fBasics data sets — fBasicsData • fBasics

The following data sets are part of this package:

`Capitalization`	Market capitalization of domestic companies,
`cars2`	Data for various car models,
`DowJones30`	Down Jones 30 stocks,
`HedgeFund`	Hennessee Hedge Fund Indices,
`msft.dat`	Daily Microsoft OHLC prices and volume,
`nyse`	NYSE composite Index,
`PensionFund`	Swiss Pension Fund LPP-2005,
`swissEconomy`	Swiss Economic Data,
`SWXLP`	Swiss Pension Fund LPP-2000,
`usdthb`	Tick data of USD to THB.

Details

All datasets are data frames. A brief description is given below.

Capitalization:
Capitalization contains market capitalization of 13 domestic companies for 6 years (from 2003 to 2008) in USD millions. Each row contains the data for one company/stock exchange.

cars2:
cars2 contains columns rowNames (model), Price, Country, Reliability, Mileage, (Type), (Weight), Disp. (engine displacement) and HP (net horsepower) reprsenting the indicated properties of 60 car models.

DowJones30:
DowJones30 contains 2529 daily observations from the ‘Dow Jones 30’ Index series. The first row contains the dates (from 1990-12-31 to 2001-01-02). Each of the remaining thirty columns represents the closing price of a stock in the Index.

HedgeFund:
HedgeFund contains monthly percentage returns of 16 hedge fund strategies from Hennessee Group LLC for year 2005.

msft.dat:
msft.dat contains daily prices (open, high, low and close) and volumes for the Microsoft stocks. It is a data frame with column names "%Y-%m-%d", "Open", "High", "Low", "Close", "Volume".

Note: there is a dataset, MSFT, in package timeSeries which contains the same data but is of class "timeSeries".

nyse:
nyse contains daily records of the NYSE Composite Index from 1966-01-04 to 2002-12-31 (9311 observations). The data is in column "NYSE" (second column). The first column contains the dates.

PensionFund:
PensionFund is a daily data set of the Swiss pension fund benchmark LPP-2005. The data set ranges from 2005-11-01 to 2007-04-11. The columns are named: SBI, SPI, SII, LMI, MPI, ALT, LPP25, LPP40, LPP60.

swissEconomy:
swissEconomy contains the GDP per capita (GDPR), exports (EXPO), imports (IMPO), interest rates (INTR), inflation (INFL), unemployment (UNEM) and population (POPU) foryears 1964 to 1999 for Switzerland.

SWXLP:
SWXLP is a daily data set of the Swiss pension fund benchmark LPP-2000. The data set ranges from 2000-01-03 to 2007-05-08 (1917 observations). The first column contains the dates. The remaining columns are named: SBI, SPI, SII, LP25, LP40, LP60.

usdthb:
usdthb Tick data of US Dollar (USD) in Thailand Bhat (THB) collected from Reuters. The date is in the first column in YYYYMMDDhhmm format. The remaining columns contain: delay time (DELAY), contributor (CONTRIBUTOR), bid (BID) and ask (ASK) prices, and quality flag (FLAG). It covers the Asia FX crisis in June 1997.

References

Capitalization:
World Federation of Stock Exchanges, http://www.world-exchanges.org/statistics.

cars2:
Derived from the car90 dataset within the rpart package. The car90 dataset is based on the car.all dataset in S-PLUS. Original data comes from: April 1990, Consumer Reports Magazine, pages 235-255, 281-285 and 287-288.

DowJones30
https://www.yahoo.com.

HedgeFund:
http://www.hennesseegroup.com/indices/returns/year/2005.html.

msft.dat:
https://www.yahoo.com.

nyse:
https://www.nyse.com.

PensionFund:
SBI, SPI, SII: SIX (Swiss Exchange Zurich); LPP25, LPP40, LPP60: Banque Pictet Geneva; LMI, MPI, ALT: Recalculated from the indices and benchmarks.

swissEconomy:
https://www.oecd.org/ and https://www.imf.org/.

SWXLP:
SBI, SPI, SII: SIX (Swiss Exchange Zurich); LPP25, LPP40, LPP60: Banque Pictet Geneva.

usdthb:
Reuters Select Feed Terminal (1997).

Examples

## Plot DowJones30 Example Data Set
   series <- timeSeries::as.timeSeries(DowJones30)
   head(series)
#> GMT
#>              AA  AXP     T    BA  CAT    C   KO    DD    EK   XOM   GE    GM
#> 1990-12-31 5.92 4.70 14.67 21.77 9.30 1.87 9.88 13.15 23.02 12.09 4.63 19.72
#> 1991-01-02 5.92 4.70 14.67 21.77 9.30 1.87 9.88 13.15 23.02 12.09 4.63 19.72
#> 1991-01-03 5.88 4.73 14.73 21.71 9.15 1.87 9.60 12.83 22.95 12.15 4.53 19.57
#> 1991-01-04 5.76 4.73 14.79 22.50 9.00 1.92 9.85 13.06 22.74 12.27 4.47 19.00
#> 1991-01-07 5.72 4.58 14.67 21.65 8.87 1.89 9.69 12.83 22.11 12.12 4.40 18.35
#> 1991-01-08 5.63 4.53 14.73 21.34 9.05 1.85 9.60 12.60 22.18 12.09 4.44 18.28
#>             HWP   HD  HON INTC   IBM    IP  JPM  JNJ  MCD   MRK MSFT   MMM
#> 1990-12-31 3.91 2.80 5.70 1.20 27.86 20.45 2.67 7.31 7.08 11.83 2.08 31.41
#> 1991-01-02 3.91 2.80 5.70 1.20 27.86 20.45 2.67 7.31 7.08 11.83 2.08 31.41
#> 1991-01-03 3.91 2.74 5.67 1.20 27.95 20.21 2.67 7.23 6.99 11.45 2.09 30.90
#> 1991-01-04 3.85 2.75 5.65 1.20 27.86 20.50 2.69 7.18 7.02 11.27 2.11 30.80
#> 1991-01-07 3.88 2.65 5.50 1.19 27.39 20.45 2.58 6.96 6.80 10.97 2.08 30.43
#> 1991-01-08 3.90 2.59 5.47 1.18 27.08 20.26 2.58 7.02 6.83 11.01 2.04 29.65
#>               MO    PG  SBC  UTX  WMT  DIS
#> 1990-12-31 10.55 20.91 9.75 9.31 7.05 7.86
#> 1991-01-02 10.55 20.91 9.75 9.31 7.05 7.86
#> 1991-01-03 10.27 20.70 9.64 9.19 7.05 7.82
#> 1991-01-04 10.24 20.48 9.56 9.24 6.97 7.79
#> 1991-01-07 10.08 20.05 9.40 8.95 6.82 7.58
#> 1991-01-08 10.11 20.02 9.32 8.78 6.85 7.41
   plot(series[,1:6], type = "l")


## msft.dat contains (almost?) the same data as MSFT in package timeSeries
data(MSFT, package = "timeSeries")

m1 <- as.matrix(msft.dat[, -1]) # drop date stamps in column 1
m2 <- as.matrix(MSFT)
all.equal(m1, m2, check.attributes = FALSE) # TRUE
#> [1] TRUE
## compare the dates:
all.equal(format(msft.dat[ , 1]), format(time(MSFT))) # TRUE
#> [1] TRUE