Obtaining Portfolios Along the Entire Efficient Frontier
The most basic way to obtain optimal portfolios is to obtain points over the entire range of the efficient frontier.
Given a portfolio optimization problem in a Portfolio
object, the estimateFrontier
function computes efficient portfolios spaced evenly according to the return proxy from the minimum to maximum return efficient portfolios. The number of portfolios estimated is controlled by the hidden property defaultNumPorts
which is set to 10
. A different value for the number of portfolios estimated is specified as an input argument to estimateFrontier
. This example shows the default number of efficient portfolios over the entire range of the efficient frontier.
m = [ 0.05; 0.1; 0.12; 0.18 ]; C = [ 0.0064 0.00408 0.00192 0; 0.00408 0.0289 0.0204 0.0119; 0.00192 0.0204 0.0576 0.0336; 0 0.0119 0.0336 0.1225 ]; p = Portfolio; p = setAssetMoments(p, m, C); p = setDefaultConstraints(p); pwgt = estimateFrontier(p); disp(pwgt)
0.8891 0.7215 0.5540 0.3865 0.2190 0.0515 0 0 0 0 0.0369 0.1289 0.2209 0.3129 0.4049 0.4969 0.4049 0.2314 0.0579 0 0.0404 0.0567 0.0730 0.0893 0.1056 0.1219 0.1320 0.1394 0.1468 0 0.0336 0.0929 0.1521 0.2113 0.2705 0.3297 0.4630 0.6292 0.7953 1.0000
If you want only four portfolios, you can use estimateFrontier
with NumPorts
specified as 4
.
pwgt = estimateFrontier(p, 4); disp(pwgt)
0.8891 0.3865 0 0 0.0369 0.3129 0.4049 0 0.0404 0.0893 0.1320 0 0.0336 0.2113 0.4630 1.0000
Starting from the initial portfolio, estimateFrontier
also returns purchases and sales to get from your initial portfolio to each efficient portfolio on the efficient frontier. For example, given an initial portfolio in pwgt0
, you can obtain purchases and sales:
pwgt0 = [ 0.3; 0.3; 0.2; 0.1 ]; p = setInitPort(p, pwgt0); [pwgt, pbuy, psell] = estimateFrontier(p); display(pwgt)
pwgt = 4×10
0.8891 0.7215 0.5540 0.3865 0.2190 0.0515 0 0 0 0
0.0369 0.1289 0.2209 0.3129 0.4049 0.4969 0.4049 0.2314 0.0579 0
0.0404 0.0567 0.0730 0.0893 0.1056 0.1219 0.1320 0.1394 0.1468 0
0.0336 0.0929 0.1521 0.2113 0.2705 0.3297 0.4630 0.6292 0.7953 1.0000
display(pbuy)
pbuy = 4×10
0.5891 0.4215 0.2540 0.0865 0 0 0 0 0 0
0 0 0 0.0129 0.1049 0.1969 0.1049 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0.0521 0.1113 0.1705 0.2297 0.3630 0.5292 0.6953 0.9000
display(psell)
psell = 4×10
0 0 0 0 0.0810 0.2485 0.3000 0.3000 0.3000 0.3000
0.2631 0.1711 0.0791 0 0 0 0 0.0686 0.2421 0.3000
0.1596 0.1433 0.1270 0.1107 0.0944 0.0781 0.0680 0.0606 0.0532 0.2000
0.0664 0.0071 0 0 0 0 0 0 0 0
If you do not specify an initial portfolio, the purchase and sale weights assume that your initial portfolio is 0
.
See Also
Portfolio
| estimateFrontier
| estimateFrontierLimits
| estimatePortMoments
| estimateFrontierByReturn
| estimatePortReturn
| estimateFrontierByRisk
| estimatePortRisk
| estimateFrontierByRisk
| estimateMaxSharpeRatio
| setSolver
Related Examples
- Estimate Efficient Portfolios for Entire Efficient Frontier for Portfolio Object
- Creating the Portfolio Object
- Working with Portfolio Constraints Using Defaults
- Estimate Efficient Frontiers for Portfolio Object
- Asset Allocation Case Study
- Portfolio Optimization Examples Using Financial Toolbox
- Portfolio Optimization with Semicontinuous and Cardinality Constraints
- Black-Litterman Portfolio Optimization Using Financial Toolbox
- Portfolio Optimization Using Factor Models
- Portfolio Optimization Using Social Performance Measure
- Diversify Portfolios Using Custom Objective