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    <p>First of all, you should be storing your rules in a list, rather than a data.frame. This saves your from having to pad each "rule list" with NAs to make them the same length, and also allows you to process your data with <code>lapply</code>.</p> <p>Since you didn't provide any data, I made some up:</p> <pre><code>#Load data set.seed(42) library(quantmod) getSymbols('SPY') SPY &lt;- adjustOHLC(SPY) dat &lt;- dailyReturn(Cl(SPY)) #Add some TTRs for (rule in c('RSI', 'SMA')){ for (n in c(5, 10, 15, 20, 25)){ newvar &lt;- paste(rule, n, sep='_') FUN &lt;- get(rule) dat &lt;- cbind(dat, FUN(dat[,1], n=n)) names(dat)[length(names(dat))] &lt;- newvar } } dat &lt;- na.omit(dat) rulenames &lt;- names(dat)[-1] </code></pre> <p>Note that this is an <code>xts</code> object, not a data.frame. This is important, as it keeps the index in the <code>Date</code> format, rather than as a character vector:</p> <pre><code>&gt; dat[1:5, 1:5] daily.returns RSI_5 RSI_10 RSI_15 RSI_20 2007-02-08 -0.001308450 40.06379 46.99824 48.59484 49.11738 2007-02-09 -0.007447249 26.65296 40.34267 44.35689 46.10753 2007-02-12 -0.003404196 42.49883 45.94447 47.58264 48.30373 2007-02-13 0.008434995 67.89045 58.59450 55.64932 54.07276 2007-02-14 0.006567123 62.45177 56.28547 54.23836 53.08886 </code></pre> <p>I also made up some TTRs to use for each year</p> <pre><code>#Make a list of rules for each year library(lubridate) dat$Year &lt;- year(index(dat)) uniqueYear &lt;- sort(unique(dat$Year)) rulesList &lt;- lapply(uniqueYear, function(x) rulenames[runif(length(rulenames))&gt;.5]) names(rulesList) &lt;- uniqueYear </code></pre> <p>Note that my ruleList is literally a list:</p> <pre><code>&gt; rulesList $`2007` [1] "RSI_5" "RSI_10" "RSI_20" "RSI_25" "SMA_5" "SMA_10" "SMA_20" "SMA_25" $`2008` [1] "RSI_10" "RSI_15" "SMA_5" "SMA_10" "SMA_25" $`2009` [1] "RSI_5" "RSI_15" "RSI_20" "SMA_5" "SMA_15" "SMA_25" $`2010` [1] "RSI_5" "RSI_10" "RSI_20" "SMA_5" "SMA_20" "SMA_25" $`2011` [1] "RSI_20" "SMA_5" "SMA_10" "SMA_15" "SMA_20" "SMA_25" $`2012` [1] "RSI_20" "SMA_5" "SMA_10" "SMA_25" </code></pre> <p>Now it's simply a matter of looping through each year, and subsetting the <code>dat</code> object to the proper rows (year) and columns (TTRs):</p> <pre><code>#Apply the rules to each data.frame data.by.year &lt;- lapply(uniqueYear, function(year){ rule_subset &lt;- rulesList[[as.character(year)]] data_subset &lt;- dat[dat$Year==year, rule_subset] }) names(data.by.year) &lt;- uniqueYear </code></pre> <p>The <code>data.by.year</code> is a list (of length 6), where each element represent 1 year's worth of data, with the selected TTRs.</p> <pre><code>&gt; str(data.by.year[[1]]) An ‘xts’ object from 2007-02-08 to 2007-12-31 containing: Data: num [1:226, 1:8] 40.1 26.7 42.5 67.9 62.5 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:8] "RSI_5" "RSI_10" "RSI_20" "RSI_25" ... Indexed by objects of class: [Date] TZ: xts Attributes: List of 3 $ tclass : chr "Date" $ tzone : chr "" $ na.action:Class 'omit' atomic [1:25] 1 2 3 4 5 6 7 8 9 10 ... .. ..- attr(*, "index")= num [1:25] 1.17e+09 1.17e+09 1.17e+09 1.17e+09 1.17e+09 ... &gt; </code></pre>
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    1. COThanks a lot Zach for your very valuable answer.
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