ch01data: Financial time series for Tsay (2005, ch. 1)

ch01dataR Documentation

Financial time series for Tsay (2005, ch. 1)

Description

Financial time series used in examples in chapter 1.

Usage

data(d.ibmvwewsp6203)
data(d.intc7303)
data(d.3m6203)
data(d.msft8603)
data(d.c8603)
data(m.ibmvwewsp2603)
data(m.intc7303)
data(m.3m4603)
data(m.msft8603)
data(m.c8603)
data(m.gs10)
data(m.gs1)
data(d.fxjp00)
data(m.fama.bond5203)
data(m.gs3)
data(m.gs5)
data(w.tb3ms)
data(w.tb6ms)

Format

Objects of class zoo giving simple returns for each trading period (day, week or month) for different periods, with different start dates but typically running to the end of 2003.

d.ibmvwewsp6203, m.ibmvwewsp2603

Zoo objects with 4 columns (IBM, VW, EW, and SP). Daily data starts with 1962-07-03. Monthly data starts with 1926-01-30.

d.intc7303, m.intc7303

Matrices of class zoo with a single column "Intel" starting from January 1973.

d.3m6203, m.3m6203

Matrices of class zoo with a single column "MMM". Daily data starts with 1962-07-03. Monthly data starts with 1946-02-28.

d.msft8603, m.msft8603

Matrices of class zoo with a single column "MSFT" starting from 1906-03-14.

d.c8603, m.c8603

Matrix of class zoo with a single column "C" starting from 1986-10-30.

m.gs10, m.gs1

Monthly 10-yr and 1-yr Treasury constant maturity rates (4/53-3/04)

d.fxjp00

Daily exchange rate between U.S. dollar and Japanese yen

m.fama.bond5203

Monthly bond returns as follows:

m1.12

1-12m

m24.36

24-36m

m48.60

48-60m

m61.120

61-120m

m.gs3, m.gs5

Monthly 3-yr and 5-yr Treasury constant maturity rates

w.tb3ms, w.tb6ms

Weekly Treasury Bill rates

Details

The first 16 of these objects contain daily and monthly simple returns for 8 financial time series analyzed Tsay (2005, Table1.2). These 8 are SP (Standard & Poors), EW, IBM, Intel, Microsoft, and Citi-Group, beginning at different times and running to the end of 2003.

The others are used elsewhere in chapter 1.

Source

https://faculty.chicagobooth.edu/ruey-s-tsay/teaching

References

Ruey Tsay (2005) Analysis of Financial Time Series, 2nd ed. (Wiley, ch. 1)

See Also

FinTS.stats

Examples

# First half of Table 1.2:
data(d.ibmvwewsp6203)
data(d.intc7303)
data(d.3m6203)
data(d.msft8603)
data(d.c8603)
(Daily.Simple.Returns.pct <- rbind(
    SP = FinTS.stats(100*d.ibmvwewsp6203[, "SP"]),
    VW = FinTS.stats(100*d.ibmvwewsp6203[, "VW"]),
    EW = FinTS.stats(100*d.ibmvwewsp6203[, "EW"]),
    IBM= FinTS.stats(100*d.ibmvwewsp6203[, "IBM"]),
    Intel=FinTS.stats(100*d.intc7303[, "Intel"]),
    MMM= FinTS.stats(100*d.3m6203[, "MMM"]),
    MSFT=FinTS.stats(100*d.msft8603[, 'MSFT']),
    C  = FinTS.stats(100*d.c8603[, "C"])
) )

(Daily.log.Returns.pct <- rbind(
    SP = FinTS.stats(100*log(1+d.ibmvwewsp6203[, "SP"])),
    VW = FinTS.stats(100*log(1+d.ibmvwewsp6203[, "VW"])),
    EW = FinTS.stats(100*log(1+d.ibmvwewsp6203[, "EW"])),
    IBM= FinTS.stats(100*log(1+d.ibmvwewsp6203[, "IBM"])),
    Intel=FinTS.stats(100*log(1+d.intc7303[,"Intel"])),
    MMM= FinTS.stats(100*log(1+d.3m6203[, "MMM"])),
    MSFT=FinTS.stats(100*log(1+d.msft8603[, 'MSFT'])),
    C  = FinTS.stats(100*log(1+d.c8603[, "C"]))
) )

FinTS documentation built on May 29, 2024, 4:24 a.m.

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