Market Extended, Still Dips to Buy

The market is getting extended again, but with the Citigroup news, the futures are signaling that we might see a 4th day of gains. I will probably add another couple names to my portfolio because as everyone has learned, if your not long, your wrong.

The Power Dip System is consuming the bulk of what used to be my blogging time as I am testing and then uploading many models (ways to trade the system picks) to the new site. I’m testing on over 29K symbols, and running some filters to ignore various unwanted securities such as preferred share issues. It all takes a lot of time. I relish the thought of blogging again about something besides the Power Dip. That day will soon be here.

One of the beta testers (as well as Dr. Fly) suggested that we needed a better way to alert users to closed trades. The graphic above was Jeremy’s solution. It will greet you in the sidebar of the home page.

Yes, beyond critiquing the new Power Dip site, there are rumors that even Dr. Fly himself, an avowed hater of all things technical analysis, is becoming fond of the system. Shhh…don’t tell anyone that he gave more than a passing consideration of the black arts!

The Power Dip System is long only.

Buys weakness in strong stocks.

Sells positions into strength.

Produced over 400 trades in 2009.

Uses a liquidity and volume filter.

Doesn’t produce picks every day.

Works well with a percentage or volatility stop.

Can be traded as a system or not.

At a minimum should be traded with 10K, if traded as a system.

Should not be traded with one’s entire account.

Has an exit price threshold published and updated at every close, until the position is closed.

Does not scale in or out.

Entry signals published nightly.

Sends email alerts at 3:30 for any positions meeting the exit threshold.

Will have many models to consider for those who want to trade it as a system.

I’m sure there are more, but this is all I can think of right now. The PDS site will have more in depth FAQs as well as instructions for navigating the site.

The Power Dip web service is in beta testing. I am getting some great feedback on the service, and am looking to implement a few of the suggestions before launching.

I am most excited about the email alerts, which will be sent out at 3:30 for any positions exceeding their exit thresholds. This is a very cool function for working stiffs like myself.

System performance has been excellent, with over 2% average trade and 78% winners since we started tracking it automatically.

Stay tuned…More to come!

As we get closer to launching, I’ve been getting some questions about using limit orders with the Power Dip. The system was configured to be an end-of-day system, meaning the signals are given in the evening and acted on the next morning. I’ve never personally traded the system using limit orders. However, for traders who can trade intra-day, the question always comes up about setting limit orders instead of market-on-open orders. There would be a couple of benefits to using limit orders orders rather than MOO, the primary benefit being that one would not be floating a market order during the open when spreads are wide and liquidity can be thin. The other benefit can be a significant price improvement, easily enough to cover the cost of commissions.

What would happen if we waited for the opening print, and then set a limit order just beneath that price?

For these backtests, I set a limit order -0.30% beneath the open. The results are very interesting. (All tests used .01/share for commissions, 10% stop, 1% risk per trade, with 10 maximum open positions, from 1/1/1990 t0 12/4/2009).

Compound Annual Growth Rate: 17.38%
Average Trade: 1.61%
Percentage of Winners: 66.38%
Number of Trades: 2070
Average Days Held: 9.18

The results aren’t bad. The major difference between these results and the results of using market orders on the open is that opportunity is reduced by ~70%. Even though the average trade increased from 1.15% to 1.61%, 70% of the orders were not filled as the stocks never traded 0.30% beneath the open. (This in itself is an interesting statistic).

The decrease in opportunity is demonstrated in the CAGR, which fell from ~47% to ~17% (astute readers may have noticed that CAGR decreased almost as much as opportunity, roughly 65%).

Of course when opportunity decreases, so does our exposure and our cost of doing business. How then can we take advantage of a larger average trade and decreased exposure/commissions? We can simply double our risk per trade, and theoretically our results should double.

The results below assume 2% risk per trade (2K risked per trade on a 100K account) rather than the 1% risk in the previous test.

Compound Annual Growth Rate: 28.29%
Average Trade: 1.63%
Percentage of Winners: 66.16%
Number of Trades: 1631
Average Days Held: 8.24

We now are looking at performance that is still almost 20% less annualized than using market orders on the open, however, we will have significantly decreased our exposure and our commissions. Furthermore, these results are more likely to be replicable in real-time as slippage and wide opening spreads have been taken out of the mixture.

Finally, lets increase our limit order to be -0.40% beneath the open and look at those results:

Compound Annual Growth Rate: 14.80%
Average Trade: 1.98%
Percentage of Winners: 65.70%
Number of Trades: 1452
Average Days Held: 8.49

Again, the low CAGR is due to lack of opportunity. An average trade of 1.98% is huge, but there were only 1452 chances over the past 20 years to earn this 1.98%.

The other way to use limit orders for an end-of-day system is to base them off of the previous day’s close. The next post will take a look at setting limit orders x% beneath the previous day’s close. This method would be replicable for traders who can’t trade during the day and normally have to use market orders on the open.

Here are some good articles on percent-risk position sizing:

The Percent Risk Model: Size Does Matter

Position Sizing

The results below show the performance of the Power Dip system risking 2% of account value on each trade (all previous tests have used 1% risk), with a maximum of 5 position held at one time. All other parameters from previous tests remain the same: .01/share commissions, 10% stops, opened at the open and closed at the close.

The system grows capital to such a large amount that near the end of the test period, it would be buying positions so large that it would move the market. The point is that doubling risk nearly doubles performance.

More needs to be explained about using percent risk position sizing, but this will have to suffice for now. Feel free to ask questions in the comments section.

Some readers have posed good questions about the Power Dip, in terms of how the system would perform during various alternative external conditions. For example, what would happen if gains were not compounded, or we bought one day late, or trade size was reduced as not to move stocks without enough liquidity to handle the required position-size. This post compiles a summary of system results during various not-optimal external conditions.

Keep in mind that the factors in the Power Dip that determine when stocks are bought or sold have not been optimized to any extent, except in the case of one factor, which was loosened to provide more opportunity.

However, we should not ignore what I consider to be “external conditions” as they too may be optimized. In many ways it is harder to curve-fit external conditions as the trader may have little choice as to how much slippage occurs, or whether or not he is forced to trade only at certain times of the day. What the results seem to suggest is that external conditions are primarily measuring exposure, be it due to increased position-sizing (compounding) or more/less time in the trade.

One reader suggested that I discard the top x% of trades and then report the system returns. That would take some extra work in excel, and I think the profit distribution graph below shows that gains are not coming from a few large trades. I therefore did not run that specific test.

Summary

The results are of course predicated upon the risk per trade and stop level used.

As I mentioned, the primary difference in most of the external conditions is the adjustment in exposure levels as well as amount of opportunity. Keeping with the line of thinking that returns are affected by exposure, we can get out-sized returns similar to the returns provided by not using a stop. This is accomplished rather simply, by adjusting our risk to 2% per trade. And, we can keep using a 10% stop.

In the end, monitoring slippage, monitoring the overnight vs. daytime risk premium, and making sure to capture every opportunity are the most important considerations when trying to replicate historical, backtested results with real-time trading results.

I’ve taken a screen shot of the new Power Dip premium service.

Below are today’s picks.

There were no sell signals for today.