Introduction

Following is a proposal to adopt a new strategy for the hedge fund and a supplemental strategy for the discretionary fund. The objective of this strategy is to construct a consistent philosophy and trading plan based on an observational model about how markets work in the context of the Hanseatic model's characteristics.

How Markets Work

One can argue endlessly about the sources of price change in markets. Fascinating, and fortunately, unnecessary. The purpose here is to suggest a model of price behavior based on a lot of study and some statistical characteristics of our model. We're trying to combine a few fundamental principles into a consistent process. The major objective of this process is simply to be in harmony with the market's movements, patterns and environments. First, in general terms, this is the basic observational model of market environments.

One can argue endlessly about the sources of price change in markets. Fascinating, and fortunately, unnecessary. The purpose here is to suggest a model of price behavior based on a lot of study and some statistical characteristics of our model. We're trying to combine a few fundamental principles into a consistent process. The major objective of this process is simply to be in harmony with the market's movements, patterns and environments. First, in general terms, this is the basic observational model of market environments.

One of the most compelling books I've read about price behavior is The Path of Least Resistance. The author, Robert Fritz, is a musician and there is no mention of markets in this book. He talks about the underlying structures (of anything) determining the path of least resistance. Some structures lead to oscillation and some structures lead to resolution. Similarly, markets spend a lot of time oscillating in trading range environments, where the dominant price characteristic is to move away from the mean (smooth price) and generate a buy or sell signal which represents a return to one end or the other in the oscillating structure. But market forces, whatever their composition, do not permit price to resolve outside the oscillating structure, hence a return to the smoothed price, and then a deviation in the opposite direction. At some point as the market moves through time, some combination of fundamental and/or technical factors create a structure that resolves (into a trend).

Then the path of least resistance for the market is to move away from the smooth price in a sustained way. Market psychology and momentum make if difficult for signals counter to the trend to extend beyond the smoothed price of the larger time dimension (weekly). Instead, volatility declines and the market enjoys a benign period of "sponsorship," that is interrupted by minor excesses (i.e. figure 8 type patterns) and corrections of these excesses.

At some point in time, excess develops in the larger time dimension that is relieved by either a correction in time, i.e. trading range, or resolution and sustained trend in the opposite direction.
This is a general philosophy of price behavior in markets as I have observed them over the years. It applies, I believe, to all time dimensions and with rare exceptions, to all markets. Is this philosophy perfect and do prices always behave in the framework of these two dominant structures? No and no. As we all know, the reality of markets is that they can behave in ways that are quite messy and very frustrating to rigid rules. But I nevertheless think that it is important to have a market philosophy, and that a trading plan absent that philosophy is not likely to be successful.

The Hanseatic Model

With the relatively slow smoothing in our exponential moving average, the buy and sell signals are essentially a trend-following model. However we have never used the model in this way. Rather, to the extent we use the signals at all, it is very selective and then sometimes in the opposite direction, i.e. buying on a sell signal, or what we refer to as a countersignal. Nevertheless, because I want to incorporate these signals in the trading process I am proposing, it is important to know the characteristics of the signals.

Using the Ten Year Notes as an example, this is a summary description of all buy and sell signals for this market: Since October, 1993 there has been a total of 123 buy and sell signals. 29.3% have been profitable, 70.7% unprofitable. The profit factor is 0.70 and the total gain for all trades is -26.98%. Profit factor (PF) is the sum of the gains divided by the sum of the losses (PF = 1.0 is break even). If we look at the best winning trades, say the top 5% which is the best six trades in this case, the gain from these trades are 52% of the total gain. Of 123 total trades, only 36 were profitable, and 5 of the 36 winning trades accounted for more than half the gain. The biggest single trade contributed 20% of the total gain.

The most basic conclusion we can draw is that most of the signals lose and that relatively few trades account for most of the gain. Said another way, the majority of trades belong to the oscillating trading range environment and a minority of trades resolve into trends. The table on the next page shows some relevant statistics about the signals for a wide variety of markets.

Some conclusions we can reach from the signal analysis are as follows:

1. Overall, about one-third of all signals are profitable, the remaining two-thirds of signals are unprofitable. U.S. financial markets have been profitable less than 30% over the last ten years. A few commodities have had good signals over 35% of the time.

2. The profit factor over a wide range of futures contracts is essentially 1.0 or breakeven, and negative for U.S. financial markets.

3. On Average, about 45% of the total gain for a market is accounted for by only 5% of the total trades. In the S&P 500, 10 out of a total 202 daily buy and sell signals made 51 % of the total gain, or 100% of the total gain of 197%. About 74% of the total gain, or 146% of the total gain of 197% is derived from only 10% of all the trades.

4. Not discernable from the table are two other perhaps obvious but nonetheless salient facts. First, losing trades are relatively short and winning trades last much longer. Losing trades last about 6-8 days on average, while the best trades last from 25-100 days. Second, 30-40% of the maximum gain during a buy or sell signal is given up as the market reverses course and transitions to the opposite signal.

Trading Plan

Our goal is to develop a trading plan that is consistent with both our observational philosophy and the nature of our basic model. The objectives of the trading plan are as follows:

1. Participate in every major trend in every market or stock that we choose to trade.

2. Function in the oscillating or trading range markets through the use of countersignals.

3. Try to observe and trade the excesses that develop in every trend using the figure 8 and other patterns of that character.

4. Conserve capital.

Now, returning to the observational model shown earlier, the diagram below is an expanded version that incorporates the Hanseatic model.
Note: B* and S* refer to new signals.

This is how I view market price flow incorporating the characteristics of the model and some of the patterns we have developed. Another way to view the process is as a sequence of market patterns or fractals.

We have quite a bit of experience in trying to develop models that are similar in character to the process above. That is, selling into strength in the trading range environment, taking selected signals that have better probabilities straight, and trying to recognize the transition from a trading range environment to a trended environment. My conclusion is that while it is relatively easy to model a base version of the process, try to capture all of it makes the model very complex.

I am proposing that we us the discipline inherent in the process to trade a wide variety of exchange traded funds, individual stocks and futures. That we anchor ourselves to the process, but not a systematized model of the process. When one analyzes a market using this process, there is only one task at each part of the sequence. In the countersignal environment, the only thing to observe is whether or not the signal has developed any trend characteristics. Most of the time it doesn't. In a trend environment the only purpose one has in the daily review of the model is to determine whether one of the "excess" patterns has developed. This is quite different and more efficient that analyzing a market from the perspective of both daily and weekly models and all their parameters.

Application to the hedge fund

Below are a list of exchange traded funds (ETF) which have good liquidity and which taken together represent a composite of the equity markets' dominant themes, i.e. growth and value, its structure in the form of large, middle and small capitalization stocks and the sectors and groups which compete for leadership.

Other Considerations
What I am proposing obviously entails some observation and judgment, albeit within the framework of a defined process. My intention is to have the process itself shoulder the burden of the trading decisions rather that the trader. Inevitably there will be errors of judgment and stops will be an integral part of the process.
Does this mean that we stop trying to design systematic models for the futures markets or equities? No! We are about to finish the NDX models mentioned on the R&D agenda for instance, and that will be implemented in a systematic way. But, as a practical matter, the actual experience of trading this process on a daily basis will give us a better chance at programming more and more of the process.