Modifications, Updates, and New Data

Updates to our back testing platform brought in a whole new set of data -- visual data. To reiterate, our signals are:

Strategy 

Buy:

- Price above 200 day MA, and
- Price above the 50 day MA, and
- Price sets a new 10 day low

Sell:

- Price drops below the 50 day MA, or
- Price sets a new 10 day high, or
- Position has been open for 10 days

In order to check if our signals provide an edge we compared it to a random strategy.  We will be calling this our 'base case' and the signals are:

Base Case

Buy: 

- None

Sell:

- Random day in the next 1 to 10 days

We've also created a portfolio function that allows us to account for our initial investment, commissions, and slippage; it will also avoid fractional ownership.  Our portfolio parameters are:

Portfolio

- 5,000 initial investment
- 3.95 comission
- Random slippage of [-.5%, .5%] of the target price

We conducted 10,000 scenarios with each being a possible sequence of trades over the duration of our analysis. Here is our data:

Chart Legend

- Gray: end of trade portfolio values for all 10,000 scenarios
- Blue: middle 25% of gray values
- Red: the return of buying and holding SPY

2007

Stratgey			Basis
Ave. Return	44%		Ave. Retrun	1%
Stdev.	30%		Stdev.	24%
Max. Return	207%		Max. Return	196%
Min. Return	-40%		Min. Return	-74%
Scenario Returns > 0	95%		Scenario Returns > 0	48%

2008

Stratgey			Basis
Ave. Return	35%		Ave. Retrun	-34%
Stdev.	24%		Stdev.	32%
Max. Return	160%		Max. Return	173%
Min. Return	-23%		Min. Return	-96%
Scenario Returns > 0	95%		Scenario Returns > 0	12%

2009

Stratgey			Basis
Ave. Return	87%		Ave. Retrun	30%
Stdev.	40%		Stdev.	57%
Max. Return	328%		Max. Return	627%
Min. Return	-21%		Min. Return	-92%
Scenario Returns > 0	99%		Scenario Returns > 0	68%

2010

Stratgey			Basis
Ave. Return	44%		Ave. Return	10%
Stdev.	25%		Stdev.	26%
Max. Return	168%		Max. Return	154%
Min. Return	-276		Min. Return	-39%
Scenario Returns > 0	98%		Scenario Returns > 0	61%

2011

Stratgey			Basis
Ave. Return	6%		Ave. Retrun	-7%
Stdev.	16%		Stdev.	23%
Max. Return	78%		Max. Return	142%
Min. Return	-37%		Min. Return	-75%
Scenario Returns > 0	63%		Scenario Returns > 0	33%

2012

Stratgey			Basis
Ave. Return	27%		Ave. Retrun	6%
Stdev.	21%		Stdev.	24%
Max. Return	137%		Max. Return	193%
Min. Return	-27%		Min. Return	-69%
Scenario Returns > 0	91%		Scenario Returns > 0	56%

Code:

Language: Python 2.7

Third party packages: NumPy, matplotlib

FileSnack zip folder: http://snk.to/f-c7k56nnx
GitHub main program: https://gist.github.com/theBrokeQuant/5746064

The FileSnack link has everything we'll need to run our program; it's a zipped folder that contains:

• theBullsSupplier.py
• poorBoysData.py
• SP500.txt
• Empty folder 'Tickers"

If we have all the prerequisites then we can simply copy and paste the GitHub code to a new python file.