How To Compute Chaikin Money Flow (CMF) using MATLAB?

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by dana , in category: Third Party Scripts , 4 months ago

How To Compute Chaikin Money Flow (CMF) using MATLAB?

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1 answer

by aniya.jaskolski , 4 months ago

@dana 

To compute Chaikin Money Flow (CMF) using MATLAB, you can follow these steps:

  1. Prepare your data: You need historical price data for a particular asset (e.g. stock, currency pair, etc.) to calculate CMF. Make sure you have the high, low, close, and volume data for the asset.
  2. Load the data into MATLAB: You can load the data into MATLAB using the readtable function or any other method that suits your data format.
  3. Calculate the Money Flow Multiplier: The Money Flow Multiplier is calculated as follows: Money Flow Multiplier = ((close - low) - (high - close)) / (high - low)
  4. Calculate the Money Flow Volume: The Money Flow Volume is calculated as follows: Money Flow Volume = Money Flow Multiplier * volume
  5. Calculate the Accumulation Distribution Line (ADL): The Accumulation Distribution Line is calculated by summing the Money Flow Volume over the desired period (e.g. 20 days).
  6. Calculate the Chaikin Money Flow (CMF): Finally, CMF is calculated by dividing the ADL by the sum of volumes over the desired period (e.g. 20 days). You can use the cumsum function in MATLAB to calculate the cumulative sum.


Here is an example code snippet to calculate CMF using MATLAB:

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% Load historical price data
data = readtable('your_data.csv');

% Calculate Money Flow Multiplier
money_flow_multiplier = ((data.Close - data.Low) - (data.High - data.Close)) / (data.High - data.Low);

% Calculate Money Flow Volume
money_flow_volume = money_flow_multiplier .* data.Volume;

% Calculate Accumulation Distribution Line (ADL)
adl = cumsum(money_flow_volume);

% Calculate Chaikin Money Flow (CMF)
period = 20;
cmf = adl ./ cumsum(data.Volume);

% Plot the CMF
figure;
plot(data.Date, cmf);
xlabel('Date');
ylabel('Chaikin Money Flow (CMF)');
title('Chaikin Money Flow (CMF) for the Asset');


Make sure to replace 'your_data.csv' with the path to your historical price data file. You can also adjust the period (e.g. 20 days) and customize the plot according to your preferences.