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

Copyright 2011 - 2022 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

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 July 2020

y=diff(log(price)); % calculate returns
plot(y)    % plot returns
title("S&P500 returns")


##### Listing 1.3/1.4: Sample statistics in R Last updated July 2020

library(moments)
library(tseries)
mean(y)
sd(y)
min(y)
max(y)
skewness(y)
kurtosis(y)
jarque.bera.test(y)

##### Listing 1.3/1.4: Sample statistics in MATLAB Last updated July 2020

mean(y)
std(y)
min(y)
max(y)
skewness(y)
kurtosis(y)
[h,pValue,stat]=jbtest(y);
%% NOTE: in MATLAB some functions require name-value pairs
%% e.g. [h,pValue,stat]=jbtest(y);


##### Listing 1.5/1.6: ACF plots and the Ljung-Box test in R Last updated July 2020

library(MASS)
library(stats)
par(mfrow=c(1,2), pty="s")
q = acf(y,20)
q1 = acf(y^2,20)
Box.test(y, lag = 20, type = c("Ljung-Box"))
Box.test(y^2, lag = 20, type = c("Ljung-Box"))

##### Listing 1.5/1.6: ACF plots and the Ljung-Box test in MATLAB Last updated July 2020

%% subplots here are just for ease of visualization
subplot(1,2,1)
autocorr(y, 20)
subplot(1,2,2)
autocorr(y.^2, 20)
[h,pValue,stat]=lbqtest(y,'lags',20);
[h,pValue,stat]=lbqtest(y.^2,'lags',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