[Eventstudies-commits] r415 - pkg/vignettes

[noreply at r-forge.r-project.org]

Author: chiraganand
Date: 2015-04-08 17:00:21 +0200 (Wed, 08 Apr 2015)
New Revision: 415

Modified:
   pkg/vignettes/eventstudies.Rnw
Log:
Fixed market model, reduced event window to 5.

Modified: pkg/vignettes/eventstudies.Rnw
===================================================================
--- pkg/vignettes/eventstudies.Rnw	2015-03-31 19:35:06 UTC (rev 414)
+++ pkg/vignettes/eventstudies.Rnw	2015-04-08 15:00:21 UTC (rev 415)
@@ -81,7 +81,7 @@
 <<no-adjustment>>=
 es <- eventstudy(firm.returns = StockPriceReturns,
                  event.list = SplitDates,
-                 event.window = 10,
+                 event.window = 5,
                  type = "None",
                  to.remap = TRUE,
                  remap = "cumsum",
@@ -90,7 +90,7 @@
 @ 
 
 This runs an event study using events listed in \emph{SplitDates}, and using
-returns data for the firms in \emph{StockPriceReturns}. An event window of 10
+returns data for the firms in \emph{StockPriceReturns}. An event window of 5
 days is analysed.
 
 Event studies with returns data typically do some kind of adjustment
@@ -115,7 +115,7 @@
 The object returned by eventstudy is of \texttt{class} `es'. It is a list with
 two components. Three of these are just a record of the way
 \texttt{eventstudy()} was run: the inference procedure adopted (``\texttt{bootstrap}''
-inference in this case), the window width (10 in this case) and the
+inference in this case), the window width (5 in this case) and the
 method used for mapping the data (``\texttt{cumsum}''). The two new things are
 `\texttt{outcomes}' and `\texttt{result}'.
 
@@ -144,7 +144,7 @@
 Plot and print methods for the class `es' are supplied. The standard
 plot is illustrated in Figure \ref{f:esplot1}. In this case, we see
 the 95\% confidence interval is above 0 and below 0 and in no case can
-the null of no-effect, compared with the starting date (10 days before
+the null of no-effect, compared with the starting date (5 days before
 the stock split date), be rejected.
 
 In this first example, raw stock market returns was utilised in the
@@ -166,14 +166,14 @@
 improved statistical efficiency as $\textrm{Var}(\epsilon_j) <
 \textrm{Var}(r_j)$.
 
-This is invoked by setting \texttt{type} to ``\texttt{marketResidual}'':
+This is invoked by setting \texttt{type} to ``\texttt{marketModel}'':
 
 <<mm-adjustment>>=
 data(OtherReturns)
 es.mm <- eventstudy(firm.returns = StockPriceReturns,
                     event.list = SplitDates,
-                    event.window = 10,
-                    type = "marketResidual",
+                    event.window = 5,
+                    type = "marketModel",
                     to.remap = TRUE,
                     remap = "cumsum",
                     inference = TRUE,
@@ -182,7 +182,7 @@
                     )
 @ 
 
-In addition to setting \texttt{type} to ``\texttt{marketResidual}'', we are now required
+In addition to setting \texttt{type} to ``\texttt{marketModel}'', we are now required
 to supply data for the market index, $r_{Mt}$. In the above example,
 this is the data object `\texttt{NiftyIndex}' supplied from the \emph{OtherReturns} data
 object in the package. This is just a zoo vector with daily returns of
@@ -230,7 +230,7 @@
 <<amm-adjustment>>=
 es.amm <- eventstudy(firm.returns = StockPriceReturns,
                     event.list = SplitDates,
-                    event.window = 10,
+                    event.window = 5,
                     type = "lmAMM",
                     to.remap = TRUE,
                     remap = "cumsum",
@@ -256,10 +256,10 @@
 interval at date 0 as a measure of efficiency.
 
 <<efficiency-comparison,results=verbatim>>=
-tmp <- rbind(es$result[10, ],
-             es.mm$result[10, ],
-             es.amm$result[10, ]
-             )[,c(1,3)]
+tmp <- rbind(es$result[5, ],
+             es.mm$result[5, ],
+             es.amm$result[5, ]
+             )[, c(1, 3)]
 rownames(tmp) <- c("None", "MM", "AMM")
 
 print(tmp["MM", ] - tmp["None", ])