correlation using specific values of the table

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Marlon
Marlon 2022-9-9
回答： Hiro Yoshino 2022-9-10
Hello, im trying to calculate the correlations of 3 different stocks and an index. I got the code up to here
clc
clear all
formatSpec = '%s %f %f %f %f';
temp_dat = readtable('Prices4.csv','Format',formatSpec,'ReadVariableNames',true);
% Extract pirices from table
price = table2array(temp_dat(:,2:end));
%Returns
rets = log(price(2:end,:)./price(1:end-1,:));
I want to Find the correlation matrix between the stocks on days when index returns are positive, and the correlation matrix when index returns are below the 10th percentile.
I dont know how to tell matlab to only take in to account those specifc values .
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Marlon
Marlon 2022-9-10
hey thanks for the answer, yes the first colum in the table are just dates, sorry to bother with further questions, i just started using matlab about three weeks ago, a timetable function? this is my tmpdata, is this the table i can directly use? or I need another timetable, will group summary will take the days for all the other 3 stocks?
Thank you very much for your help
Marlon
Marlon 2022-9-10
I have another table, with only the returns from each stock and the index

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Hiro Yoshino
Hiro Yoshino 2022-9-10
Ran in:
Here is my idea.
I reccomend you should use useful functions such as price2ret, corrplot (corr), prctile and the functionality of timetable as follows:
Sample data generation
t = datetime(2022,8,1:31,12,0,0)';
price = timetable(t,rand(31,1),rand(31,1))
price = 31×2 timetable
t Var1 Var2 ____________________ ________ ________ 01-Aug-2022 12:00:00 0.63836 0.63655 02-Aug-2022 12:00:00 0.21399 0.82862 03-Aug-2022 12:00:00 0.79756 0.015867 04-Aug-2022 12:00:00 0.33462 0.30921 05-Aug-2022 12:00:00 0.99808 0.028121 06-Aug-2022 12:00:00 0.93243 0.90636 07-Aug-2022 12:00:00 0.92369 0.54634 08-Aug-2022 12:00:00 0.77849 0.57087 09-Aug-2022 12:00:00 0.61343 0.77218 10-Aug-2022 12:00:00 0.98854 0.96529 11-Aug-2022 12:00:00 0.82305 0.43109 12-Aug-2022 12:00:00 0.24589 0.57595 13-Aug-2022 12:00:00 0.61277 0.49913 14-Aug-2022 12:00:00 0.25548 0.37036 15-Aug-2022 12:00:00 0.040045 0.59132 16-Aug-2022 12:00:00 0.62331 0.93248
Return calculation
tmp = price2ret(price);
price_to_return = tmp(:,["Var1","Var2"])
price_to_return = 30×2 timetable
Time Var1 Var2 ____________________ __________ ________ 02-Aug-2022 12:00:00 -1.093 0.26371 03-Aug-2022 12:00:00 1.3156 -3.9555 04-Aug-2022 12:00:00 -0.86855 2.9697 05-Aug-2022 12:00:00 1.0928 -2.3975 06-Aug-2022 12:00:00 -0.068044 3.4729 07-Aug-2022 12:00:00 -0.0094157 -0.50619 08-Aug-2022 12:00:00 -0.17102 0.043917 09-Aug-2022 12:00:00 -0.2383 0.30205 10-Aug-2022 12:00:00 0.47717 0.22321 11-Aug-2022 12:00:00 -0.18321 -0.8061 12-Aug-2022 12:00:00 -1.2081 0.2897 13-Aug-2022 12:00:00 0.91309 -0.14316 14-Aug-2022 12:00:00 -0.87483 -0.29839 15-Aug-2022 12:00:00 -1.8531 0.46788 16-Aug-2022 12:00:00 2.745 0.4555 17-Aug-2022 12:00:00 0.21941 -0.21122
[1] correlation between positive returns
find the data indices that satisfy the condition (positive return) to work out the correlation.
pos_idx = (price_to_return.Var1 > 0) & (price_to_return.Var2 > 0);
[R,pValue] = corrplot(price_to_return(pos_idx,:))
R = 2×2 table
Var1 Var2 ________ ________ Var1 1 -0.40455 Var2 -0.40455 1
pValue = 2×2 table
Var1 Var2 _______ _______ Var1 1 0.42628 Var2 0.42628 1
[2] ccorrelation between returns under 10th percentile
first, calculation the 10 percentile values for Var1 and Var2 respectively:
prct10 = prctile(price_to_return.Variables,10)
prct10 = 1×2
-1.7133 -2.0793
find the data indices that meet the condition ( < 10 percentile)
Var1_idx = price_to_return.Var1 < prct10(1);
Var2_idx = price_to_return.Var2 < prct10(2);
calculate the correlation:
[R2,pValue2] = corrplot([price_to_return.Var1(Var1_idx),price_to_return.Var2(Var2_idx)])
R2 = 2×2
1.0000 -0.4191 -0.4191 1.0000
pValue2 = 2×2
1.0000 0.7247 0.7247 1.0000

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