Continuing my work on the PairDicator theme, this is the PDQ Dashboard reflecting most of the database metrics I need in order to apply some more sophisticated system trading algorithms and the resultant signals.
Over the past 2 months I've put together a number of pair baskets that I intent to track and trade on a systematic basic. Although my original focus was on ETFs, I've found that adding a few correlated stocks into the basket mix can definitely pump the net return numbers.
My current stable of ETF pair baskets includes Qs, UUP, KRE, RTH and XHB.
The stock based pair baskets include GE, NEM, EXPD, COST and LUV.
Sticking with the PDQ template as shown above, each basket contains 9 pairs.
As with most of my projects, this is a work in progress and has consumed a few hundred hours of fiddling around with these data fields that I hadn't really anticipated.
Nevertheless, I'm encouraged by the current product and optimistic that ongoing refinements of the PDQ will provide a robust and adaptable predictor of market momentum.
Watching the various pairs Z-score reversals intraday for the past 2 months has given me a real appreciation for the forecasting possibilities of this rather simple algorithm. At the same time I've come to understand why several large prop shops focus enormous capital on pair trading strategies as pair trading can significantly handicap the risk otherwise assumed by taking a directional position. Pair trading is not about trading market direction, but rather about trading the relative strength and momentum of various sectors and themes. Clearly a different approach to gaming the markets and one that, as shown briefly already, can provide an effective risk management tool.
An additional benefit of using the PDQ basket format is its scalability both in terms of capital deployment and signal confirmation (add-to positions).
Just a caveat . . the data shown above is from 10/9/09 and does not reflect current PDQ signals.