fSeriesData {fSeries}R Documentation

fSeries Data Sets

Description

A collection of Data Sets used in the examples of the fSeries library.

recession
Data sets used in the regression analysis. Recession data from the US, 3 Month Tbills data from US FED, 10 Year Tbonds data from US FED, Stock-Watson experimental recession index.

spc1970 and spcindis
These data are indicators for daily SP500 Stock Data together with an set of trading indicators for technical analysis.

dem2gbp
The file "dem2gbp" contains daily observations of the Deutschmark / British Pound foreign exchange log returns. This data set has been promoted as an informal benchmark for GARCH time-series software validation. See McCullough and Renfro [1991], and Brooks, Burke, and Persand (2001) for details. The nominal returns are expressed in percent, as published in Bollerslev and Ghysels (2001). The data set is available from the Journal of Business and Economic Statistics, (JBES), ftp://www.amstat.org. A text file has one column of data listing the percentual log-returns of the DEM/GBP exchange rates. The sample period is from January 3, 1984, to December 31, 1991, for a total of 1975 daily observations of FX exchange rates.

cac40
Daily CAC40 index returns with realized volatility. The data cover the period January 1995 until December 1999, and have 1249 observations. The first column of the file CAC40 lists the averaged return of the Index, and the second column CAC40VOL lists the realized volatility. The data are used a s a benchmark for GARCH modeling by Laurent and Peters (2002).

Format

All files are in CSV Excel spreadsheet format.

References

Brooks C., Burke S.P, Persand G. (2001); Benchmarks and the Accuracy of GARCH Model Estimation, International Journal of Forecasting 17, 45–56.

McCullough B.D., Renfro C.G. (1998); Benchmarks and Software Standards: A Case Study of GARCH Procedures, Journal of Economic and Social Measurement 25, 59–71.

Laurent S., Peters J.P. (2002), G@RCH 2.2: An Ox Package for Estimating and Forecasting Various ARCH Models, Journal of Economic Surveys 16, 447–485.

Examples

## NYSE Residuals:
   data(nyseres)
   ts.plot(nyseres, xlab = "Index", ylab = "log-Returns",
         main = "NYSE: log-Returns")

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