alg_RPP_theoretical: Peservation Price Policy for Portfolio Selection (RPP)

In ngloe/olpsR: Algorithms and functions for On-line Portfolio Selection

Description

computes the Reservation Price Policy Algorithm by El-Yaniv applied to the portfolio selection problem

Usage

alg_RPP_theoretical(returns, PR = "uni")

Arguments

returns	Matrix of price relatives, i.e. the ratio of the closing (opening) price today and the day before (use function get_price_relatives to calculate from asset prices).
PR	preemption rule: possible values are "uni" and "maxQ".

Details

The idea of RPP is to decide for each asset whether to convert it into another asset at at each time instant t = 1, ..., T based the Reservation Price algorithm by El-Yaniv. For more details see Gloeckner et al.

Value

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

Note

The print method for OLP objects prints only a short summary.

References

El-Yaniv, R.: Competitive Solutions for Online Financial Problems. In: ACM Comput. Surv. 30.1 (Mar. 1998), pp. 28-69.

Gloeckner, N.; Dochow, R.; Schmidt, G.: Reservation Price Policy for the Conversion and Portfolio Selection Problem, working paper, 2016.

Examples

# load data
data(NYSE)
# select stocks
x = cbind(kinar=NYSE$kinar, iroqu=NYSE$iroqu)

# compute RPP algorithm
RPP = alg_RPP_theoretical(x); RPP
plot(RPP)

ngloe/olpsR documentation built on May 23, 2019, 4:42 p.m.