Chapter 1. Financial Markets, Prices and Risk (in R/MATLAB)


Copyright 2011 - 2019 Jon Danielsson. This code is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This code 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 General Public License for more details. The GNU General Public License is available at: https://www.gnu.org/licenses/.


Listing 1.1/1.2: Download S&P500 data in R
Last updated August 2019

price = read.csv('index.csv')
y=diff(log(price$Index))      # calculate returns
plot(y)                       # plot returns
		
Listing 1.1/1.2: Download S&P 500 data in MATLAB
Last updated August 2016

price = csvread('index.csv', 1, 0);
y=diff(log(price));                 % calculate returns
plot(y)                             % plot returns
		

Listing 1.3/1.4: Sample statistics in R
Last updated August 2019

library(moments)
library(tseries)
mean(y)
sd(y)
min(y)
max(y)
skewness(y)
kurtosis(y)
acf(y,1)
acf(y^2,1)
jarque.bera.test(y)
Box.test(y, lag = 20, type = c("Ljung-Box"))
Box.test(y^2, lag = 20, type = c("Ljung-Box"))
		
Listing 1.3/1.4: Sample statistics in MATLAB
Last updated June 2018

%% the function sacf uses Kevin Sheppard's MFE toolbox
%% download at https://www.kevinsheppard.com/MFE_Toolbox
mean(y)
std(y)
min(y)
max(y)
skewness(y)
kurtosis(y)
sacf(y,1,[],0)
sacf(y.^2,1,[],0)
[h,pValue,stat]=jbtest(y);
[h,pValue,stat]=lbqtest(y,'lags',20);
[h,pValue,stat]=lbqtest(y.^2,'lags',20);
%% NOTE: in MATLAB 2018a, some functions require name-value pairs
%% e.g. MATLAB 2016a: [h,pValue,stat] = lbqtest(y,20)
		

Listing 1.5/1.6: ACF plots and the Ljung-Box test in R
Last updated August 2019

library(MASS)
library(stats)
par(mfrow=c(1,2), pty="s")
q = acf(y,20)
q1 = acf(y^2,20)
		
Listing 1.5/1.6: ACF plots and the Ljung-Box test in MATLAB
Last updated August 2016

%% subplots here are just for ease of visualization
subplot(1,2,1)
autocorr(y, 20)
subplot(1,2,2)
autocorr(y.^2, 20)
		

Listing 1.7/1.8: QQ plots in R
Last updated June 2018

library(car)
par(mfrow=c(1,2), pty="s")
qqPlot(y)
qqPlot(y,distribution="t",df=5)
		
Listing 1.7/1.8: QQ plots in MATLAB
Last updated 2011

%% subplots here are just for ease of visualization
subplot(1,2,1)
qqplot(y)
subplot(1,2,2)
qqplot(y, fitdist(y,'tLocationScale'))
		

Listing 1.9/1.10: Download stock prices in R
Last updated June 2018

p = read.csv('stocks.csv')
y=apply(log(p),2,diff)
print(cor(y))              # correlation matrix
		
Listing 1.9/1.10: Download stock prices in MATLAB
Last updated 2011

price = csvread('stocks.csv', 1, 0);
y=diff(log(price));
corr(y)                              % correlation matrix