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import numpy as np
import yfinance as yf
import logging
def get_advanced_metrics(symbol):
"""
Master function to fetch all statistical, valuation, and daily data for a stock.
"""
try:
ticker = yf.Ticker(symbol)
info = ticker.info
# 1. Basic Stats (PE, PB) - Dividend Yield removed
valuation_stats = {
"PE Ratio": round(info.get("trailingPE"), 2) if info.get("trailingPE") else None,
"PB Ratio": round(info.get("priceToBook"), 2) if info.get("priceToBook") else None,
}
# 2. Risk Calculation
hist_6mo = ticker.history(period="6mo", auto_adjust=True)
if not hist_6mo.empty:
returns = hist_6mo['Close'].pct_change()
volatility = returns.std() * np.sqrt(252)
risk = round(float(volatility), 4)
else:
risk = None
# 3. Valuation Models (Graham Number)
eps = info.get("trailingEps")
bvps = info.get("bookValue")
graham_number = None
if eps and bvps and eps > 0 and bvps > 0:
graham_number = round(np.sqrt(22.5 * eps * bvps), 2)
valuation_models = {
"graham_number": graham_number
}
# 4. Latest Daily Data (OHLC, Volume)
hist_1d = ticker.history(period="1d", auto_adjust=True)
if not hist_1d.empty:
daily_data = {
"open": round(hist_1d['Open'].iloc[0], 2),
"high": round(hist_1d['High'].iloc[0], 2),
"low": round(hist_1d['Low'].iloc[0], 2),
"volume": int(hist_1d['Volume'].iloc[0])
}
else:
daily_data = {"open": None, "high": None, "low": None, "volume": None}
return {
"valuation_stats": valuation_stats,
"risk": risk,
"valuation_models": valuation_models,
"daily_data": daily_data
}
except Exception as e:
logging.error(f"Failed to get advanced metrics for {symbol}: {e}")
return None |