feat: Add institutional sponsorship check for CANSLIM strategy

src/screener/i_canslim.py

@@ -0,0 +1,88 @@
+from db.db_connection import create_client
+
+def check_institutional_sponsorship(symbol):
+    """
+    Determines if a stock has strong institutional sponsorship.
+
+    Criteria:
+    - Should have at least several institutional sponsors
+    - Look for increasing institutional ownership
+    - Focus on higher-quality institutions
+    - Avoid stocks with too much institutional ownership (>80-90%)
+
+    Args:
+        symbol (str): Stock ticker symbol.
+
+    Returns:
+        float: 1 (Pass), 0 (Fail), 0.25 (Insufficient Data)
+    """
+    client = create_client()
+
+    # Get current institutional ownership data
+    query = """
+        SELECT 
+            COUNT(DISTINCT holder_name) as num_institutions,
+            SUM(percentage_held) as total_ownership,
+            MAX(date_reported) as latest_date
+        FROM stock_db.yf_institutional_holders
+        WHERE ticker = '{}'
+        GROUP BY ticker
+    """.format(symbol)
+
+    result = client.query(query)
+
+    if not result.result_rows:
+        return 0.25  # Insufficient data
+
+    num_institutions, total_ownership, _ = result.result_rows[0]
+
+    # Get ownership trend (comparing with 3 months ago)
+    trend_query = """
+        WITH current AS (
+            SELECT SUM(percentage_held) as current_ownership,
+                   MAX(date_reported) as latest_date
+            FROM stock_db.yf_institutional_holders
+            WHERE ticker = '{}'
+        ),
+        previous AS (
+            SELECT SUM(percentage_held) as previous_ownership
+            FROM stock_db.yf_institutional_holders
+            WHERE ticker = '{}'
+            AND date_reported <= (SELECT latest_date - INTERVAL 3 MONTH FROM current)
+        )
+        SELECT current_ownership, previous_ownership
+        FROM current, previous
+    """.format(symbol, symbol)
+
+    trend_result = client.query(trend_query)
+
+    # Evaluate criteria
+    if num_institutions is None or total_ownership is None:
+        return 0.25
+
+    # Convert total_ownership to percentage (0-100 scale)
+    total_ownership = float(total_ownership)
+
+    # Criteria thresholds
+    MIN_INSTITUTIONS = 10
+    MIN_OWNERSHIP = 20  # percentage
+    MAX_OWNERSHIP = 85  # percentage
+
+    # Basic institutional presence check
+    has_sufficient_institutions = num_institutions >= MIN_INSTITUTIONS
+    has_healthy_ownership = MIN_OWNERSHIP <= total_ownership <= MAX_OWNERSHIP
+
+    # Check ownership trend
+    ownership_increasing = False
+    if trend_result.result_rows:
+        current_ownership, previous_ownership = trend_result.result_rows[0]
+        if current_ownership and previous_ownership:
+            ownership_increasing = current_ownership > previous_ownership
+
+    # Final evaluation
+    if has_sufficient_institutions and has_healthy_ownership and ownership_increasing:
+        return 1
+    elif not has_sufficient_institutions or total_ownership < MIN_OWNERSHIP:
+        return 0
+    else:
+        return 0.25  # Borderline cases