mathEfrontCashRisky: mathEfrontCashRisky
In kecoli/mpo: Companion to Modern Portfolio Optimization with R, 2nd Edition

Usage Arguments Examples

mathEfrontCashRisky(returns, rf = 0.005, scalex = 1.2, scaley = 2, display.stocks = T, stock.names = T, risk.tol = F, npoints = 10, plot.efront = T, wts.plot = T, equal.wts = T, bar.ylim = c(0, 1), digits = NULL)

`returns`
`rf`
`scalex`
`scaley`
`display.stocks`
`stock.names`
`risk.tol`
`npoints`
`plot.efront`
`wts.plot`
`equal.wts`
`bar.ylim`
`digits`

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (returns, rf = 0.005, scalex = 1.2, scaley = 2, display.stocks = T, 
    stock.names = T, risk.tol = F, npoints = 10, plot.efront = T, 
    wts.plot = T, equal.wts = T, bar.ylim = c(0, 1), digits = NULL) 
{
    V = var(returns)
    mu.stocks = apply(returns, 2, mean)
    sigma.stocks = apply(returns, 2, sd)
    mue = mu.stocks - rf
    a = solve(V, mue)
    b = as.numeric(t(mue) %*% a)
    sr.opt = sqrt(as.numeric(b))
    bsr = sqrt(b)
    mu.max = scaley * max(mu.stocks)
    muvals = seq(0, mu.max, length.out = npoints)
    sigmavals = c(muvals/bsr)
    muvalse = seq(0, mu.max, length.out = npoints)
    muvals = rf + muvalse
    inv.lambdavals = (muvals - rf)/b
    if (plot.efront) {
        if (wts.plot) {
            par(mfrow = c(1, 2))
        }
        if (risk.tol) {
            x = inv.lambdavals
            y = muvals
            xlab = "Risk Tolerance"
            par(mfrow = c(1, 1))
        }
        else {
            x = sigmavals
            y = muvals
            xlab = "Portfolio Standard Deviation"
        }
        xlim = c(0, scalex * max(sigma.stocks, x))
        ylim = c(min(mu.stocks), max(muvals))
        plot(x, y, type = "l", xaxs = "i", lwd = 2, xlim = xlim, 
            ylim = ylim, xlab = xlab, ylab = "Portfolio Mean Return")
        if (risk.tol) {
            display.stocks = F
            stock.names = F
        }
        if (display.stocks) {
            points(sigma.stocks, mu.stocks, pch = 20)
            if (stock.names) {
                text(sigma.stocks + 0.02 * xlim[2], mu.stocks, 
                  names(returns), cex = 0.5, adj = 0)
            }
        }
        x <- xlim[1] + 0.05 * (xlim[2] - xlim[1])
        y <- ylim[2] - 0.02 * (ylim[2] - ylim[1])
        text(x, y, paste("Rf = ", round(rf, 3), sep = ""), pos = 4)
        y = y - 0.05 * (ylim[2] - ylim[1])
        text(x, y, paste("SR = ", round(sr.opt, 2), sep = ""), 
            pos = 4)
        if (equal.wts) {
            n = length(mu.stocks)
            wts = rep(1/n, n)
            mu.eq = mean(mu.stocks)
            sigma.eq = as.numeric((t(wts) %*% V %*% wts)^0.5)
            sr.eq = mu.eq/sigma.eq
            points(sigma.eq, mu.eq, pch = 15, cex = 1.2)
            text(sigma.eq, mu.eq, "EQ.WTS", pos = 4, cex = 0.7)
        }
    }
    wts.risky = (sum(a)/b) * muvalse
    wts.cash = 1 - wts.risky
    wts.efront = rbind(wts.cash, wts.risky)
    row.names(wts.efront) = c("Cash", "Risky Assets")
    if (wts.plot) {
        barplot.wts(wts.efront, legend.text = T, col = topo.colors(2), 
            ylab = "Weights", xlab = xlab, bar.ylim = bar.ylim)
        par(mfrow = c(1, 1))
    }
    if (is.null(digits)) {
        if (!risk.tol) {
            wts.efront
        }
    }
    else {
        if (equal.wts) {
            out = list(MU.EQ.WT = mu.eq, STDEV.EQ.WT = sigma.eq, 
                SR.EQ.WT = sr.eq, SR.EFRONT = sr.opt)
            out = lapply(out, round, digits = digits)
        }
        else {
            out = list(SR.EFRONT = sr.opt)
            out = lapply(out, round, digits = digits)
        }
        out
    }
  }