subset) > 50:
+        df_subset = df_subset.head(50)
     return f"<h3>{title} ({len(df)})</h3>{df_subset.to_html(index=False, border=0, classes='table')}"
 
 # Summary as HTML
+latest_value_millions = latest_value / 1000  # Convert to millions for display
 summary = f"""
 <html>
 <head>{html_style}</head>
 <body>
 <h2>Point72 13F Changes {prev['periodOfReport']} to {latest['periodOfReport']}</h2>
+<p>Total Portfolio Value (Latest): ${latest_value_millions:,.0f}M</p>
 {df_to_html(additions, ['nameOfIssuer', 'ticker', 'shrsOrPrnAmt', 'value_formatted'], 'Additions')}
 {df_to_html(removals, ['nameOfIssuer', 'ticker', 'shrsOrPrnAmt', 'value_formatted'], 'Removals')}
 {df_to_html(changes, ['nameOfIssuer_new', 'ticker_new', 'share_change'], 'Changes')}