quantlib-physics
Calculate Maximum Entropy Distribution
Computes the maximum entropy probability distribution subject to given moment constraints. The maximum entropy principle selects the least informative distribution consistent with constraints, avoiding unwarranted assumptions. Widely used in portfolio optimization, risk-neutral pricing, and statistical inference.
Use Cases:
- Portfolio optimization with return/variance constraints
- Risk-neutral density estimation from option prices
- Bayesian prior selection with limited information
- Robust probability modeling
- Market-implied distribution inference
Formula: Maximize H(P) = -Σ p_i log(p_i) subject to Σ f_k(i) p_i = μ_k
Credits: 5 credits per request (Pro Tier) [Tier: ENTERPRISE, Credits: 10]
POST
Authorizations
API key for authentication. Get your key at https://api.fincept.in/auth/register
Body
application/json
