Adding indicators to basic charts
In my previous post I outlined quantmod library basic charting features. In this post, I am going to enrich such basic charting with additional plots specifically related to quantitative indicators. At the purpose, I am going to take advantage of Yahoo 2014 year share price.
library(quantmod)ticker <- "YHOO"
stock <- new.env()
startDate = as.Date("2014-01-01")
endDate = as.Date("2014-12-31")
getSymbols(ticker, source="yahoo", env = stock, from = startDate, to=endDate)## [1] "YHOO"share <- stock[[ticker]]Starting from the basic charting capability, I add 5-days and 10-days Exponential Moving Average (EMA).
chartSeries(share, type='line', theme = chartTheme("white"), TA=c(addEMA(5, col="red"), addEMA(10, col="blue")), TAsep=',')
Always starting from the basic charting capability, here below I add 20-days and 50-days Exponential Moving Average’s (EMA).
chartSeries(share, type='line', theme = chartTheme("white"), TA=c(addEMA(20, col="pink"), addEMA(50, col="cyan")), TAsep=',')
Herein below, I add Relative Strength Index (RSI) and Bollinger Bands.
chartSeries(share, type='line', theme = chartTheme("white"), TA=c(addRSI(),addBBands()), TAsep=',')
Herein below, I add Average Directional Index (ADX) and Commodity Channel Index (CCI).
chartSeries(share, type='line', theme = chartTheme("white"), TA=c(addADX(),addCCI() ), TAsep=',')
Herein below, I add Rate Of Change (ROC) and Williams Percent Range (WPR).
chartSeries(share, type='line', theme = chartTheme("white"), TA=c(addROC(),addWPR()), TAsep=',')
Herein below, I add parabolic Stop and Reversal (SAR) and Stochastic Momentum Indicator (SMI).
chartSeries(share, type='line', theme = chartTheme("white"), TA=c(addSAR(),addSMI() ), TAsep=',')
You may wonder how you can access the values associated to each indicator, here is how.
m <- addMACD()
head(m@TA.values, n=40)## macd signal
## 2014-01-02 NA NA
## 2014-01-03 NA NA
## 2014-01-06 NA NA
## 2014-01-07 NA NA
## 2014-01-08 NA NA
## 2014-01-09 NA NA
## 2014-01-10 NA NA
## 2014-01-13 NA NA
## 2014-01-14 NA NA
## 2014-01-15 NA NA
## 2014-01-16 NA NA
## 2014-01-17 NA NA
## 2014-01-21 NA NA
## 2014-01-22 NA NA
## 2014-01-23 NA NA
## 2014-01-24 NA NA
## 2014-01-27 NA NA
## 2014-01-28 NA NA
## 2014-01-29 NA NA
## 2014-01-30 NA NA
## 2014-01-31 NA NA
## 2014-02-03 NA NA
## 2014-02-04 NA NA
## 2014-02-05 NA NA
## 2014-02-06 NA NA
## 2014-02-07 -4.7171391 NA
## 2014-02-10 -4.1740120 NA
## 2014-02-11 -3.5420627 NA
## 2014-02-12 -3.0895738 NA
## 2014-02-13 -2.6125677 NA
## 2014-02-14 -2.2704118 NA
## 2014-02-18 -1.9594595 NA
## 2014-02-19 -1.7988565 NA
## 2014-02-20 -1.6567421 -2.868981
## 2014-02-21 -1.6321395 -2.621612
## 2014-02-24 -1.5671167 -2.410713
## 2014-02-25 -1.5324096 -2.235052
## 2014-02-26 -1.4116673 -2.070375
## 2014-02-27 -1.1210957 -1.880520
## 2014-02-28 -0.8387384 -1.672163In my next post, I will show how quantmod can be used to build a model for experimenting trading strategies.
