Exponential Moving Average Stock Model Documents

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Main Document

Exponential Moving Average Sock Model 

written by Matthew Mohorn

A primary application of econophysics  is using digital signal processing techniques to filter and predict market data, which is theorized to exhibit random walk motion.  An exponential moving average is one tool that physicists use to smooth data from an input signal to identify its trends.  The Exponential Moving Average Stock Model implements three types of exponential moving averages and allows the user to change the parameters of each.  The model allows the user to view the results of exponential moving averages computed on the New York Stock Exchange daily closing price of six familiar companies.  It demonstrates one way that traders use causal filters to smooth market data and forecast the next day's price.

Last Modified February 15, 2013

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Source Code Documents

Exponential Moving Average Stock Source Code 

The source code zip archive contains an XML representation of the Exponential Moving Average Stock Model.  Unzip this archive in your EJS workspace to compile and run this model using EJS.

Last Modified February 15, 2013