Financial Portfolio Optimization Algorithms
Project description
azapy
Financial Portfolio Optimization Algorithms
Author: Mircea Marinescu
email: Mircea.Marinescu@outlook.com
Install: pip install azapy
Contents
A. Risk based portfolio optimization algorithms:
- Mixture CVaR (Conditional Value at Risk)
- Mixture SMCR (Second Moment Coherent Risk)
- MV (Mean Variance)
- SD (Standard Deviation)
- Mixture MAD (Mean Absolute Deviation)
- Mixture LSSD (Lower Semi-Standard Deviation)
- GINI (as in Corrado Gini - statistician 1884-1965)
- MSGINI (Second Moment Gini dispersion measure)
- Omega ratio (introduced by Con Keating and William F. Shadwick - 2002)
For each class of portfolios the following optimization strategies are available:
- minimization of dispersion for a give expected rate of return
- maximization of generalized Sharpe ratio
- minimization of the inverse of generalized Sharpe ratio
- minimum dispersion portfolio
- Inverse-N risk optimal portfolio (optimal portfolio with the same dispersion measure as equal weighted portfolio)
- maximization of expected rate of returns for a fixed value of risk aversion
B. "Naïve" portfolio strategies:
- Constant weighted portfolio. A particular case is equal weighted portfolio.
- Inverse volatility portfolio (i.e. portfolio weights are proportional to the inverse of asset volatilities)
- Inverse variance portfolio (i.e. portfolio weights are proportional to the inverse of asset variances)
- Inverse drawdown portfolio (i.e. portfolio weights are proportional to the asset absolute value of maximum drawdowns over a predefined historical period)
C. Greedy portfolio optimization strategies:
- Kelly's portfolio (as in John Larry Kelly Jr. - scientist 1923-1965) - maximization of portfolio log returns
Utility functions:
- Collect historical market data from a data provider (at this point only from alphavantage)
- Generate business calendars (at this point only NYSE business calendar)
- Generate rebalancing portfolio schedules
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