# This library is free software; you can redistribute it and/or # modify it under the terms of the GNU Library General Public # License as published by the Free Software Foundation; either # version 2 of the License, or (at your option) any later version. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Library General Public License for more details. # # You should have received a copy of the GNU Library General # Public License along with this library; if not, write to the # Free Foundation, Inc., 59 Temple Place, Suite 330, Boston, # MA 02111-1307 USA # Copyrights (C) # for this R-port: # 1999 - 2006, Diethelm Wuertz, GPL # Diethelm Wuertz # info@rmetrics.org # www.rmetrics.org # for the code accessed (or partly included) from other R-ports: # see R's copyright and license files # for the code accessed (or partly included) from contributed R-ports # and other sources # see Rmetrics's copyright file ################################################################################ # FUNCTION: DESCRIPTION: # acfPlot Displays autocorrelations function plot # pacfPlot Displays partial autocorrelation function plot # teffectPlot Estimates and plots the Taylor effect # lmacfPlot Estimates and plots the long memory ACF # lacfPlot Plots lagged autocorrelations # logpdfPlot Returns a pdf plot on logarithmic scale(s) # qqgaussPlot Returns a Gaussian quantile-quantile plot # scalinglawPlot Evaluates and plots scaling law behavior ################################################################################ test.acfPlot = function() { # MSFT Data: msft.dat = as.timeSeries(data(msft.dat)) msft = msft.dat[, 1] msft.vol = msft.dat[ , 5]/10^6 msft.ret = returnSeries(msft) # Graph Frame: par(mfrow = c(1, 1)) # acfPlot - acfPlot(x = msft.ret) # acfPlot - acfPlot(x = msft.ret, labels = FALSE) # Return Value: return() } # ------------------------------------------------------------------------------ test.pacfPlot = function() { # MSFT Data: msft.dat = as.timeSeries(data(msft.dat)) msft = msft.dat[, 1] msft.vol = msft.dat[ , 5]/10^6 msft.ret = returnSeries(msft) # Graph Frame: par(mfrow = c(1, 1)) # pacfPlot - pacfPlot(x = msft.ret) # pacfPlot - pacfPlot(x = msft.ret, labels = FALSE) # Return Value: return() } # ------------------------------------------------------------------------------ test.teffectPlot = function() { # MSFT Data: msft.dat = as.timeSeries(data(msft.dat)) msft = msft.dat[, 1] msft.vol = msft.dat[ , 5]/10^6 msft.ret = returnSeries(msft) # Graph Frame: par(mfrow = c(1, 1)) # teffectPlot - teffectPlot(x = msft.ret) # teffectPlot - teffectPlot(x = msft.ret, labels = FALSE) # Return Value: return() } # ------------------------------------------------------------------------------ test.lmacfPlot = function() { # MSFT Data: msft.dat = as.timeSeries(data(msft.dat)) msft = msft.dat[, 1] msft.vol = msft.dat[ , 5]/10^6 msft.ret = returnSeries(msft) # Graph Frame: par(mfrow = c(1, 1)) # lmacfPlot - ## lmacfPlot(x = abs(msft.ret), type = "acf") ## lmacfPlot(x = abs(msft.ret), type = "hurst") # ... CHECK ACF OF RETURNS # lmacfPlot - ## lacfPlot(x = msft, n = 4, type = "values") ## CHECK !!! # lmacfPlot - ## lmacfPlot(x = abs(msft.ret), type = "acf", labels = FALSE) ## lmacfPlot(x = abs(msft.ret), type = "hurst", labels = FALSE) # ... CHECK ACF OF RETURNS # lmacfPlot - ## lacfPlot(x = msft, n = 4, labels = FALSE, type = "values") ## CHECK !!! # Return Value: return() } # ------------------------------------------------------------------------------ test.lacfPlot = function() { # MSFT Data: msft.dat = as.timeSeries(data(msft.dat)) msft = msft.dat[, 1] msft.vol = msft.dat[ , 5]/10^6 msft.ret = returnSeries(msft) # Graph Frame: par(mfrow = c(1, 1)) # Return Value: return() } # ------------------------------------------------------------------------------ test.logpdfPlot = function() { # MSFT Data: msft.dat = as.timeSeries(data(msft.dat)) msft = msft.dat[, 1] msft.vol = msft.dat[ , 5]/10^6 msft.ret = returnSeries(msft) # Graph Frame: par(mfrow = c(1, 1)) # logpdfPlot - logpdfPlot(x = msft.ret, labels = FALSE) logpdfPlot(x = msft.ret, type = "log-log") # ... CHECK WARNINGS # ... CHECK COLORS # logpdfPlot - logpdfPlot(x = msft.ret, labels = FALSE) logpdfPlot(x = msft.ret, type = "log-log", labels = FALSE) # ... CHECK WARNINGS # ... CHECK COLORS # Return Value: return() } # ------------------------------------------------------------------------------ test.qqgausPlot = function() { # MSFT Data: msft.dat = as.timeSeries(data(msft.dat)) msft = msft.dat[, 1] msft.vol = msft.dat[ , 5]/10^6 msft.ret = returnSeries(msft) # Graph Frame: par(mfrow = c(1, 1)) # qqgaussPlot - qqgaussPlot(x = msft.ret) # qqgaussPlot - qqgaussPlot(x = msft.ret, labels = FALSE) # Return Value: return() } # ------------------------------------------------------------------------------ test.scalinglawPlot = function() { # MSFT Data: msft.dat = as.timeSeries(data(msft.dat)) msft = msft.dat[, 1] msft.vol = msft.dat[ , 5]/10^6 msft.ret = returnSeries(msft) # Graph Frame: par(mfrow = c(1, 1)) # scalinglawPlot - scalinglawPlot(x = msft.ret, span = 4) # ... CHECK COLORS # scalinglawPlot - scalinglawPlot(x = msft.ret, span = 4, labels = FALSE) # ... CHECK COLORS # Return Value: return() } ################################################################################