ch09data {FinTS} | R Documentation |
Financial time series used in examples in chapter 9.
data(m.fac9003) data(m.cpice16.dp7503) data(m.barra.9003) data(m.5cln) #data(m.bnd) <- documented with ch08, also used in ch09 data(m.apca0103)
m.fac9003 a zoo object of 168 observations giving simple excess returns of 13 stocks and the Standard and Poor's 500 index over the monthly series of three-month Treasury bill rates of the secondary market as the risk-free rate from January 1990 to December 2003. (These numbers are used in Table 9.1.)
AAAlcoa
AGEA. G. Edwards
CATCaterpillar
FFord Motor
FDXFedEx
GMGeneral Motors
HPQHewlett-Packard
KMBKimberly-Clark
MELMellon Financial
NYTNew York Times
PGProctor & Gamble
TRBChicago Tribune
TXNTexas Instruments
SP5Standard & Poor's 500 index
m.cpice16.dp7503 a zoo object of 168 monthly on two macroeconomic variables from January 1975 through December 2002 (p. 412):
CPI consumer price index for all urban consumers: all items and with index 1982-1984 = 100
CE16 Civilian employment numbers 16 years and over: measured in thousands
m.barra.9003 a zoo object giving monthly excess returns of ten stocks from January 1990 through December 2003:
AGEA. G. Edwards
CCitigroup
MWDMorgan Stanley
MERMerrill Lynch
DELLDell, Inc.
IBMInternational Business Machines
AAAlcoa
CATCaterpillar
PGProctor & Gamble
m.5cln a zoo object giving monthly log returns in percentages of 5 stocks from January 1990 through December 1999:
IBMInternational Business Machines
HPQHewlett-Packard
INTCIntel
MERMerrill Lynch
MWDMorgan Stanley Dean Witter
m.apca0103 data.frame of monthly simple returns of 40 stocks from January 2001 through December 2003, discussed in sect. 9.6.2, pp. 437ff.
CompanyID5-digit company identification code
datethe last workday of the month
returnin percent
http://faculty.chicagobooth.edu/ruey.tsay/teaching/fts2
Ruey Tsay (2005) Analysis of Financial Time Series, 2nd ed. (Wiley, ch. 7)
ch01data
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ch02data
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ch03data
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ch04data
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ch05data
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ch06data
data(m.apca0103) dim(m.apca0103) # 1440 3; 1440 = 40*36 # Are the dates all the same? sameDates <- rep(NA, 39) for(i in 1:39) sameDates[i] <- with(m.apca0103, all.equal(date[1:36], date[(i*36)+1:36])) stopifnot(all(sameDates)) M.apca0103 <- with(m.apca0103, array(return, dim = c(36, 40), dimnames = list(NULL, paste("Co", CompanyID[seq(1, 1440, 36)], sep=""))))