Description Usage Arguments Details Value Note References Examples
copmutes the SCRP algorithm that directly adopts the Best Constant Rebalanced Portfolio until time t.
1 |
returns |
Matrix of price relatives, i.e. the ratio of the closing
(opening) price today and the day before (use function
|
method |
The method used to calculate BCRP. " |
... |
further arguments ( |
For the "approx
" method the calculation may require very much
memory dependend on the number of assets and the "step
" argument.
If an error occurs due to memory problems the "rand
" method may work.
Object of class OLP containing
Alg |
Name of the Algorithm |
Names |
vector of asset names in the portfolio |
Weights |
calculated portfolio weights as a vector |
Wealth |
wealth achieved by the portfolio as a vector |
mu |
exponential growth rate |
APY |
annual percantage yield (252 trading days) |
sigma |
standard deviation of exponential growth rate |
ASTDV |
annualized standard deviation (252 trading days) |
MDD |
maximum draw down (downside risk) |
SR |
Sharpe ratio |
CR |
Calmar ratio |
see also print.OLP
, plot.OLP
The print method for OLP
objects prints only a short summary.
Gaivoronski & Stella 2000, Stochastic Nonstationary Optimization for Finding Universal Portfolios http://mpra.ub.uni-muenchen.de/21913/
1 2 3 4 5 6 7 8 9 10 | # load data
data(NYSE)
# select stocks
returns = cbind(comme=NYSE$comme, kinar=NYSE$kinar)
# calculate BCRP
SCRP_rnd = alg_SCRP(returns, method="rand", samplings=1000); SCRP_rnd
SCRP_approx = alg_SCRP(returns, method="approx", step=0.05); SCRP_approx
plot(SCRP_rnd, SCRP_approx)
plot(SCRP_approx$Weights, type="l")
|
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