Code covered by the BSD License
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Technical Analysis Tool
GUI for viewing simple technical analysis indicators for a time series.
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axislocations_set(obj)
tatool helper function to set axes locations to their expected locations
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axislocations_store(obj)
tatool helper function to store current axes locations and so that
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bollingerul(data,period,nstd)
Function to calculate the upper and lower bollinger bands for a vector
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cci(data,period)
Function to calculate the Commodity Channel Index of a data set
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dema(data,period)
Function to calculate the double exponential moving average of a data set
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dpo(data,period)
Function to calculate the detrended price oscillator of a data set.
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ema(data,period)
Function to calculate the exponential moving average of a data set
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etb(data,period,percent)
Function to calculate the envelopes(trading bands) for a data series
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getclassfromworkspace(classna...
tatool helper function for getting the name of all variables of a
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getvarfromworkspace(WS,varnam...
TATOOL helper function to get a variable with the given name from the
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lri(data,period)
Function to calculate the linear regression indicator of a data set.
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macd(data,p1,p2,p3)
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momentum(data,period)
Function to calculate the Momentum of a data set
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roc(data,period,format)
Function to calculate the Rate-of-Change of a data set
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rsi(data,period)
Function to calculate the Relative Strength Index of a data set
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sma(data,period)
Function to calculate the simple moving average of a data set
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tatool(flag)
This is the entry point function to create a tatool, technical analysis
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wildersmoothing(data,period)
Function to perform Wilder Smoothing on a data set
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wma(data,period)
Function to calculate the weighted moving average of a data set
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ALLFUNCTIONS.m
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ReadMe.m
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View all files
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Technical Analysis Tool
by Phil Goddard
GUI for viewing various simple technical analysis indicators of a time series
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| wildersmoothing(data,period)
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function out = wildersmoothing(data,period)
% Function to perform Wilder Smoothing on a data set
% 'data' is the vector of values to be smoothed. The first element is assumed to be
% the oldest data.
% 'period' is the length of the smoothing window.
%
% Example:
% out = wildersmoothing(data,period)
%
% Error check
[m,n]=size(data);
if ~(m==1 || n==1)
error(['The first input to ',mfilename,' must be a vector.']);
end
if numel(period) ~= 1
error('The Wilder smoothing period must be a scalar.');
end
% perform the filtering
ld = length(data);
if ld < period
error('The data vector must be at least as long as the required period of smoothing.');
elseif ld == period
out = mean(data);
else
out = nan*ones(size(data));
out(period:end) = filter(1/period,[1 -(period-1)/period],data(period:end),sum(data(1:(period-1)))/period);
end
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