Portfolio Performance for June 2009

June was a great month, both personally and for the portfolio. My family and I headed off to Texas for a few weeks to spend time with family and escape to the hill country for some good old R&R.

It was great visiting with everyone, checking out the beautiful Texas scenery, and enjoying some great food. There's a place in Liberty called Jax that served great catfish and an equally great ambiance. The restaurant is just across the street from the courthouse...so the place is the true heartbeat of the town. Could have been a setting out of a John Grisham novel. Very cool.

The picture taken to above was a rainbow we caught on our way back from dinner just before sunset. Felt it was appropriate considering the portfolio beat the market for the first month since February.



Not obvious in the above chart, but the S&P 500 returned only 0.02% for the month of June. And the portfolio returned 1.58%. Not much to brag about but nice to breathe some air for a month.


For the month of June, the portfolio is approximately 21% in cash which is quickly dropping due to the high number of signals received in the month of July.

As far as the portfolio simulation engine...I've had some exciting progress this past month.It really helped getting some quiet time. Each morning, I would get my coffee, sit out on the front porch, watch the hummingbirds go to war, the doves get lovey, and hack away on the simulation engine. I've created a new database that utilizes the Python's struct module for binary storage, SQLite for storing pointers to the records, and Numpy for field named record access. The best part is the database requires very little memory, has a small disk footprint, and is faster than anything I've worked with before. Previously, using a database of any kind was not an option. The aha moment was in realizing the bottleneck in performance was due to the number of records stored not the size of the records. Therefore, my main goal was to reduce the number of rows in the table and scale horizontally in the table versus vertically. This drastically reduced the lookup time.

Now, I'm in the process of refining the reporting engine and building a price series plotting framework with Matplotlib and Numpy. So, far the results look very promising. Nice to finally get some pretty charts to the simulation engine instead of a clunky MS Excel interface. Still more work ahead.

Heck, I've made so much progress sitting out watching those birds in the morning that I came home and started on a flower garden in our backyard. I've just finished tilling up the dirt and planting a few plants. We've already got hummingbirds fighting and a squirrel trying to figure out how to open that bird feeder. Now, I just need to get to hacking!

Later Trades,

MT