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Nasdaq and the Thrust Oscillator -- Part I

02/15/01 03:16:54 PM
by Dennis D. Peterson

The thrust oscillator (TO) uses market breadth measures to determine market trend.

Security:   $compq
Position:   N/A

Technical analysis employs a number of indicators and tools. Ideally you will use a set of indicators that are at least relatively independent of each other. Many indicators use the high, low, open, or close of the price, and some incorporate volume. Alternatives to indicators using price and volume data are indicators using market breadth measures. Breadth measures, such as the number of advancing and declining issues or up and down volume, are derived from price and volume in much the same way that RSI is derived from price --by using only the up days for the average up day price and the down days for average down day price. In the same way that RSI measures momentum, the number of advancing and declining issues play an analogous role.

The Arms index, sometimes referred to as TRIN for trading index, is designed to incorporate both advancing and declining issues as well as up and down volume. A number of studies show that TRIN has some shortcomings. The thrust oscillator was created to overcome those shortcomings. The formula for the thrust oscillator is

TO=(AdvI(UpVol/DwnVol)-DeclI )/ (AdvI(UpVol/DwnVol)+DeclI ),


AdvI = the number of advancing issues,
UpVol = the up volume (or the volume of the advancing issues),
DwnVol = the down volume (or the volume of the declining issues),
DeclI = the number of declining issues.

I built a thrust oscillator (TO) using Nasdaq breadth measures and charted the indicator (Figure 1: bottom chart). I saw that it oscillated, as I expected, since comparing the number of days when a stock is up to the number of days when a stock is down is the basis of the RSI oscillator. I could also see that TO tends to follow the Nasdaq. I decided to base a trading strategy on the 5- and 20-day exponential moving averages of TO.

When the faster of the two moving averages crosses above the slower line, it is considered a buy signal. When the faster line crosses below the slower line a sell signal is triggered. Since either of the moving averages can be used as an oscillator, I should be able to set overbought and oversold thresholds. I chose the faster moving average because I wanted to use the average that had the quickest reaction. The tradeoff is a more timely signal at the potential expense of being whipsawed.

Building a trading system using TO was a quick way to verify its reliability. If TO is reliable then it should be possible to create a trading system that does better than buy and hold. Since the end objective is to establish reliability, I built the system to go long. The end result was a system where a $1,000 investment in 1996 grew to $2,600. Since the Nasdaq was around 1000 in 1996, it is slightly better than a buy and hold strategy.

Figure 1: Thrust oscillator (TO) using Nasdaq breadth measures with two exponential moving averages (bottom chart), Nasdaq with entry and exit signals (middle chart), and equity performance (top chart).
Graphic provided by: MetaStock.
Graphic provided by: Data vendor: eSignal<.
Breadth indicators, used alone for a short-term trading system, can generate unreliable entry and exit signals, and it takes a bit of work, patience and experience to use them successfully. But the effort is worth the time since using breadth in conjunction with standard price-based indicators has a potentially big payoff. If you look at the chart you will see that the two moving averages move down as the Nasdaq moves down, and then move up again as the Nasdaq moves up. The 20-day exponential moving average is more closely correlated with the Nasdaq price change. That kind of movement and following is very encouraging.

I initially built a system that triggers an entry when the faster moving average crosses above the slower. This results in equity performance that does well in a bull market but has serious drawdowns in a bear market. Entry for a long position in a downtrending market is essentially going against the market, hence using breadth measures becomes risky.

I went through several steps to finally achieve an equity performance (Figure 1: top chart) that was starting to be acceptable. Again, I first started with the strategy of long entry based on the two moving averages crossing over, and saw unsatisfactory drawdowns. I next assigned overbought/oversold thresholds by taking the points on the Nasdaq that were localized high and low points and noting the value of the faster (five-day exponential) moving average. This gave benchmark thresholds of 0.2 for the overbought threshold and -0.4 for the oversold threshold. After optimizing, the values were 0.2 and -0.45. This suggests that the technique of matching Nasdaq localized highs and lows to values of the faster moving average works well. When I added crossing the thresholds to the trading strategy, I got more equity but drawdowns were still an issue.

Because I use Bollinger bands often, I noticed that some of the serious drawdown issues occurred with increased TO volatility. I then created the standard deviation of TO over a 14-day period and compared today's standard deviation of TO to the 14-day period standard deviation of TO 30 days ago. I optimized my entry based on the difference between what the standard deviation of today should be and the standard deviation 30 days ago. The result showed that today's volatility should be twice as low as the volatility 30 days ago. The statistics on this final trading system are:

-Annual gain of 33%,
-Winning trades 110, losing trades 69,
-Largest win $362.80, largest loss $184.60,
-Most consecutive wins 9, most consecutive losses 6.

It appears that if TO is properly applied it can have both short and long term signals have at least a 60% success rate. Still the drawdowns are higher than what I prefer. In Part II, I will discuss applying the MACD to TO.

Dennis D. Peterson

Market index trading on a daily basis.

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