From noreply at r-forge.r-project.org Thu Feb 26 09:07:05 2015 From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org) Date: Thu, 26 Feb 2015 09:07:05 +0100 (CET) Subject: [Eventstudies-commits] r405 - pkg/inst/tests Message-ID: <20150226080705.E2D5A1862BE@r-forge.r-project.org> Author: sargam_jain Date: 2015-02-26 09:07:05 +0100 (Thu, 26 Feb 2015) New Revision: 405 Added: pkg/inst/tests/test_compilation.txt Removed: pkg/inst/tests/test_INR.rda pkg/inst/tests/test_NiftyIndex.rda pkg/inst/tests/test_SplitDates.rda pkg/inst/tests/test_StockPriceReturns.rda pkg/inst/tests/test_USDINR.rda pkg/inst/tests/test_eventstudy.R pkg/inst/tests/test_firmExposuresData.rda pkg/inst/tests/test_inr_inference.R pkg/inst/tests/test_interfaces.R pkg/inst/tests/test_lmAMM.R pkg/inst/tests/test_marketresiduals.R pkg/inst/tests/test_y3c3.rda Log: Removed old test cases. Added the draft for new test cases to test for. Deleted: pkg/inst/tests/test_INR.rda =================================================================== (Binary files differ) Deleted: pkg/inst/tests/test_NiftyIndex.rda =================================================================== (Binary files differ) Deleted: pkg/inst/tests/test_SplitDates.rda =================================================================== (Binary files differ) Deleted: pkg/inst/tests/test_StockPriceReturns.rda =================================================================== (Binary files differ) Deleted: pkg/inst/tests/test_USDINR.rda =================================================================== (Binary files differ) Added: pkg/inst/tests/test_compilation.txt =================================================================== --- pkg/inst/tests/test_compilation.txt (rev 0) +++ pkg/inst/tests/test_compilation.txt 2015-02-26 08:07:05 UTC (rev 405) @@ -0,0 +1,209 @@ +###### Testing functions in eventstudies package ##### + +Tests are categorized as follows: +I. Tests for argument inputs (context: user input) +II. Tests for functionality (context: functionality) +III. Tests for aggregate function (context: aggregate) +IV. Example from book as test case (context: example) + +I. TESTS FOR ARGUMENT INPUTS + +1. Function phys2eventime + a) Check for following values for width: + # Normal values: + * 10 + * 1 + # Extreme values: + * zero + * +Inf + * -Inf + * Values greater than the no. of rows in dataframe StockPriceReturns + b) Check for following when zoo object with firm data and dates as index is a univariate series: + # If univariate series is input as vector (not matrix), then the function fails. + c) Check for following values for z (zoo object): + # Normal values: + * ? + * ? + # Extreme values: + * ? + * ? + d) Check for following values for event.list: + # Normal values: + * ? + * ? + # Extreme values: + * ? + * ? + +****************** Models ******************** + +2. Function marketModel + a) Check whether: # of rows in df(firm returns) = # of rows in df(market returns) + b) Check for extreme values of no. of rows and columns i.e. 1 row or 1 col in dataset + c) Check for residuals = TRUE (whether data is in returns or price format) + d) Check for class of arguments + +3. Function excessReturn + a) Check whether: # of rows in df(firm returns) = # of rows in df(market returns) + b) Check for extreme values of no. of rows and columns i.e. 1 row or 1 col in dataset + c) Check for class of arguments + +4. Function lmAMM + a) Check for whether X is the output of makeX or not (read makeX manual) + b) Check for other logical arguments (those with TRUE/FALSE) + +5. Function None + a) Check that no model arguments should be specified + + +************** Remap functions ************** + +6. Function remap.cumsum + a) Check for is.pc = TRUE (whether data is in percentage) + b) Check for following values of base: + # Normal values: + * 0 + * 100 + # Extreme values: + * -Inf + * Inf +7. Function remap.cumprod + a) Check for is.pc = TRUE (whether data is in percentage) + b) Check for is.pc = TRUE (whether data is in returns or price format) + c) Check for following values of base: + # Normal values: + * 0 + * 100 + # Extreme values: + * -Inf + * Inf + +************* Inference procedures *********** + +8. Function inference.bootstrap + a) Check for following values of boot.run: + # Normal values: + * 1000 + * 10 + # Extreme values: + * 0 + * Inf/ -Inf + b) Check for following values of es.w: + # Extreme values: + * ? + * ? +10. Function inference.wilcox + a) Check for following values of prob: + # Normal values: + * .10 + # Extreme values: + * Any value less than 0 and greater than 1 + b) Check for following values of es.w: + # Extreme values: + * ? + * ? + + +************************************************************************************************************ + +II. TESTS FOR FUNCTIONALITY + +1. Function phys2eventime + a) Check for list components returned by the function + b) Check for firm selected should not have NA in data for defined width + c) Check for class of arguments + d) Check for if the function handles following data discrepancies in events: + * Missing dates in eventlist + * Missing firm in eventlist + e) When zoo object with firm data and dates as index is a univariate series, + function must work if its a matrix of one column. + + +****************** Models ******************** + +2. Function marketModel + a) Check the working and results of regression analysis manually + +3. Function excessReturn + a) Check with small sample data whether the result is correct or not. + +4. Function lmaMM + a) Check for class of arguments + b) Check the working and results of regression analysis manually: difficult @leave this for now + @ remind to come up with test cases for lmAMM + +5. Function None + +************** Remap functions ************** +6. Function remap.cumsum + a) Cumulate by summing and tally + +7. Function remap.cumprod + a) Cumulate by multiplying and tally + +************* Inference procedures *********** + +8. Function inference.bootstrap @think and read + +9. Function inference.wilcox @think and read + +******************************************************************************** + +III. TESTS FOR AGGREGATE FUNCTION (eventstudy) + +10. Check the following for argument, event.window: + # Normal values: + * Any value less than no. of rows of firm.returns and greater than zero + # Extreme values: + * 0 + * Inf/ -Inf + * Any value greater than no. of rows of firm.returns and less than zero + b) Check that event.window does not overlap with estimation window (i.e. firm returns + used to estimate market returns through any of the described models. + +***************** Models ********************* + +10. Check the function for all the models using small data sets: + a) Check for the argument, type: by default, model type (argument in eventstudy + function) should be market model, else specify the type as any of the following: + # none + # lmAMM + # excessReturn + +***************** Remap functions ************ + +11. Check the function for logical argument to.remap (taking values TRUE/ FALSE): + a) for cumsum + b) for cumprod + +************* Inference procedures *********** + +12. Check the function for logical argument inference (taking values TRUE/ FALSE): +13. Check the function for the argument inference.strategy taking following values: + a) bootstrap + b) wilcoxin + + + + + +Function prepare.returns(): for (model != "None") and (number of returns > 1) + - Merge all the returns (firm.returns, currency, and/or market) + into one 'zoo' object. + - Convert the merged object for each event separately to event + time. + - Store the outcomes as attributes of the event time object. + - Return a 'list' of event time objects for each event. + 2. prepare.returns(): for (model = "None") and (number of returns = 1) + - Convert the whole zoo object 'firm.returns' to event time. + - Returns this object as a whole. + 3. Check whether all the outcomes are not "success". + 4. If model is not "None", run the model program for each object in + the returned list, and return the series index only within the + event window. + 5. If model is None, then directly return the series within the + event window. + 6. Check for any NULL values. + 7. Handle univariate output: convert to a single column zoo object. + 8. Perform remapping if asked by the user. + 9. Perform inference if asked by the user. Deleted: pkg/inst/tests/test_eventstudy.R =================================================================== --- pkg/inst/tests/test_eventstudy.R 2015-01-26 14:49:09 UTC (rev 404) +++ pkg/inst/tests/test_eventstudy.R 2015-02-26 08:07:05 UTC (rev 405) @@ -1,78 +0,0 @@ -context("phys2eventtime") - -test_that("test.phys2eventtime", { - -# An example dataset, with 3 firms -- -p <- structure(c(33.16, 34.0967, 35.3683, 34.46, 34.17, 35.89, 36.19, - 37.1317, 36.7033, 37.7933, 37.8533, 285.325, 292.6, - 290.025, 286.2, 290.075, 295.05, 289.325, 285.625, - 293.7, 298.5, 289.05, 704.5438, 708.35, 735.8375, - 710.625, 711.65, 731.0125, 727.575, 715.0187, 724.2, - 713.1875, 695.1812), .Dim = c(11L, 3L), .Dimnames = - list( NULL, c("ITC", "Reliance", "Infosys")), index = - structure(c(12418, 12419, 12422, 12423, 12424, 12425, - 12426, 12429, 12430, 12431, 12432), class = "Date"), - class = "zoo") -# An example events list -eventslist <- data.frame(name=c("ITC","Reliance","Infosys", - "ITC","Reliance","Junk"), - when=as.Date(c( - "2004-01-02", "2004-01-08", "2004-01-14", - "2005-01-15", "2004-01-01", "2005-01-01"))) -eventslist$name <- as.character(eventslist$name) - -# What we expect if we don't worry about width -- -rawres <- structure(list(z.e = structure(c(NA, NA, NA, NA, NA, NA, - NA, NA, 33.16, 34.0967, 35.3683, 34.46, 34.17, 35.89, 36.19, - 37.1317, 36.7033, 37.7933, 37.8533, NA, NA, NA, NA, 285.325, 292.6, - 290.025, 286.2, 290.075, 295.05, 289.325, 285.625, 293.7, 298.5, - 289.05, NA, NA, NA, NA, 704.5438, 708.35, 735.8375, 710.625, 711.65, - 731.0125, 727.575, 715.0187, 724.2, 713.1875, 695.1812, NA, NA, NA, - NA, NA, NA, NA, NA), .Dim = c(19L, 3L), .Dimnames = list( NULL, - c("1", "2", "3")), index = -9:9, class = "zoo"), outcomes = - structure(c(1L, 1L, 1L, 3L, 3L, 2L), .Label = c("success", - "unitmissing", "wrongspan" ), class = "factor")), .Names = c("z.e", - "outcomes")) - -cat("\nCheck without width handling ") -a <- phys2eventtime(p, eventslist,width=0) -expect_that(a, equals(rawres)) - -cat("\nCheck with width of 1 ") -a <- phys2eventtime(p, eventslist,width=1) -expect_that(a, equals(rawres)) - -# But when we go to width=2, column 1 and 3 drop off because they have -# only 1 obs before & after the event date respectively. -cat("\nCheck with width of 2 ") -a <- phys2eventtime(p, eventslist,width=2) -expect_that(a, equals(structure(list(z.e = structure(c(NA, NA, NA, NA, 285.325, - 292.6, 290.025, 286.2, 290.075, 295.05, - 289.325, 285.625, 293.7, 298.5, 289.05, - NA, NA, NA, NA), - index = -9:9, - class = "zoo"), - outcomes = structure(c(3L, 1L, 3L, 4L, 4L, 2L), - .Label = c("success", "unitmissing", - "wdatamissing", "wrongspan"), - class = "factor")), - .Names = c("z.e", "outcomes" )))) - -## Check the previous date -cat("\nTesting handling of missing data on event date: ") -eventdate <- as.Date("2004-01-10") -eventdate_output <- "2004-01-09" -eventslist <- data.frame(name = "ITC", when = eventdate, - stringsAsFactors = FALSE) -a <- phys2eventtime(p, eventslist, width = 2) -expect_that(as.numeric(a$z.e["0",]), - equals(as.numeric(p$ITC[as.Date(eventdate_output), ]))) - - -## events$when should be a time-based class -cat("\nTesting class of events$when: ") -eventdate <- "2004-01-09" -eventslist <- data.frame(name = "ITC", when = eventdate, - stringsAsFactors = FALSE) -expect_error(a <- phys2eventtime(p, eventslist, width = 2), regexp = "events\\$when.*class.*$") -}) Deleted: pkg/inst/tests/test_firmExposuresData.rda =================================================================== (Binary files differ) Deleted: pkg/inst/tests/test_inr_inference.R =================================================================== --- pkg/inst/tests/test_inr_inference.R 2015-01-26 14:49:09 UTC (rev 404) +++ pkg/inst/tests/test_inr_inference.R 2015-02-26 08:07:05 UTC (rev 405) @@ -1,45 +0,0 @@ -context("INR Inference") - -test_that("test.inr.inference", { -library(eventstudies) - -load("test_INR.rda") - -inr_returns <- diff(log(INR))[-1] - -eventslist <- data.frame(when=as.Date(c( - "2010-04-20","2010-07-02","2010-07-27", - "2010-09-16","2010-11-02","2011-01-25", - "2011-03-17","2011-05-03","2011-06-16", - "2011-07-26") - ), - name=rep("inr",10) - ) - -event_time_data <- phys2eventtime(inr_returns[, , drop = FALSE] , eventslist,width=10) -w <- window(event_time_data$z.e,start=-10,end=10) - -expect_that(inference.bootstrap(w, to.plot=FALSE)[,2], - equals(c(-0.000015327455, - -0.002526819039, - 0.001190000495, - 0.001193534934, - 0.001846733711, - -0.000105473215, - -0.001659771669, - 0.001644517771, - -0.001325235918, - 0.001546368579, - -0.000809734240, - -0.001499191073, - -0.000289413740, - -0.000003273428, - -0.000416661873, - -0.001150000190, - -0.000759748390, - 0.002306711019, - -0.0004872993296, - 0.001122457470, - 0.000635889955))) -}) - Deleted: pkg/inst/tests/test_interfaces.R =================================================================== --- pkg/inst/tests/test_interfaces.R 2015-01-26 14:49:09 UTC (rev 404) +++ pkg/inst/tests/test_interfaces.R 2015-02-26 08:07:05 UTC (rev 405) @@ -1,189 +0,0 @@ -context("eventstudy") - -test_that("test.interfaces", { - load("test_SplitDates.rda") - load("test_StockPriceReturns.rda") - load("test_NiftyIndex.rda") - load("test_USDINR.rda") - -### Basic event study with default args (market residuals) - cat("\nChecking market residuals interface: ") - expected_mean <- c(0, 0.0393985717416213, -0.7458035091065, - 0.457817077869512, 0.715714066835461, 2.33986420702835, - 2.37333344340029) - expected_outcomes <- c("success", "success") - - test_events <- data.frame(name = "ONGC", - when = as.Date(c("2011-08-01", "2010-05-14")), - stringsAsFactors = FALSE) - test_returns<- StockPriceReturns[complete.cases(StockPriceReturns$ONGC), "ONGC", - drop = FALSE] - test_es <- eventstudy(firm.returns = test_returns, - event.list = test_events, - event.window = 3, - model.args = list(market.returns = NiftyIndex)) - - expect_that(expected_mean, equals(test_es$result[, "Mean"])) - expect_that(expected_outcomes, equals(test_es$outcomes)) - expect_is(test_es, "es") - -### None - cat("\nChecking no model output: ") - expected_mean <- c(0, -0.197406699931557, -0.804299958306487, - 0.0135570496689663, -0.418062964428412, - 0.904144365357373, -0.806779427723603) - expected_outcomes <- c("success", "success") - - test_events <- data.frame(name = "ONGC", - when = as.Date(c("2011-08-01", "2010-05-14")), - stringsAsFactors = FALSE) - test_returns<- StockPriceReturns[complete.cases(StockPriceReturns$ONGC), "ONGC", - drop = FALSE] - test_es <- eventstudy(firm.returns = test_returns, - event.list = test_events, - event.window = 3, - type = "None") - - expect_that(expected_mean, equals(test_es$result[, "Mean"])) - expect_that(expected_outcomes, equals(test_es$outcomes)) - expect_is(test_es, "es") - -### AMM interface - cat("\nChecking AMM interface: ") - expected_mean <- c(0, 0.135927645042554, -0.600457594252805, 0.631525565290171, - 0.871423869901684, 2.54741102266723, 2.5989730099384) - - expected_outcomes <- c("success", "success") - - test_events <- data.frame(name = "ONGC", - when = as.Date(c("2011-08-01", "2010-05-14")), - stringsAsFactors = FALSE) - test_returns<- StockPriceReturns[complete.cases(StockPriceReturns$ONGC), "ONGC", - drop = FALSE] - test_others <- USDINR - test_es <- eventstudy(firm.returns = test_returns, - event.list = test_events, - event.window = 3, - type = "lmAMM", - model.args = list(market.returns = NiftyIndex[index(USDINR)], - others = test_others)) - - expect_that(expected_mean, equals(test_es$result[, "Mean"])) - expect_that(expected_outcomes, equals(test_es$outcomes)) - expect_is(test_es, "es") - -### Excess return - cat("\nChecking excess return interface: ") - expected_mean <- c(0, 0.138567158395153, -0.631185954448288, 0.701644918222266, - 1.15001275036422, 2.88646832315114, 3.32315429568726) - expected_outcomes <- c("success", "success") - - test_events <- data.frame(name = "ONGC", - when = as.Date(c("2011-08-01", "2010-05-14")), - stringsAsFactors = FALSE) - test_returns<- StockPriceReturns[complete.cases(StockPriceReturns$ONGC), "ONGC", - drop = FALSE] - - test_es <- eventstudy(firm.returns = test_returns, - event.list = test_events, - event.window = 3, - type = "excessReturn", - model.args = list(market.returns = NiftyIndex)) - - expect_that(expected_mean, equals(test_es$result[, "Mean"])) - expect_that(expected_outcomes, equals(test_es$outcomes)) - expect_is(test_es, "es") - -### Remapping - cat("\nChecking remapping: ") - test_events <- data.frame(name = "ONGC", - when = as.Date(c("2011-08-01", "2010-05-14")), - stringsAsFactors = FALSE) - test_returns <- StockPriceReturns[complete.cases(StockPriceReturns$ONGC), "ONGC", - drop = FALSE] - - ## cumsum - test_es <- eventstudy(firm.returns = test_returns, - event.list = test_events, - event.window = 3, - type = "None", - to.remap = FALSE, - remap = "cumsum") - - test_es_remap <- eventstudy(firm.returns = test_returns, - event.list = test_events, - event.window = 3, - type = "None", - to.remap = TRUE, - remap = "cumsum") - - expect_false(isTRUE(all.equal(test_es, test_es_remap))) - - ## cumprod - test_es <- eventstudy(firm.returns = test_returns, - event.list = test_events, - event.window = 3, - type = "None", - to.remap = FALSE, - remap = "cumprod") - - test_es_remap <- eventstudy(firm.returns = test_returns, - event.list = test_events, - event.window = 3, - type = "None", - to.remap = TRUE, - remap = "cumprod") - - expect_false(isTRUE(all.equal(test_es, test_es_remap))) - -### Inference - cat("\nChecking inference interface: ") - ## bootstrap - test_es_inference <- eventstudy(firm.returns = test_returns, - event.list = test_events, - event.window = 3, - type = "None", - inference = TRUE, - inference.strategy = "bootstrap") - - test_es <- eventstudy(firm.returns = test_returns, - event.list = test_events, - event.window = 3, - type = "None", - inference = FALSE, - inference.strategy = "bootstrap") - - expect_false(isTRUE(all.equal(test_es, test_es_inference))) - - ## wilcoxon - test_es_inference <- eventstudy(firm.returns = test_returns, - event.list = test_events, - event.window = 3, - type = "None", - inference = TRUE, - inference.strategy = "wilcoxon") - - test_es <- eventstudy(firm.returns = test_returns, - event.list = test_events, - event.window = 3, - type = "None", - inference = FALSE, - inference.strategy = "wilcoxon") - - expect_false(isTRUE(all.equal(test_es, test_es_inference))) - -}) # end test_that() - -test_that("test.arguments", { - load("test_StockPriceReturns.rda") - - cat("\nChecking single series handling: ") - test_events <- data.frame(name = "ONGC", - when = c("2011-08-01", "2010-05-14"), - stringsAsFactors = FALSE) - test_returns<- StockPriceReturns$ONGC - expect_error(eventstudy(firm.returns = test_returns, - event.list = test_events, - event.window = 3, - type = "None")) -}) Deleted: pkg/inst/tests/test_lmAMM.R =================================================================== --- pkg/inst/tests/test_lmAMM.R 2015-01-26 14:49:09 UTC (rev 404) +++ pkg/inst/tests/test_lmAMM.R 2015-02-26 08:07:05 UTC (rev 405) @@ -1,126 +0,0 @@ -context("lmAMM") - -test_that("test.lmAMM", { - load("test_firmExposuresData.rda") - - firm.returns <- firmExposuresData$Company_A - market.returns <- firmExposuresData$NIFTY_INDEX - inrusd <- firmExposuresData$usdinr - rM3 <- firmExposuresData$baa - - cat("\nDoing Testcase P2") - X <- makeX(market.returns, others=inrusd, - switch.to.innov=FALSE, market.returns.purge=FALSE, verbose=FALSE) - a <- lmAMM(firm.returns, X, nlags=0, verbose=FALSE) - expect_that(c(a$exposures, a$s.exposures), - equals(structure(c(0.716160223601197,-0.673093436292401, - 0.152101606133946,1.02143820457251), - .Names = c("market.returns", "z", "market.returns", "z")), tolerance=1e-1)) - - cat("\nDoing Testcase P3") - X <- makeX(market.returns, others=inrusd, - switch.to.innov=TRUE, market.returns.purge=FALSE, verbose=FALSE) - a <- lmAMM(firm.returns, X, nlags=0, verbose=FALSE) - expect_that(c(a$exposures, a$s.exposures), - equals(structure(c(0.716160223601197,-0.673093436292401, - 0.152100337597009,1.02146106755333), - .Names = c("market.returns", "z", "market.returns", "z")), tolerance=1e-1)) - - cat("\nDoing Testcase P4") - a <- lmAMM(firm.returns, X, nlags=1, verbose=FALSE) - expect_that(c(a$exposures, a$s.exposures), - equals(structure(c( 0.736264286484902, -1.450805, - 0.177929844631439, 1.646730), - .Names = c("market.returns","z", "market.returns", "z")),tolerance=1e-1)) - - - cat("\nDoing Testcase P5") - X <- makeX(market.returns, others=inrusd, - switch.to.innov=TRUE, market.returns.purge=TRUE, nlags=1, verbose=FALSE) - a <- lmAMM(firm.returns, X, nlags=1, verbose=FALSE) - expect_that(c(a$exposures, a$s.exposures), - equals(structure(c(0.7365566,-2.340171, - 0.1653025, 1.1436666), - .Names = c("market.returns", "z", "market.returns", "z")),tolerance=1e-1)) - - cat("\nDoing Testcase P6") - X <- makeX(market.returns, others=cbind(inrusd, rM3), - switch.to.innov=c(FALSE, FALSE), market.returns.purge=FALSE, verbose=FALSE) - a <- lmAMM(firm.returns, X, nlags=0, verbose=FALSE) - expect_that(c(a$exposures, a$s.exposures), - equals(structure(c(0.7230599,-0.7642377, - 0.207374104922771,0.173380799334299, - 1.01806122963342,0.467821650129292), - .Names = c("market.returns", "inrusd", "rM3", "market.returns", "inrusd", "rM3")),tolerance=1e-1)) - - cat("\nDoing Testcase P7") - X <- makeX(market.returns, others=cbind(inrusd, rM3), - switch.to.innov=c(TRUE, TRUE), market.returns.purge=TRUE, nlags=1, verbose=FALSE) - a <- lmAMM(firm.returns, X, nlags=1, verbose=FALSE) - - expect_that(c(a$exposures, a$s.exposures), - equals(structure(c(0.7482719,-1.9468851,-0.4802211, - 0.1740678,1.2455112,0.6146619), - .Names = c("market.returns", "inrusd", "rM3", "market.returns", "inrusd", "rM3")),tolerance=1e-1)) - -################################################################################ - # # - # THE NEXT CASES TESTS THE FUNCTION FOR THREE COMPANIES FOR THREE YEARS # - # # -################################################################################ - - - cat("\nDoing Testcases P8\n") - load("test_y3c3.rda") - - NIFTY_INDEX <- y3c3$NIFTY_INDEX - INRUSD <- y3c3$INRUSD - Company_A <- y3c3$Company_A - Company_B <- y3c3$Company_B - Company_C <- y3c3$Company_C - - regressors <- makeX(NIFTY_INDEX, others=INRUSD, - switch.to.innov=TRUE, market.returns.purge=TRUE, nlags=1, - dates=as.Date(c("2005-01-15","2006-01-07","2007-01-06", - "2008-01-05","2009-01-03")), verbose=FALSE) - - regressand <- cbind(Company_A,Company_B,Company_C) - - res <- manyfirmssubperiod.lmAMM(regressand,regressors,lags=1, - dates=as.Date(c("2005-01-15","2006-01-07","2007-01-06", - "2008-01-05","2009-01-03")),periodnames=c("P1","P2","P3","P4"), - verbose=FALSE) - - expect_that(as.data.frame(res), - - equals(structure(list(market.returns.P1 = c(0.756294904326272, 0.359467326140834,0.914021428042946), - z.P1 = c(-2.23264294525560, -1.05654919420689,0.296635483126946), - market.returns.P2 = c(1.02094561445355, 0.988758963378838,0.879236409569888), - z.P2 = c(-4.72831391695047, -2.0508684999854,-1.02215809586573), - market.returns.P3 = c(1.20585808099744, 0.676388278572118,0.530718379431386), - z.P3 = c(-1.32677083522489, -2.74055730512260, -1.50032216697694), - market.returns.P4 = c(1.11331096371784, 0.437117737120777,0.663182186702262), - z.P4 = c(-2.05336868436562, -1.60350865767951,-0.466253391408585), - market.returns.P1 = c(0.143617135793294, 0.263130891045529,0.154272220123111), - z.P1 = c(1.20226371286803, 1.22122136357895,1.02442932195400), - market.returns.P2 = c(0.203037609116444, 0.123122376136099,0.121880488983820), - z.P2 = c(1.118400430819, 0.798694545623495,1.29755067543957), - market.returns.P3 = c(0.230304109532112, 0.289262660515515,0.164866239494693), - z.P3 = c(1.17618117392934, 0.795008683829453,0.650736332270758), - market.returns.P4 = c(0.231338818884745, 0.213858364836974,0.207154237634752), - z.P4 = c(0.771450066857429, 0.415931231130697,0.696448914066602), - market.returns.P1 = c(5.26604920888266, 1.36611602200152,5.9247311493511), - z.P1 = c(-1.85703263049467, -0.865157804896683,0.289561687438957), - market.returns.P2 = c(5.02835715460001, 8.0307007906172,7.21392256382075), - z.P2 = c(-4.2277468665565, -2.56777576762391,-0.787759673062059), - market.returns.P3 = c(5.23593818385294, 2.33831866638673,3.21908464133114), - z.P3 = c(-1.12803270842405, -3.44720423923131,-2.30557614900882), - market.returns.P4 = c(4.81246929972659, 2.04395903547657,3.20139329165723), - z.P4 = c(-2.66170005367969, -3.85522542589652,-0.669472493949494)), - .Names = c("market.returns.P1", "z.P1", "market.returns.P2","z.P2", "market.returns.P3", "z.P3", - "market.returns.P4", "z.P4", "market.returns.P1", "z.P1","market.returns.P2", "z.P2", "market.returns.P3", "z.P3", - "market.returns.P4", "z.P4", "market.returns.P1", "z.P1", "market.returns.P2", "z.P2", "market.returns.P3", - "z.P3", "market.returns.P4", "z.P4"), - row.names = c("Company_A","Company_B", "Company_C"), class = "data.frame"), - check.attributes=FALSE)) -}) Deleted: pkg/inst/tests/test_marketresiduals.R =================================================================== --- pkg/inst/tests/test_marketresiduals.R 2015-01-26 14:49:09 UTC (rev 404) +++ pkg/inst/tests/test_marketresiduals.R 2015-02-26 08:07:05 UTC (rev 405) @@ -1,25 +0,0 @@ -context("Market residuals") - -test_that("test.market.residuals", { -library(eventstudies) - -load("test_StockPriceReturns.rda") -load("test_NiftyIndex.rda") - -alldata <- merge(StockPriceReturns, NiftyIndex, all = TRUE) -StockPriceReturns <- alldata[,-which(colnames(alldata) %in% "NiftyIndex")] -NiftyIndex <- alldata$NiftyIndex - -mm.result <- marketResidual(firm.returns=StockPriceReturns[,c("BHEL")], - market.returns=NiftyIndex) -mm.result <- xts(mm.result[complete.cases(mm.result),]) -colnames(mm.result) <- "BHEL" - -# Calculating manually -result <- lm(BHEL ~ NiftyIndex, data=StockPriceReturns) -resid.res <- xts(result$resid,as.Date(attr(result$resid,"names"))) -colnames(resid.res) <- "BHEL" - -expect_that(mm.result,equals(resid.res)) - -}) Deleted: pkg/inst/tests/test_y3c3.rda =================================================================== (Binary files differ)