1. By Shivgan Joshi Qcfinance.in
Technical Analysis using MATLAB using Financial Time Series Focus on Moving average and Bollinger Bands
By Shivgan Joshi
Qcfinance.in

2. Caution
MATLAB is case sensitive

3. Difference formats to get data in the FTS Object
From CSV
From file directly
From the .dat file
Using ascii2fints carefully by specifying the right parameters

4. Input CSV – Method 1 filename = 'csvlist.dat'; M = csvread(filename)
Make sure it is numeric format
Then create fts object from matrices
ead.html

5. Inputting Data
.dat are tab delimited data which can be saved using excel txt save
myinc = ascii2fts('input.dat');
An alternative is the load command to bring all variables from a file into the current variables
ASCII2FTS is an important conversion function ml
analysis-examples.html

6. Code Part 1 Use GUI to import the FTS
Things work with the close price so all other prices don’t matter
macd_input = macd(input);

7. Code for Moving average of the data
subplot(2, 1, 1);
plot(macd_input);
title('MACD of Input Close Stock Prices, 10/01/95-12/31/95');
datetick('x', 'mm/dd/yy');
subplot(2, 1, 2);
highlow(part_input);
title('IBM Stock Prices, 10/01/95-12/31/95');
datetick('x', 'mm/dd/yy')

8. Bollinger Band on the Data
[input_Mid,input_Uppr,input_Lowr]= bollinger(myinc);
input_CloseBolling = [input_Mid.CLOSE, input_Uppr.CLOSE,...
input_Lowr.CLOSE];
plot(input_CloseBolling)
title('Bollinger Bands for inputney Closing Prices')

9. Cleaning and Exporting Data
Count rows and columns of matrix
[rows columns] = size(input)
for a = 1:rows
Input(a,2)
end
if input(2,a)>100
disp('Value within specified range.')
csvwrite('csvlist.dat',input)

10. Saving output
rite.html

11. Playing with matrix
Logic including count, for and if to extract the data

12. [input_Mid,input_Uppr,input_Lowr]= bollinger(candle);
tsmat = fts2mat(tsobj)