Market Summary

This was a turbulent week for the markets as they coped with rising and then falling oil prices and the terrorist attacks in London. After closing down on Wednesday on rising oil prices and falling further on Thursday morning, a rally began on Thursday afternoon which continued strongly on Friday. The DJI gained 1.41% for the week, the NASDAQ Composite gained 2.7% and the S&P 500, 1.46%. Our market model issued an exit signal on Wednesday as the NASDAQ suffered its 5th distribution day in 9 sessions, but it reversed itself on Friday as the NASDAQ gained 1.8% and broke through the 2100 resistance level. My readers will recall that we have been watching for a breakthrough at that level since the NASDAQ's recent rally stalled just below that level on June 2. The NASDAQ is now at its highest level since January 4th, but still down 2.9% for the year. The DJI is off 3.1% and the S&P 500 is at breakeven for the year. The gains in the last two days were particularly impressive considering the events in London. With strong earnings being reported in the last few days by retailers and Alcoa exceeding earnings expectations on Friday, it appears that the markets are poised to move higher if earnings continue to exceed expectations and oil prices do not throw another scare into the markets. The potential for the broad market indexes to move higher is demonstrated in the following charts.

With the breakthrough of the 2100 resistance level, the NASDAQ is set to test the high set on December 31, 2004 of 2191.

The S&P 500 has not yet broken out of the bearish head and shoulders pattern, but the gains of this week make it more likely that the neckline at 1220 will be penetrated.

There were 40 breakouts this week, exceeding the average of the last 13 weeks, which indicates the tendency of the markets to move higher. 12 of these gained more than 5% and 3 gained more than 10%. The strongest breakout of the week was Bottomline Technologies (EPAY) which gained 16.23% after its breakout on Wednesday on 5 times average volume. This breakout was presaged by three days of price gains on well above average volume. We have often commented that the strongest breakouts occur under these conditions and we have enhanced our 'Handle Quality' (HQ) metric to allow easier recognition of these conditions. See this week's Top Tip to learn how to pick outstanding breakouts.

The two strongest sectors produced over 25% of this weeks breakouts. The Healthcare sector continued to demonstrate strength with 8 breakouts, while the Oil and Gas sector produced 5 breakouts.

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Using Handle Quality to Find Stronger Breakouts

We have previously shown (Newsletter, 4/23/05) that the strength of the breakout, as measured by the gain on breakout day, is influenced by the price and volume action on the day prior to the breakout. If the price moves up and the volume is greater than the day before, then the gain over the pivot on breakout day is around 17% better than the average breakout gain.

Until now our HQ metric evaluated a handle's properties based on the desirable behavior in the early days of the handle, when we want to see volume drying up as the price falls. It did not take account of the desirable behavior towards the end of the handle, when we want to see the handle start to turn up. This has now been corrected with the following modifications to the HQ formula:

• if the latest close is higher than the previous close and the latest volume is equal to or greater than the average volume then add 1 to the HQ score.
• if the latest close is higher than the previous close and the latest volume is equal to or greater than the previous day's volume then add 0.5 to the HQ score.

To take advantage of this enhanced HQ metric, you will need to adjust your HQ filter value. For example, to be to sure to be alerted to stocks that are breaking out when the price rose on the previous day and the volume was greater than average, then set the HQ filter to be => 1. When combined with other filters, this can be used to select very powerful breakouts, as the following example shows:

The example above also shows the enhancement made to our backtest feature, which now allows you to backtest over any number of trading days up to a maximum of 65 (13 weeks). This is to allow you to optimize your filters for current market conditions.