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Created September 6, 2013 18:04
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rCharts with ReturnAnalytics | Rolling Style Beta with French
Raw
code.R
#redo analysis with some interactivity
#original post is here
#http://timelyportfolio.blogspot.com/2011/11/after-reading-fine-article-style.html
#use Ken French momentum style indexes for style analysis
#http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/6_Portfolios_ME_Prior_12_2.zip
require(PerformanceAnalytics)
require(FactorAnalytics)
require(quantmod)
my.url="http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/6_Portfolios_ME_Prior_12_2.zip"
my.tempfile<-paste(tempdir(),"\frenchmomentum.zip",sep="")
my.usefile<-paste(tempdir(),"\6_Portfolios_ME_Prior_12_2.txt",sep="")
download.file(my.url, my.tempfile, method="auto",
quiet = FALSE, mode = "wb",cacheOK = TRUE)
unzip(my.tempfile,exdir=tempdir(),junkpath=TRUE)
#read space delimited text file extracted from zip
french_momentum <- read.table(file=my.usefile,
header = TRUE, sep = "",
as.is = TRUE,
skip = 12, nrows=1038)
colnames(french_momentum) <- c(paste("Small",
colnames(french_momentum)[1:3],sep="."),
paste("Large",colnames(french_momentum)[1:3],sep="."))
#get dates ready for xts index
datestoformat <- rownames(french_momentum)
datestoformat <- paste(substr(datestoformat,1,4),
substr(datestoformat,5,7),"01",sep="-")
#get xts for analysis
french_momentum_xts <- as.xts(french_momentum[,1:6],
order.by=as.Date(datestoformat))
french_momentum_xts <- french_momentum_xts/100
#get price series from monthly returns
french_price<-as.xts(
apply(1+coredata(french_momentum_xts[,1:6]),MARGIN=2,cumprod),
index(french_momentum_xts))
#check data for reasonability
plot.zoo(french_price,log="y")
#for this example lets use Bill Millers fund
getSymbols("LMVTX",from="1896-01-01", to=Sys.Date(), adjust=TRUE)
LMVTX <- to.monthly(LMVTX)
index(LMVTX) <- as.Date(format(as.Date(index(LMVTX)),"%Y-%m-01"))
LMVTX.roc <- ROC(LMVTX[,4],type="discrete",n=1)
perfComp <- na.omit(merge(LMVTX.roc,french_momentum_xts))
fit.time <- fitTimeSeriesFactorModel(
assets.names=colnames(perfComp[,1]),
factors.names=colnames(perfComp[,-1]),
data=perfComp,
fit.method="DLS"
)
betasRolling <- rollapply(perfComp, width = 36, by.column=FALSE, by=1, FUN = function(x){
fit.time <- fitTimeSeriesFactorModel(
assets.names=colnames(x[,1]),
factors.names=colnames(x[,-1]),
data=x,
fit.method="OLS"
)
return(fit.time$beta)
})
colnames(betasRolling) <- colnames(perfComp)[-1]
require(reshape2)
betasRolling.melt <- melt(data.frame(index(betasRolling),betasRolling),id.vars=1)
colnames(betasRolling.melt) <- c("date", "factor", "beta")
nBeta <- nPlot(
beta ~ date,
group = "factor",
data = na.omit(betasRolling.melt),
type = "lineChart"
)
#nBeta$chart(stacked = TRUE)
nBeta$xAxis(tickFormat =
"#!function(d) {return d3.time.format('%Y-%m-%d')(new Date(d * 24 * 60 * 60 * 1000));}!#"
)
nBeta
Raw
index.html
<!doctype HTML>
<meta charset = 'utf-8'>
<html>
<head>
<link rel='stylesheet' href="http://netdna.bootstrapcdn.com/bootswatch/2.3.1/cosmo/bootstrap.min.css">
<link rel="stylesheet" href="http://netdna.bootstrapcdn.com/twitter-bootstrap/2.3.1/css/bootstrap-responsive.min.css" >
<link rel='stylesheet' href="http://getbootstrap.com/2.3.2/assets/js/google-code-prettify/prettify.css">
<link rel='stylesheet' href="http://aozora.github.io/bootplus/assets/css/docs.css">
<link rel='stylesheet' href='http://nvd3.org/src/nv.d3.css'>
<script src='http://ajax.googleapis.com/ajax/libs/jquery/1.8.3/jquery.min.js' type='text/javascript'></script>
<script src='http://d3js.org/d3.v2.min.js' type='text/javascript'></script>
<script src='http://nvd3.org/nv.d3.js' type='text/javascript'></script>
<script src='http://nvd3.org/lib/fisheye.js' type='text/javascript'></script>
<style>
.rChart {
display: block
margin: auto auto;
width: 100%;
height: 400px;
}
/*
body {
margin-top: 60px;
}
*/
</style>
</head>
<body>
<div class='container'>
<div class='row'>
<div class='span8'>
<div class="bs-docs-example">
<div id='chart172c60a44598' class='rChart nvd3Plot nvd3'></div>
<br/>
<pre><code class='r'>#redo analysis with some interactivity
#original post is here
#http://timelyportfolio.blogspot.com/2011/11/after-reading-fine-article-style.html
#use Ken French momentum style indexes for style analysis
#http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/6_Portfolios_ME_Prior_12_2.zip
require(PerformanceAnalytics)
require(FactorAnalytics)
require(quantmod)
my.url=&quot;http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/6_Portfolios_ME_Prior_12_2.zip&quot;
my.tempfile&lt;-paste(tempdir(),&quot;\frenchmomentum.zip&quot;,sep=&quot;&quot;)
my.usefile&lt;-paste(tempdir(),&quot;\6_Portfolios_ME_Prior_12_2.txt&quot;,sep=&quot;&quot;)
download.file(my.url, my.tempfile, method=&quot;auto&quot;,
quiet = FALSE, mode = &quot;wb&quot;,cacheOK = TRUE)
unzip(my.tempfile,exdir=tempdir(),junkpath=TRUE)
#read space delimited text file extracted from zip
french_momentum &lt;- read.table(file=my.usefile,
header = TRUE, sep = &quot;&quot;,
as.is = TRUE,
skip = 12, nrows=1038)
colnames(french_momentum) &lt;- c(paste(&quot;Small&quot;,
colnames(french_momentum)[1:3],sep=&quot;.&quot;),
paste(&quot;Large&quot;,colnames(french_momentum)[1:3],sep=&quot;.&quot;))
#get dates ready for xts index
datestoformat &lt;- rownames(french_momentum)
datestoformat &lt;- paste(substr(datestoformat,1,4),
substr(datestoformat,5,7),&quot;01&quot;,sep=&quot;-&quot;)
#get xts for analysis
french_momentum_xts &lt;- as.xts(french_momentum[,1:6],
order.by=as.Date(datestoformat))
french_momentum_xts &lt;- french_momentum_xts/100
#get price series from monthly returns
french_price&lt;-as.xts(
apply(1+coredata(french_momentum_xts[,1:6]),MARGIN=2,cumprod),
index(french_momentum_xts))
#check data for reasonability
plot.zoo(french_price,log=&quot;y&quot;)
#for this example lets use Bill Millers fund
getSymbols(&quot;LMVTX&quot;,from=&quot;1896-01-01&quot;, to=Sys.Date(), adjust=TRUE)
LMVTX &lt;- to.monthly(LMVTX)
index(LMVTX) &lt;- as.Date(format(as.Date(index(LMVTX)),&quot;%Y-%m-01&quot;))
LMVTX.roc &lt;- ROC(LMVTX[,4],type=&quot;discrete&quot;,n=1)
perfComp &lt;- na.omit(merge(LMVTX.roc,french_momentum_xts))
fit.time &lt;- fitTimeSeriesFactorModel(
assets.names=colnames(perfComp[,1]),
factors.names=colnames(perfComp[,-1]),
data=perfComp,
fit.method=&quot;DLS&quot;
)
betasRolling &lt;- rollapply(perfComp, width = 36, by.column=FALSE, by=1, FUN = function(x){
fit.time &lt;- fitTimeSeriesFactorModel(
assets.names=colnames(x[,1]),
factors.names=colnames(x[,-1]),
data=x,
fit.method=&quot;OLS&quot;
)
return(fit.time$beta)
})
colnames(betasRolling) &lt;- colnames(perfComp)[-1]
require(reshape2)
betasRolling.melt &lt;- melt(data.frame(index(betasRolling),betasRolling),id.vars=1)
colnames(betasRolling.melt) &lt;- c(&quot;date&quot;, &quot;factor&quot;, &quot;beta&quot;)
nBeta &lt;- nPlot(
beta ~ date,
group = &quot;factor&quot;,
data = na.omit(betasRolling.melt),
type = &quot;lineChart&quot;
)
#nBeta$chart(stacked = TRUE)
nBeta$xAxis(tickFormat =
&quot;#!function(d) {return d3.time.format('%Y-%m-%d')(new Date(d * 24 * 60 * 60 * 1000));}!#&quot;
)
nBeta
</code></pre>
</div>
</div>
</div>
</div>
<script type='text/javascript'>
$(document).ready(function(){
drawchart172c60a44598()
});
function drawchart172c60a44598(){
var opts = {
"dom": "chart172c60a44598",
"width": 700,
"height": 400,
"x": "date",
"y": "beta",
"group": "factor",
"type": "lineChart",
"id": "chart172c60a44598"
},
data = 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var data = d3.nest()
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//instead of main would think a better default is opts.x
return opts.group === undefined ? opts.y : d[opts.group];
})
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nv.addGraph(function() {
var chart = nv.models[opts.type]()
.x(function(d) { return d[opts.x] })
.y(function(d) { return d[opts.y] })
.width(opts.width)
.height(opts.height)
chart.xAxis
.tickFormat(function(d) {return d3.time.format('%Y-%m-%d')(new Date(d * 24 * 60 * 60 * 1000));})
chart.yAxis
.tickFormat(function(d) {return d3.format('0.2f')(d);})
d3.select("#" + opts.id)
.append('svg')
.datum(data)
.transition().duration(500)
.call(chart);
nv.utils.windowResize(chart.update);
return chart;
});
};
</script>
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