quantlib-physics
Calculate Shannon Entropy
Calculates the Shannon entropy of a discrete probability distribution, measuring the average information content or uncertainty. Shannon entropy is fundamental in information theory and is used to quantify the uncertainty in portfolio returns, market regimes, or trading signals. Higher entropy indicates greater uncertainty or diversity in outcomes.
Use Cases:
- Measure uncertainty in portfolio return distributions
- Quantify information content in market signals
- Assess diversity in asset allocations
- Evaluate predictability of financial time series
- Compare information efficiency across markets
Formula: H(X) = -Σ p(x) log(p(x))
Credits: 5 credits per request (Pro Tier) [Tier: ENTERPRISE, Credits: 10]
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