[Eventstudies-commits] r320 - /

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Mon May 12 12:52:23 CEST 2014


Author: chiraganand
Date: 2014-05-12 12:52:23 +0200 (Mon, 12 May 2014)
New Revision: 320

Modified:
   todo.org
Log:
Removed extra text.

Modified: todo.org
===================================================================
--- todo.org	2014-05-12 10:50:15 UTC (rev 319)
+++ todo.org	2014-05-12 10:52:23 UTC (rev 320)
@@ -47,253 +47,3 @@
 
 * plot.es
   - "Event study plot capabilities" email on 30th April.
-
-* Ajay's comments
-** On the eesPlot code
-   data.frmt2 <- data.use[which(data.use$cluster.pattern != 0), ]
-
-   Can we please have better variable names.
-
-   hilo1 <- c(-big, big)
-   plot.es.graph.both(es.good.normal, es.bad.normal, es.good.purged,
-   es.bad.purged, width, titlestring, ylab)
-
-   Can we please have better names than hilo1. And, you are making it and
-   not using it.
-
-** Feedback on eesPlot
-   Why do we have eesPlot?
-
-   When I look at the name, I think "Okay, this is a plot function, and
-   why is this not just an S3 plot method". When I see the first one line
-   description on the man page my opinion is confirmed.
-   
-   Then I look deeper and it is absolutely not a plot function! It is a
-   function which figures out a list of events, then runs an event study,
-   and then does a customised plot.
-   
-   We should not have such functions.
-   
-   We should ask the user to run ees() and then run eventstudy() and then
-   use the plot method.
-   
-   Perhaps we should ask the user to do:
-   
-   es.lefttail <- eventstudies(left tail)
-   es.righttail <- eventstudies(right tail)
-   plot(mfrow=c(2,1))
-   plot(es.lefttail, type="blah")
-   plot(es.righttail, type="blah")
-   
-   On an unrelated note, I found it disturbing that the code for
-   eesPlot() does not use ees(). This violates the principle of code
-   reuse. Perhaps we should have the framework where x<-ees() just makes
-   lists of interesting events and then summary(x) generates all those
-   descriptive tables about number of events and run length and so on.
-   
-   Why is the example saying "  ## Generating event study plots (using
-   modified event study methodology)". It looks gauche.
-   
-   There is one spelling mistake in the man page but I've forgotten where
-   it is.
-
-** Feedback on eventstudies::ees
-   1. The entire concept of what we're doing is critically connected
-      to the choice of the event window!!!
-
-   The function and the documentation of the function is silent about
-   this and that's completely wrong.
-
-   Our concept of what's a clean unclustered event is : clean within a
-   stated event window. We never say this. And, it's bad software
-   engineering to hardcode this to a number. This must be an argument to
-   the function.
-
-   2. The title of the function and the first para of the function are
-   quite lame. They say:
-   
-   "This function generates summary statistics for identification and
-   analysis of extreme events.". This mostly leaves me in the dark
-   about what's going on.
-
-   "Tail (Rare) events are often the object of interest in finance.
-   These events are defined as those that have a low probability of
-   occurrence. This function identifies such events based on
-   prob.value mentioned by the user and generates summary
-   statistics about the events. If ‘prob.value’ is 2.5%, events
-   below
-   2.5% (lower tail) and above 97.5% (upper tail) of the
-   distribution
-   are identified as extreme events." This makes the function seem
-   like a massive waste of time. Using R we can trivially find the
-   upper tail observations - no new function is required here. If I
-   read this paragraph I would completely lose interest in the
-   package; I would think these lame developers are taking trivial
-   one/two lines of R code and encoding it as a function with a new
-   name - why would I never bother to learn their new API.
-   
-   The entire value added of the code lies in identifying clean
-   unclustered events, stabbing into messy situations by trying to fuse
-   clustered events under certain conditions, and walking away from
-   places where fusing can't be done. None of that is advertised in the
-   man page. The word 'fuse' does not occur anywhere on the man page!
-   
-   3. When I run the example I get a huge messy structure that's no
-   fun. Why not have: 
-   str(output, max.level=2)
-   which is more comprehensible.
-
-   4. Look at
-   
-      library(eventstudies)
-   data(EESData)
-   ## Input S&P 500 as the univariate series
-   input <- EESData$sp500
-   ## Constructing summary statistics for 5% tail values (5% on both
-   sides)
-   output <- ees(input, prob.value = 5)
-   str(output)
-   
-   It looks nicer and more readable as:
-   
-   library(eventstudies)
-   data(EESData)
-   r <- ees(EESData$sp500, prob.value = 5)
-   str(r, max.level=2)
-
-   5. Choose a consistent style. Is there going to be a
-      library(eventstudies) in front of all the examples? This was not
-      there with the others. Why is it here?
-   
-   6. Why are we saying "   To convert number to words, code uses
-      function “numbers2words†by
-      John Fox and “deprintize†function by Miron Kursa.". We are
-      using thousands of functions by others but is this a big deal?
-   
-   7. In
-   
-      $data$Clustered
-      event.series cluster.pattern
-      2000-03-16     2.524452               3
-      2003-03-17     3.904668               2
-
-      Perhaps the word `runlength' is universally understood instead of
-      cluster.pattern
-
-      The word `event.series' is incomprehensible to me.
-
-   8. In : 
-   
-      > output$upper.tail$extreme.event.distribution
-      unclstr used.clstr removed.clstr tot.clstr tot tot.used
-      upper      65          5            32        37 102       70
-
-      The column names are horrible.
-
-      Pick a more rational sequencing where this process unfolds from
-      left to right.
-
-      This table is the heart of the functionality of what's being done and
-      it isn't explained at all in the man page.
-
-      The man page should say that the researcher might like to only
-      study clean unclustered events - in which case he should run with
-      xxx. If he wishes to use the methodology of fusing adjacent events
-      as done in PSS, then additionally we are able to salvage the events
-      xxx.
-
-
-   9. The run length table should be defined as a table showing a
-      column which is the run length and a column which is the number
-      of events which are a run of that length.
-
-   10. Just confirming: In a package vignette we're going to be able
-       to reproduce some key results from the tables of PSS using this
-       function?
-    
-   11. Wouldn't it be neat to draw something graphical with
-       abline(v=xxx, lty=2) where all the extreme events are shown on
-       a picture? With a different colour for fused and for rejected
-       events.
-
-** Feedback on eventstudies package
-
-   First batch.
-
-   - At many places the phrase `eventstudy' is being used when what's
-     required is `event study'.
-
-   - When I say ?AMMData iqt is riddled with mistakes!!!! The man page
-     has four sentences and has more than 1 error per sentence.
-
-  1. The first few words read: "The data series is a daily time-series
-     zoo object. The sample range for the data is from 2012-02-01 to
-     2014-01-31." Why should this be the top priority?
-
-  2. The two sentences after this, which add up to the full man page,
-     contain one grammatical error each.
-
-  3. Nowhere in the man page is the unit mentioned (per cent).
-
-  4. The dataset contains call.money.rate and that's inconsistent with
-     the man page.
-
-  5. The example says library(zoo) which is not required.
-
-Why do we need a special data object named AMMData? Can we not just
-have one single example dataset with daily returns data for firms,
-that is used for the examples involving both event studies and AMM?
-
-If you had to have this in the package (which I doubt), a better
-example is:
-
-  data(AMMData)
-  str(AMMData)
-  tail(AMMData)
-  summary(AMMData)
-
-We in India use too many abbreviations. Let's stick to the phrase
-`augmented market model' instead of overusing the phrase AMM.
-
-
-*** When I say ?EESData I see a section `Format' which is not in ?AMMData.
-
-    The facts on this man page should say that this is a dataset for
-    the purpose of demonstrating the EES functionality (no
-    abbreviations please), and for replicating the results of the PSS
-    paper. It should explain what the data is (daily returns measured
-    in per cent).
-
-    - Why is the example here different from the example for AMMData?
-
-*** The dataset INR introduces a new word `sample' which was not used in the previous two.
-    Can we please have extreme maniacal consistency in all these?
-    As pointed out above, there is duplication between INR being here and
-    it being in AMMData.
-
-*** It is truly wrong to have a MMData data object!!
-    Nothing prevents you from estimating an MM using the data for an AMM.
-    Can we please be more intelligent about all this.
-
-** Collated
-   - bad variable names
-   - eesPlot: make it S3 function
-     - Do: ees(), eventstudy(), plot()
-   - summary.ees()
-   - ees(): event window in the API and the man pages (language + information)
-   - Remove comments from examples, plus cleaning
-   - Example consistency: remove library() calls from examples
-   - Remove unneeded references
-   - ees(): output colnames, output table format (+sequencing)
-   - ees(): reproducibility of PSS in the vignette
-   - plot.ees()
-   - Spell check
-   - Use "event study" instead of "eventstudy"
-   - Man pages: AMMData: grammatical errors, language, units,
-     consistent sections, call.money.rate
-   - EESData: say about PSS
-   - Avoid abbreviations
-   - Get rid of MMData, INR dataset
-   - lmAMM example
-   - phys2eventtime example
-   - Spell check



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