⼏何布朗运动模拟MATLAB实现
time = data.date;%抽取年份
clo = data.clo;%抽取收盘价
pos = time.Year ==2019;%选择2019年打标签
clo_2019 = clo(pos);%选择2019年收盘价
[ret,vol]= RetVolCaculation(data);
simup = MCSimulation(ret,vol,time,clo);
resultplot(clo_2019,simup);
function [ret,vol]= RetVolCaculation(data)
ret = zeros(14,1);
vol = zeros(14,1);
time_2005 = table2array(
('2005-01-04','2005-12-30'),'clo'));
time_2006 = table2array(
('2006-01-04','2006-12-29'),'clo'));
time_2007 = table2array(
('2007-01-04','2007-12-28'),'clo'));
time_2008 = table2array(
('2008-01-04','2008-12-29'),'clo'));
time_2009 = table2array(
('2009-01-05','2009-12-11'),'clo'));
time_2010 = table2array(
('2010-01-04','2010-12-30'),'clo'));
time_2011 = table2array(
('2011-01-04','2011-12-30'),'clo'));
time_2012 = table2array(
('2012-01-04','2012-12-28'),'clo'));
time_2013 = table2array(
('2013-01-04','2013-12-30'),'clo'));
time_2014 = table2array(
('2014-01-02','2014-12-30'),'clo'));
time_2015 = table2array(
('2015-01-05','2015-12-30'),'clo'));
time_2016 = table2array(
('2016-01-05','2016-12-29'),'clo'));
time_2017 = table2array(
('2017-01-03','2017-12-29'),'clo'));
time_2018 = table2array(
('2018-01-02','2018-12-28'),'clo'));
ret(1)= log(table2array(data({'2005-01-04'},'clo')))...
- log(table2array(data({'2005-12-30'},'clo')));
ret(2)= log(table2array(data({'2006-01-04'},'clo')))...
- log(table2array(data({'2006-12-29'},'clo')));
ret(3)= log(table2array(data({'2007-01-04'},'clo')))...
-
log(table2array(data({'2007-12-28'},'clo')));
ret(4)= log(table2array(data({'2008-01-04'},'clo')))...
- log(table2array(data({'2008-12-29'},'clo')));
ret(5)=log(table2array(data({'2009-01-05'},'clo')))...
- log(table2array(data({'2009-12-11'},'clo')));
ret(6)= log(table2array(data({'2010-01-04'},'clo')))...
- log(table2array(data({'2010-12-30'},'clo')));
平准书
ret(7)= log(table2array(data({'2011-01-04'},'clo')))...
雪山林- log(table2array(data({'2011-12-30'},'clo')));
ret(8)= log(table2array(data({'2012-01-04'},'clo')))...
- log(table2array(data({'2012-12-28'},'clo')));
ret(9)= log(table2array(data({'2013-01-04'},'clo')))...
- log(table2array(data({'2013-12-30'},'clo')));
ret(10)= log(table2array(data({'2014-01-02'},'clo')))...
- log(table2array(data({'2014-12-30'},'clo')));
ret(11)= log(table2array(data({'2015-01-05'},'clo')))...
- log(table2array(data({'2015-12-30'},'clo')));
ret(12)= log(table2array(data({'2016-01-05'},'clo')))...
- log(table2array(data({'2016-12-29'},'clo')));
ret(13)= log(table2array(data({'2017-01-03'},'clo')))...
- log(table2array(data({'2017-12-29'},'clo')));
ret(14)= log(table2array(data({'2018-01-02'},'clo')))...
-
log(table2array(data({'2018-12-28'},'clo')));
m = length(time_2005);
vol(1)=0;
辛苦英语for i =1:m-1
vol(1)= vol(1)+(log(time_2005(i+1))- log(time_2005(i)))^2; end
vol(1)= sqrt(vol(1));
m = length(time_2006);
vol(2)=0;
for i =1:m-1
vol(2)= vol(2)+(log(time_2006(i+1))- log(time_2006(i)))^2; end
vol(2)= sqrt(vol(2));
m = length(time_2007);
vol(3)=0;
for i =1:m-1
vol(3)= vol(3)+(log(time_2007(i+1))- log(time_2007(i)))^2; end
vol(3)= sqrt(vol(3));
m = length(time_2008);
vol(4)=0;
for i =1:m-1
vol(4)= vol(4)+(log(time_2008(i+1))- log(time_2008(i)))^2; end
vol(4)= sqrt(vol(4));
m = length(time_2009);
vol(5)=0;
for i =1:m-1
vol(5)= vol(5)+(log(time_2009(i+1))- log(time_2009(i)))^2; end
vol(5)= sqrt(vol(5));
m = length(time_2010);
vol(6)=0;英语电影台词
for i =1:m-1
vol(6)= vol(6)+(log(time_2010(i+1))- log(time_2010(i)))^2; end
vol(6)= sqrt(vol(6));
m = length(time_2011);
vol(7)=0;
for i =1:m-1
vol(7)=vol(7)+(log(time_2011(i+1))- log(time_2011(i)))^2; end
vol(7)= sqrt(vol(7));
m = length(time_2012);
vol(8)=0;
for i =1:m-1
vol(8)= vol(8)+(log(time_2012(i+1))- log(time_2012(i)))^2; end
vol(8)= sqrt(vol(8));
vol(8)= sqrt(vol(8));
m = length(time_2013);
vol(9)=0;
for i =1:m-1
vol(9)= vol(9)+(log(time_2013(i+1))- log(time_2013(i)))^2;
end
vol(9)= sqrt(vol(9));
m = length(time_2014);
vol(10)=0;
for i =1:m-1
vol(10)= vol(10)+(log(time_2014(i+1))- log(time_2014(i)))^2;
end
vol(10)= sqrt(vol(10));两个巡逻兵
m = length(time_2015);
vol(11)=0;
for i =1:m-1
vol(11)= vol(11)+(log(time_2015(i+1))- log(time_2015(i)))^2;
end
vol(11)= sqrt(vol(11));
m = length(time_2016);
vol(12)=0;
for i =1:m-1
vol(12)= vol(12)+(log(time_2016(i+1))- log(time_2016(i)))^2;
end
vol(12)= sqrt(vol(12));
高抗冲聚苯乙烯
m = length(time_2017);
vol(13)=0;
for i =1:m-1
vol(13)= vol(13)+(log(time_2017(i+1))- log(time_2017(i)))^2;
end
vol(13)= sqrt(vol(13));
m = length(time_2018);
vol(14)=0;
for i =1:m-1
vol(14)= vol(14)+(log(time_2018(i+1))- log(time_2018(i)))^2;
最好的夏天end
vol(14)= sqrt(vol(14));
fprintf('2005, Yearly Return: %f, Yearly Volatility: %f \n',ret(1),vol(1)); fprintf('2006, Yearly Return: %f, Yearly Volatility: %f \n',ret(2),vol(2)); fprintf('2007, Yearly Return: %f, Yearly Volatility: %f \n',ret(3),vol(3)); fprintf('2008, Yearly Return: %f, Yearly Volatility: %f \n',ret(4),vol(4)); fprintf('2009, Yearly Return: %f, Yearly Volatility: %f \n',ret(5),vol(5)); fprintf('2010, Yearly Return: %f, Yearly Volatility: %f \n',ret(6),vol(6)); fprintf('2011, Yearly Return: %f, Yearly Volatility: %f \n',ret(7),vol(7)); fprintf('2012, Yearly Return: %f, Yearly Volatility: %f \n',ret(8),vol(8)); fprintf('2013, Yearly Return: %f, Yearly Volatility: %f \n',ret(9),vol(9)); fprintf('2014, Yearly Return: %f, Yearly Volatility: %f \n',ret(10),vol(10)); fprintf('2015, Yearly Return: %f, Yearly Volatility: %f \n',ret(11),vol(11)); fprintf('2016, Yearly Return: %f, Yearly Volatility: %f \n',ret(12),vol(12)); fprintf('2017, Yearly Return: %f, Yearly Volatility: %f \n',ret(13),vol(13)); fprintf('2018, Yearly Return: %f, Yearly Volatility: %f \n',ret(14),vol(14));
function [simup]= MCSimulation(ret,vol,time,clo)
mu = ret(10);
theta = vol(10);
教师制服
pos = time.Year ==2019;
n = length(pos(pos ==1));
clo_2019 = clo(pos);
simup = zeros(length(clo_2019),5);
simup(1,:)= clo_2019(1);
for iter=1:5
day =1;
for i =0:0.5/118:1
day = day+1;
eps = normrnd(0,1);
simup(day,iter)= exp(log(simup((day-1),iter))+(mu - theta^2/2)*(0.5/118)...
+ theta * eps * sqrt(0.5/118));
end
end
function resultplot(clo_2019,simup)
m = length(clo_2019);
plot(clo_2019,'black');
hold on
plot(simup(1:m,:));
