numpy scipy larry nose bottleneck paramiko

1. create an hdf file that holds stock quotes

   "python re-generateHDF5.py"

2. edit the file containing information for PyTAA to report results

   • options exist to send an email to your desired email from another email account (they don't have to be the same email account)
   • edit PyTAAA.params with a text editor and replace example values with your information

3. run PyTAAA with the command: "python PyTAAA.py"

   • the code updates quotes and re-runs every few hours. It runs un-interrupted for 2 weeks (duration can be changed in PyTAAA.params).
   • on the 2nd trading day of the month, PyTAAA recommends new stock holdings

4. It's up to the user to decide if they want to do anything with the recommendations. This is designed and provided for entertainment only. The author does not accept and responsibility for anything done by others with the recommendations.

5. To let the code know how to track a portfolio for you, manually update the stock holdings in "PyTAAA_holdings.params".

6. A web page is created in the 'pyTAAA_web' directory. In Windows, you can double-click pyTAAAweb.html to see the latest status and holdings, as recommended by PyTAAA.

Backtest plots that start ca. 1991 contain different stocks for historical testing than those created by 're-generateHDF5.py'. Therefore backtest plots will not match those created by PyTAAA.py and shown on the created web page. This is due to changes in the Nasdaq 100 index over time.

The backtest plots show only an approximation to "Buy & Hold" investing. This is particularly true for the Daily backtest that is created every time the PyTAAA code runs. Buy & Hold is approximated on the plot by the red value curves. The calculations assume that equal dollar investments are made in all the current stocks in the Nasdaq 100 index. For example, note that the current Nasdaq 100 stocks as of February 2014 did not have the same performance during 2000-2003 as the stocks in the index during 2000-2003. Whereas the Nasdaq Index lost more than 50% of its peak value, the stocks that are in the index as of February 2014 AND were also in the index in 2000, maintained nearly constant value over the period. Similar cautions need to be made about the historical backtest performance of PyTAAA trading recommendations. Therefore, hypothetical performance as portrayed by PyTAAA backtests should be viewed as untested and unverified. Actual investment performance under real market conditions will almost certainly be lower.

PyTAAA will reflect changes in the Nasdaq 100 index over time automatically. It checks a web page each time it runs to ensure that current stocks it can choose match the index.