Dynamic Zones: The Evolving Indicator

Extreme investing employs the use of oscillators to exploit tradable trends in the market. This style of investing follows a very simple form of logic: only enter the market when an oscillator has moved far above or below traditional trading levels. However, these oscillator driven systems, lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market.

Herein lies the problem. Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system's mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market -- bull or bear. Dynamic Zones offer a solution to the problem of fixed buy and sell zones for any oscillator driven systems.

An indicator's extreme levels can be quantified using statistical methods. These extreme level are calculated for a certain period of time and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the Dynamic Zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the Dynamic Zones is equal to a given probability input set by the trader.

To better understand Dynamic Zones, let's first describe them mathematically and then explain their use in a trading example.

The Dynamic Zones definition:

Find V such that

for DZ Buy: P{X less than V} = P1

for DZ Sell: P{X greater than V} = P2

Where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected time period, and V represents the value of the Dynamic Zone.

The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the Dynamic Zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. In other words, 80% of the values will fall between the two extreme levels. Because Dynamic Zone levels are penetrated so infrequently, traders know that the market has truly moved into overbought or oversold territory.

Figure 1 illustrates the buy and sell zones for the S&P 500 market using a 9-day RSI indicator. Notice the area above and below the Dynamic Zones constitute the upper and lower 10% boundaries. The zones appear to evolve with the market because they use a rolling 70-day period of indicator values in their construction. The example systems throughout this article were designed for TradeStation/SuperCharts.

Figure 1


Trading Example:

As an example, let's say our 9-day RSI system has been profitable over the last few years using the generally accepted fixed buy and sell zones of 30/70. The system buys the market as the RSI indicator crosses above the 30 level and sells when it crosses below the 70 level. The system remains in the market 100% of the time. Using these set parameters, the RSI oscillator performs well in a bull market, but breaks down in bear markets. The system's temporary failure may not be due entirely to the indicator itself, but rather may be caused by the system's strict buy and sell zones. In this case the zones should be altered to fit the declining market. In a bear market the buy and sell zones of 20/70 may work more efficiently.

The Dynamic Zones work with the market adjusting themselves automatically -- increasing for the bull and decreasing for the bear. The parameters that construct the RSI indicator remain constant, but the zones adjust to better reflect the current trading environment. This is accomplished by using a rolling average of indicator values in the calculation of the zones. The key after all is to have a mechanical system make its own decisions.

Indicator Comparison:

The principles behind the Dynamic Zones can be used with any oscillator based trading system. As an example a twenty-six year time period (1/5/70 - 11/27/96) was used to trade the S&P 500 Cash Index. Our sample 9-day RSI indicator will be used to construct our Dynamic Zones. Our system will use a look back period of 70 days with a probability of 10% for both the buy and sell zones. The fixed zones will use the traditional 30/70 levels. (These systems have been designed for comparison purposes only and are not intended or recommended for actual trading).

	DZ	Fixed	% Different
Net Profit	$202,235	$86,395	134.08%
% Profitable	68.18%	73.68%	(7.46%)
Win/Loss Ratio	.80	.45	77.78%
Profit Factor	1.72	1.25	37.60%
Adj. Profit Factor	1.37	.96	42.71%
Sharpe Ratio	.27	(.26)	203.84%
Total Trades	176	133	32.33%
Win/Loss Ratio	.80	.45	77.78%
Avg. Trade	$1,149	$649	77.04%
Avg. Run-up	$4,420	$4,805	(8.01%)
Max. Run-up	$205,105	$160,820	27.54%
Avg. Drawdown	$4,567	$5,809	(21.38%)
Max. Drawdown	$65,040	$84,606	(23.13%)

Trading results courtesy of Performance Summary Plus.

Figure 2 shows the RSI system with the Dynamic Zones in top graph and Fixed Zones in bottom graph. Notice how the Dynamic Zones adjust to accommodate the prevailing short-term trend in the market. These self adjusting zones offer not only more efficient trades but more importantly additional trading opportunities. The overbought/oversold extreme levels associated with the Dynamic Zone indicator was penetrated more frequently than the fixed zones allowing for greater trading flexibility.

Figure 2


Any oscillator driven system that attempts to trade a market whether bullish, bearish or neutral, should benefit from the use of Dynamic Zones. The trading results from this trading systems confirm these findings. Indicators that have the ability to adjust their own buy and sell zones should in fact outperform those indicators that use fixed zones. Of course, further refinements can be made to systems that use Dynamic Zones to improve trading results. These improvements include: separate probability inputs for the two zones, various exit signals, and the use of money management techniques. Dynamic Zone trading systems are limited only by the imagination of the trader.

Real World Investing:

Let’s take a look at an actual trading system and put Dynamic Zones to the test. The DZ %R system we have created uses the William’s %R indicator (Parameter 1) smoothed by a special adaptive moving average (Amafuc2) (Parameter 2). The system is simple and straight forward buying and exiting the S&P 500 Cash Index as the indicator crosses its respective extreme zones.

In this example, the extreme zones are calculated by the Dynamic Zones program using the look back period of 70 days (N), and the buy/sell Probability factor of 12% (StartPrB & StartPrS). The actual Dynamic Zones program allows users to create indicators using a total of five separate user parameters, in addition to the time and probability factors. If necessary each of these parameters can be optimized by TradeStation/SuperCharts. The specific system outlined below can be used for trading options, futures or even mutual funds. The system is specifically designed to recognize high probability trading points set by the S&P 500 market.

DZ %R System

TradeStation Code: Partial code only.

Input: Par1(9),Par2(3),Par3(3),Par4(4),Par5(5),N(70), StartPrS(0.12),StartPrB(0.12);
Vars: BuyZone(0), SellZone(0), Indicator(0);
SellZone=DZSell(Par1,Par2,Par3,Par4,Par5,StartPrS,N);
BuyZone=DZBuy(Par1,Par2,Par3,Par4,Par5,StartPrB,N);
Indicator = Amafunc2(PercentR(Par1), Par2);

IF CurrentBar > 1 and Indicator crosses above BuyZone then Buy at market;
IF CurrentBar > 1 and Indicator crosses below SellZone then ExitLong at market;

The trading results for the DZ %R trading system are impressive given that it only trades 45% of the time. Its consistent nature is set up for SPX position trader or even Index Mutual Fund traders. The system can also be used as filter for other short-term trading systems.

	DZ
Net Profit	$213,510
% Profitable	82.46%
Win/Loss Ratio	1.56
Profit Factor	7.35
Adj. Profit Factor	4.47
Sharpe Ratio	.41
Total Trades	57
Avg. Trade	$3,745
Avg. Run-up	$6,444
Equity Run-up	$218,220
Avg. Drawdown	$3,817
Equity Drawdown	$25,900

Trading results courtesy of Portfolio Evaluator.

Figure 3

The performance of this system overall is well above the average. Now let’s examine the system even further by reviewing the trading results over various time periods. We will begin with an annualized break down of the key performance figures. These results reflect trades that were initiated and closed within the calendar year.

Annual Analysis (Mark-To-Market):

	Period	Net Profit	% Gain Profit Factor	# Trades	% Profitable
YTD	$37,195.03	19.92%	7.02	5	80.00%
12 month	$38,010.00	20.49%	7.15	5	80.00%
95	$35,000.02	22.89%	100.00	6	100.00%
94	$20,319.98	15.48%	3.20	7	85.71%
93	$15,655.00	13.42%	4.54	9	55.56%
92	$8,285.00	9.32%	3.30	6	66.67%
91	$41,549.98	62.74%	100.00	6	100.00%
90	$9,830.06	18.61%	2.08	7	85.71%
89	$27,789.98	98.65%	100.00	6	100.00%
88	$17,884.98	178.85%	17.71	8	87.50%

>Trading results courtesy of Portfolio Evaluator.

The next table itemizes the systems performance over extended time periods. The trading results remain extremely consistent through various market conditions.

Annual Rolling Period Analysis (Mark-To-Market):

	Period	Net Profit	% Gain Profit Factor	# Trades	% Profitable
96	$37,195.03	19.91%	7.02	5	80.00%
95-96	$72,195.05	47.21%	12.68	11	90.91%
94-96	$92,515.03	70.47%	7.00	18	88.89%
93-96	$108,170.00	92.74%	6.45	27	77.78%
92-96	$116,455.00	130.96%	5.97	33	75.76%
91-96	$158,005.00	238.60%	7.74	39	79.49%
90-96	$167,835.10	317.72%	6.16	46	80.44%
89-96	$195,625.10	694.41%	7.01	52	82.69%
88-96	$213,510.00	2135.10%	7.35	60	83.33%

Trading results courtesy of Portfolio Evaluator.

This special William’s %R trading system is able to outperform any indicator based system in its class. The trading logic behind the Dynamic Zones can benefit any oscillator based trading system.

Conclusion:

Dynamic Zones offer traders a different perspective on the typical trading systems. The markets are constantly changing, and if oscillator driven trading systems are to remain competitive, they must learn to evolve with the markets. Dynamic Zone based trading systems can actually quantify the extremes and thereby improve the trading process. And most importantly these trading improvements can be used to increase the profit potential in any market.

---

Call today to order the Dynamic Zones Analysis Pack!
Call RINA Systems at (513) 469-7462.
Existing users please inquire about special pricing.