Welcome to ClientVPS Mirrors

Introduction
library(xts)
## Loading required package: zoo
## 
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric

Introduction

This package allows users to apply customizable quantitative trading strategies to historical portfolio data. An S4 class called “Strategy” is implemented that creates objects from which vaious performance measurements may be extracted, visualized and compared. A template for custom quantitative strategies is available and so the package can be extended in an easy way and still all methods are available for consistent evaluations.

Structure of Strategy-Objects

A Strategy-object contains all relevant information about the strategy executed on the portfolio data. Dependent packages are zoo and xts.

Data

There is no data available within this package.

Examples

library(Strategy)

# Generate positive random walks for random assets
set.seed(2)
len <- 1000
n <- 10
assets <- abs(apply(matrix(rnorm(n*len), ncol=n), 2, cumsum)) + 100
colnames(assets) <- paste0("asset", 1:n)
assets <- xts(assets, order.by = seq(from=Sys.Date()-len, length.out=len, by="d"))

# MA(200)-strategy
myStrat.MA200 <- Strategy(assets = assets
                          , strat = "MA"
                          , strat.params = list(k=200))

plot of chunk unnamed-chunk-3

“He who gives up [code] safety for [code] speed deserves neither.” (via)

Need a high-speed mirror for your open-source project?
Contact our mirror admin team at info@clientvps.com.

This archive is provided as a free public service to the community.
Proudly supported by infrastructure from VPSPulse , RxServers , BuyNumber , UnitVPS , OffshoreName and secure payment technology by ArionPay.