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docs(features): clarify that gamma * S is intentional normalization (#33) #40

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docs(features): clarify that gamma * S is intentional normalization (#33) #40

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11 changes: 9 additions & 2 deletions src/features/greeks.py
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Expand Up @@ -68,15 +68,22 @@ def calculate_gamma(self, S: float, K: float, T: float, r: float,
option_type: 'CALL' or 'PUT'

Returns:
Gamma value normalized by underlying price
Price-scale-invariant gamma (raw gamma * S).

Raw Black-Scholes gamma scales as 1/S, so multiplying by S removes
the price-level dependence and yields a feature comparable across
underlyings of any price. This is intentionally the opposite
operation from theta and vega, whose raw values scale as S and are
therefore divided by S to achieve the same normalization. Do not
"fix" this to gamma / S: that would reintroduce price dependence.
"""
if T <= 0 or sigma <= 0 or S <= 0:
return 0.0

d1 = self._calculate_d1(S, K, T, r, sigma)
gamma = norm.pdf(d1) / (S * sigma * math.sqrt(T))

# Normalize by underlying price to get relative gamma
# Multiply by S so the result is price-scale-invariant (raw gamma ~ 1/S).
return float(gamma * S)

def calculate_theta(self, S: float, K: float, T: float, r: float,
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