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Financial Portfolio Optimization Algorithms

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Financial Portfolio Optimization Algorithms

Author: Mircea Marinescu

email: [e-mail]

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Contents

A. Risk based portfolio optimization algorithms:

1. Mixture CVaR (Conditional Value at Risk)
2. Mixture SMCR (Second Moment Coherent Risk)
3. MV (Mean Variance)
4. SD (Standard Deviation)
5. Mixture MAD (Mean Absolute Deviation)
6. Mixture LSSD (Lower Semi-Standard Deviation)
7. GINI (as in Corrado Gini - statistician 1884-1965)
8. MSGINI (Second Moment Gini dispersion measure)
9. Omega ratio (introduced by Con Keating and William F. Shadwick - 2002)

For each class of portfolios the following optimization strategies are available:

1. minimization of dispersion for a give expected rate of return
2. maximization of generalized Sharpe ratio
3. minimization of the inverse of generalized Sharpe ratio
4. minimum dispersion portfolio
5. Inverse-N risk optimal portfolio (optimal portfolio with the same dispersion measure as equal weighted portfolio)
6. maximization of expected rate of returns for a fixed value of risk aversion

B. "Naïve" portfolio strategies:

1. Constant weighted portfolio. A particular case is equal weighted portfolio.
2. Inverse volatility portfolio (i.e. portfolio weights are proportional to the inverse of asset volatilities)
3. Inverse variance portfolio (i.e. portfolio weights are proportional to the inverse of asset variances)
4. 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:

1. Kelly's portfolio (as in John Larry Kelly Jr. - scientist 1923-1965) - maximization of portfolio log returns

Utility functions:

1. Collect historical market data from a data provider (at this point only from alphavantage)
2. Generate business calendars (at this point only NYSE business calendar)
3. Generate rebalancing portfolio schedules