[R-SIG-Finance] Re-Post: Performance Analytics Style Analysis

Thu Apr 1 16:36:31 CEST 2010

rollapply works on each column independently unless you use
by.column=FALSE. Also style.fit()$weights returns a data frame which
is not permitted.  Try this:

sf <- function(x) style.fit(x[,1], x[,-1])$weights[[1]]
rollapply(as.zoo(S), width = 30, FUN = sf, by.column = FALSE)

See ?rollapply for more.

On Thu, Apr 1, 2010 at 10:18 AM, René Naarmann <rene.naarmann at gmx.de> wrote:
> Dear List, Dear Thomas,
>
> thank you for your idea of using rollapply. I have already tried to use
> rollapply and I also tried to use applySeries from the timeSeries
> Package but R returns an error message which I do not understand. Here is a
> brief example of what I would like to do:
> require(timeSeries)
> require(PerformanceAnalytics)
> btime <- timeSequence(from="1999-01-01", to="1999-03-31", by = "month")
> etime <- timeLastDayInMonth(btime)
> #btime and etime are vectors, first element in btime is the first day of
> January and the first element of etime is the last of January
>
> set.seed(123)
> DATA <- matrix(rnorm(270), ncol = 3)
> colnames(DATA) <- LETTERS[1:3]
> datats <- timeSequence(from="1999-01-01", to="1999-03-31", by = "day")
> S <- timeSeries(DATA, datats)
> #S is a Matrix of class timeSeries with 3 columns of Data.
> #In the next step I would like to use the function style.fit from the
> package PerformanceAnalytics. I use the following code:
>
> applySeries(S, btime, etime, FUN = function(x) style.fit(x[,1],
> x[,-1])$weights)
> #this returns a error message which I do not understand: "Fehler in if
> (facCol[jj]) { : Fehlender Wert, wo TRUE/FALSE nötig ist"
>
> Any idea, what I am doing wrong? Am I using a wrong syntax or does
> applySeries not work with style.fit?
>
> Another idea is using rollapply but then I can not manage a specific time
> period, when using the following code
> rollapply(as.zoo(S), width = 30, FUN = function(x) style.fit(x[,1],
> x[,-1])$weights)
> #this returns the error message: "Fehler in switch(method, vector = { :
> Element 1 ist leer; Der Teil der Argumentliste 'class' der berechnet wurde
> war: (x)"
> What is wrong with this code?
>
> Furthermore when using chart.RollingStyle with dailyreturns, the plot shows
> a black rectangle because the space between the bars is to narrow, how can I
> circumvent this problem? I am using a Laptop with a 15'' screen.
>
> thanks in advance
> René Naarmann
>
> Thomas Etheber schrieb:
>>
>> Dear Rene,
>>
>> why are you trying to circumvent the already implemented wrapper in
>> style.QPfit?
>> If I got your problem right, you could just slice your data to rolling
>> estimation windows and then forward it to style.QPfit. Did you already have
>> a look at rollapply, I didn't test it but I think this should work for your
>> purpose. In this case you will have to store the coefficients in each run,
>> so that you are able to calculate the unsystematic returns, e.g. in a loop.
>>
>> Hth
>> Thomas
>>
>>
>> René Naarmann schrieb:
>>>
>>> Hi all,
>>>
>>> thank you Julien for your thougts. I working with R 2.10.0 on Windows XP.
>>> I remembered the function applySeries and fapply respectively. I tried to
>>> calculate
>>> a variance covariance matrix over different periods. When this works I
>>> could go on with solve.QP which needs the Dmat.
>>>
>>> Here is an example:
>>> require(timeSeries)
>>> btime <- timeSequence(from="1999-01-01", to="1999-03-31", by = "month")
>>> etime <- timeLastDayInMonth(btime[-1])
>>> btime <- btime[-length(btime)]
>>> data1 <- rnorm(1:90)
>>> data2 <- matrix(rnorm(270), ncol = 3)
>>> colnames(data2) <- LETTERS[1:3]
>>> datats <- timeSequence(from="1999-01-01", to="1999-03-31", by = "day")
>>> S <- timeSeries(data2, datats)
>>> applySeries(S, btime, etime, FUN = function(x) cov(x,
>>> use="pairwise.complete.obs"))
>>> cov(window(S, start="1999-01-01", end="1999-02-28"))
>>>
>>> The result is a matrix which contains the varcov matrices for 2
>>> subperiods which is fine,
>>> but when I am using my real Data I receive this Message:
>>> Fehler in midnightStandard2(charvec, format) :  'charvec' has non-NA
>>> entries of different number of characters
>>> I don't understand this error message, can anyone help?
>>>
>>>
>>> I read my datafile from a spreadsheet via readSeries(), the head looks
>>> like this:
>>>                   R2G          R2V           R1G           R1V
>>>  MSCIWexUS
>>> 1999-01-04 -0.006477506  0.004066846 -0.0026417776 -0.0009521722
>>>  0.018939565
>>> 1999-01-05  0.001725935  0.002339151  0.0128278433  0.0116685255
>>>  0.006108505
>>> 1999-01-06  0.018860732  0.007514636  0.0211913231  0.0215123444
>>>  0.019311270
>>> 1999-01-07  0.005040827 -0.004752986 -0.0028397673  0.0013254882
>>> -0.005757679
>>> 1999-01-08  0.011525972  0.003911511 -0.0006109632  0.0101291838
>>>  0.001059926
>>> 1999-01-11  0.013880501 -0.005775207 -0.0039712968 -0.0108176871
>>> -0.011788948
>>>
>>> Thanks in advance
>>> René
>>>
>>>
>>> julien cuisinier schrieb:
>>>>
>>>> Hi René,
>>>>
>>>>
>>>>
>>>> For quad prog algo, look for solve.QP from quadprog package in R. It
>>>> should allow you to do what you want (if I understood well). Please note I
>>>> am not too familiar with the PerformanceAnalytics package & its capabilities
>>>> (but suspect its style analysis function is a wrapper for solve.QP).
>>>> Building a rolling window analysis is quite trivial from there.
>>>>
>>>> On another note, using 1 month data is probably too small to have stable
>>>> results (depending on how many factors in your style analysis - personal
>>>> rule of thumb is 10 times the number of factors gives you a benchmark of nbr
>>>> of data points needed) , I would look to include more returns in your linear
>>>> regression. One could look into applying some sort of weighting to your
>>>> regression to improve forecasting power (e.g. exponential weighting). I
>>>> guess you are also looking into the residuals for autocorrelation &
>>>> heteroskedasticity which will impact the hypothesis testing of your
>>>> betas/coefficients.
>>>>
>>>> & Finally, always best to make a question as concise as possible,
>>>> include a piece of reproducible code of what you are trying to do & some
>>>> system information (what R version, what OS) ... that often makes easier for
>>>> list member to help & follow (more or less) the posting guide.
>>>>
>>>>
>>>>
>>>> HTH
>>>> Julien
>>>>
>>>>
>>>> On Mar 16, 2010, at 12:04 AM, René Naarmann wrote:
>>>>
>>>>> Hi R-users,
>>>>>
>>>>> it is the first time for me writing to this group. I would be grateful
>>>>> if somebody could help me to find
>>>>> a solution to my problem.
>>>>>
>>>>> I am working on my final thesis and I would like to analyse the impact
>>>>> of return frequency
>>>>> using return-based style analysis. Specifically I would like to
>>>>> calculate attributable returns. An attributalbe return
>>>>> is the difference between the realised return of a fund and the
>>>>> forecast from using the estimated style coefficients
>>>>> multiplied by the respective indexseries.
>>>>>
>>>>> I am using the implemented functions for style analysis in the
>>>>> PerformanceAnalytics Package.
>>>>> I would like to use the quadratic programming algorithm just for each
>>>>> day in a specific month, i.e.
>>>>> use the daily returns from january to calculate the style weigths. This
>>>>> should be done month by month.
>>>>> In the next step the calculation should include two months of data and
>>>>> calculate the style weigths month by month.
>>>>>
>>>>> So far I tried to usw apply.month in combination with style.fit. This
>>>>> returns the same results for each month.
>>>>> In the next step I tried to use some code out of chart.RollingStyle. I
>>>>> change it for my purpose and
>>>>> receive the style weights in a rolling calculation and could enable the
>>>>> by option. So I get styleweights
>>>>> over a specific width and could shift the calculation by a specified
>>>>> block, i.e. calculate styleweigths
>>>>> for 20 days shifting this calculation by the next 20 days. What I would
>>>>> like to have is a shifting by month
>>>>> to use the last month realised daily returns to forecast the style
>>>>> weigths for the next month.
>>>>>
>>>>> Has somebody an idea how to handle this problem?
>>>>> Thank you in advance
>>>>>
>>>>> René Naarmann
>>>>>
>>>>> --
>>>>> E-Mail: rene.naarmann at mnet-online.de
>>>>>
>>>>> _______________________________________________
>>>>> R-SIG-Finance at stat.math.ethz.ch mailing list
>>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-finance
>>>>> -- Subscriber-posting only. If you want to post, subscribe first.
>>>>> -- Also note that this is not the r-help list where general R questions
>>>>> should go.
>>>>>
>>>>
>>>>
>>>>
>>>
>>
>>
>>
>>
>
> --
> René Naarmann
> An der Kirche 3B  30457 Hannover
> ---
> Tel.:   (0511)-461643
> Mobil:  (0170)-8100941
> E-Mail: rene.naarmann at gmx.de
>
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