%% Lecture 10th Oct


% Load the Data
load Totasset
aggregate = US_Business_TotalAssets;
corpBusiness = US_corpBusiness_TotalAssets;
noncorpBusiness = US_NoncorpBusiness_TotalAssets;
%Lets compute the logarithmic first diff, mean and standard deviation
aggreggrowthrate = diff(log(aggregate));
mu = mean(aggregate);
sigma = std(aggregate);

corpassetgrowthrate = diff(log(corpBusiness));
mu2 = mean(corpassetgrowthrate);
sigma2 = std(corpassetgrowthrate);

noncorpassetgrowthrate = diff(log(noncorpBusiness));
mu3 = mean(noncorpassetgrowthrate);
sigma3 = std(noncorpassetgrowthrate);


%% Plot the data

figure
plot(aggreggrowthrate)

figure
plot(corpassetgrowthrate)

figure
plot(noncorpBusiness)


%% Datetime function


%Create a 3-by-1 column vector named d of type datetime as shown below.

% 01-Feb-1999
% 01-Feb-2000
% 01-Feb-2001

d= datetime([1999;2000;2011],2,1)


% adjust date format
% Create a datetime d representing the date January 11th 1989 using the format yyyy-MMM-dd.

d = datetime(1989, 1, 11, 'Format', 'yyyy-MMM-dd')





% Creat Duration variables
% The three inputs represent, in order, the number of hours, minutes, and seconds.

t = duration(12,0,2)



% Create a duration t representing 1 hour, 23 minutes and 16 seconds.

t = duration(1, 23, 16)


% Creat Calendar Duration variables
% Create a calendar duration t representing 6 calendar months.

t = calendarDuration(0, 6, 0)


%% Use datetime to plot time series

% time space
startdate = datenum('Q1-2000','QQ-yyyy');%startdate = datenum('04-1997','mm-yyyy');
enddate = datenum('Q2-2018','QQ-yyyy');%startdate = datenum('04-1997','mm-yyyy'); 
dt = linspace(startdate,enddate,74);
% convert
dtDates = datetime(dt,'ConvertFrom', 'datenum');
% plot
figure('color','w')
plot(dtDates,US_corpBusiness_TotalAssets,'Color', 'r');hold on
plot(dtDates,US_NoncorpBusiness_TotalAssets,'Color','b');hold on
title('US Businesses Total Assets','FontSize',10);
legend({'Corp Businesses', 'NonCorp Businesses'},'FontSize',10,'Location','best')
hold off




%% Datafeed Basics

% 
url = 'https://fred.stlouisfed.org/';
c = fred(url);


%  The data series required : Real Gross Domestic Product (GDPC1)	
% the start and end dates (specified as datetime variables).
startdate = datenum('Q1-2004','QQ-yyyy');%startdate = datenum('04-1997','mm-yyyy');
enddate = datenum('Q2-2018','QQ-yyyy')
d = fetch(c,'GDPC1',startdate,enddate)

% time space 
dt = linspace(startdate,enddate,58);
% convert 
dtDates = datetime(dt,'ConvertFrom', 'datenum');
% plot real GDP
figure('color','w')
plot(dtDates,d.Data(:,end),'Color', 'r');hold on % you can also extract the data with d.Data(:,2)
title('US Real GDP','FontSize',10);
hold off


%% how to merge two dataset
 
x1Data =[736390      16865;
    736391      16899;
    736392      16944;
    736393      17007;
    736396      17074]


z1Data =[ 736391      16747;
    736392      16960;
    736393      17015;
    736396      16911;
    736397      16783;
    736398      16642]



% CONVERT
x1Dates = datetime(x1Data(:, 1), ...
                'ConvertFrom', 'datenum');
            
z1Dates = datetime(z1Data(:, 1), ...
                'ConvertFrom', 'datenum');
% USE intersect function            
[commonDates, idxx1, idxz1] =     intersect(x1Dates, z1Dates);

% extract 
commonx1 = x1Data(idxx1, 2);
commonz1 = z1Data(idxz1, 2);
% check the size 
size(commonx1)            
size(commonz1)
% Merge
commonData = [commonx1, commonz1];