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modeling the behavior of stock markets: create a market simulator, technical indicator, and a strategy that generates orders

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Computational investing

There are two parts:

1 Compute stock return using Capital Asset Pricing Model (CAPM)

2 Projects:

a) Market simulator: Read in an orders file that contains trade orders (buy and sell), compute a portfolio value for all the trades and other statistics and compare the portfolio's performance with that of $SPX

b) Technical analysis: Implement a basic technical indicator and an advanced one (Bollinger value) to detect events of interest, plot them and output events as trades to be fed into a market simulator

Setup

You need Python 2.7+, and the following packages: pandas, numpy, scipy and matplotlib.

Data

Data files can be downloaded from this link or from Yahoo Finance

Place the data into a directory named 'data' and it should be one level above this repository.

Run

To run any script file, use:

python <script.py>

Source: Part 2 of Machine Learning for Trading by Georgia Tech

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