R: Gold and Silver Prices

GoldSilver {AER} | R Documentation

## Gold and Silver Prices

### Description

Time series of gold and silver prices.

### Usage

    data("GoldSilver")

### Format

A daily multiple time series from 1977-12-30 to 2012-12-31 (of class `"zoo"` with `"Date"` index).

gold

  spot price for gold,

silver

  spot price for silver.

### Source

Online complements to Franses, van Dijk and Opschoor (2014).

http://www.cambridge.org/us/academic/subjects/economics/econometrics-statistics-and-mathematical-economics/time-series-models-business-and-economic-forecasting-2nd-edition

### References

Franses, P.H., van Dijk, D. and Opschoor, A. (2014). Time Series Models for Business and Economic Forecasting, 2nd ed. Cambridge, UK: Cambridge University Press.

### Examples

    data("GoldSilver", package = "AER")

    ## p.31, daily returns
    lgs <- log(GoldSilver)
    plot(lgs[, c("silver", "gold")])

    dlgs <- 100 * diff(lgs)
    plot(dlgs[, c("silver", "gold")])

    ## p.31, monthly log prices
    lgs7812 <- window(lgs, start = as.Date("1978-01-01"))
    lgs7812m <- aggregate(lgs7812, as.Date(as.yearmon(time(lgs7812))), mean)
    plot(lgs7812m, plot.type = "single", lty = 1:2, lwd = 2)

    ## p.93, empirical ACF of absolute daily gold returns, 1978-01-01 - 2012-12-31
    absgret <- abs(100 * diff(lgs7812[, "gold"]))
    sacf <- acf(absgret, lag.max = 200, na.action = na.exclude, plot = FALSE)
    plot(1:201, sacf$acf, ylim = c(0.04, 0.28), type = "l", xaxs = "i", yaxs = "i", las = 1)

    ## ARFIMA(0,1,1) model, eq. (4.44)
    library("longmemo")
    WhittleEst(absgret, model = "fARIMA", p = 0, q = 1, start = list(H = 0.3, MA = .25))

    library("forecast")
    arfima(as.vector(absgret), max.p = 0, max.q = 1)

    ## p.254: VAR(2), monthly data for 1986.1 - 2012.12
    library("vars")

    lgs8612 <- window(lgs, start = as.Date("1986-01-01"))
    dim(lgs8612)

    lgs8612m <- aggregate(lgs8612, as.Date(as.yearmon(time(lgs8612))), mean)
    plot(lgs8612m)
    dim(lgs8612m)

    VARselect(lgs8612m, 5)
    gs2 <- VAR(lgs8612m, 2)

    summary(gs2)
    summary(gs2)$covres

    ## ACF of residuals, p.256
    acf(resid(gs2), 2, plot = FALSE)

    ## Figure 9.1, p.260 (somewhat different)
    plot(irf(gs2, impulse = "gold", n.ahead = 50), ylim = c(-0.02, 0.1))
    plot(irf(gs2, impulse = "silver", n.ahead = 50), ylim = c(-0.02, 0.1))

    ## Table 9.2, p.261
    fevd(gs2)

    ## p.266
    ls <- lgs8612[, "silver"]
    lg <- lgs8612[, "gold"]

    gsreg <- lm(lg ~ ls)
    summary(gsreg)
    sgreg <- lm(ls ~ lg)
    summary(sgreg)

    library("tseries")
    adf.test(resid(gsreg), k = 0)
    adf.test(resid(sgreg), k = 0)

[Package AER version 1.2-5 Index]