Pattern recognition?

Does the pattern recognition work?

This is really tough question. The technical analysis rely heavily on pattern recognition. Here I will share my opinion without covering all the issue.

I prefer to rely on more marginal patterns that the most used. I mean that when we have a formed typical pattern, everybody sees it. And when that happens a very complex relationship develops between the market participants. In the litterature it is referred as the insider's game.
Is it the true or just a plausible explanation I do not know.

Anyway I prefer to use more marginal patterns for that reason.

The Law of the charts of Joe Ross is a very good choice.

The Wolfe waves is another good choice.

You can refer to the excellent book Trade Chart Patterns Like The Pros
by Suri Duddella. As he says you need only one pattern to be successful. In this book you can find reference for many patterns in a consistent way.

What happens in the market?

My theory is that in the Forex markets we have long term memory chaotic processes. And then it is possible to accept that what happens now determine the future.

So basically the price movement can be persistent (fractal dimension less than 1.5) or anti-persistent (fractal dimension bigger than 1,5) according to its fractal dimension.

On the market those phases can be seen easily.

-So when a fractal break - out starts we have a transition and during this transition patterns are formed that will indicate how far this break - out is going to go. I mean the Fibonacci relationships.

-When we are into a range-bound and anti-persistent movement often the Wolfe waves give us a clue where the price may go when it goes out of balance.

-Often after the fractal break out the movement starts to consolidate there often we see harmonic patterns to develop.

Forgive me folks I do not have pictures and shots for today. This is only abstract and theoretic stuff.

High frequency algorithms versus human traders

The topic of the high frequency algorithms is a very hot potato. In fact there is a phenomenon called the rise of the machines. The stock market nowadays is totally dominated by the high frequency algorithmic trading. The old school of the technical analysis is facing hard times.

What is the difference between the high frequency algorithms and the human traders.
In fact the main difference is that the human traders are not cooperative between themselves buts the high frequency algorithms can cooperate in a blink of an eye and create strange moves.

Yes the market may seem the same but an experiences eye can distinguished that its structure is different. It does not behaves the same way like before, the risk level and the volatility is much higher. The volume in the stock market is somewhat artificial. The Forex market is different of course.

Is it possible to use the algorithmic trading trading to the benefit to the medium retail trader?
Well I think that with the fractal dimension analysis we have some tool that we can use.
The exposed ideas have the task not to be a holy grail (not at all in fact) but to reestablish the balance that has bee perturbed by the algorithmic trading.


Risk 1: A systemic risk of market failure

The high frequency algorithms are a source of systemic risk of the market. Remember the flash crash of May 6th 2010? In fact those algorithms work like turbo accelerators of the movement.
The common approach is to look for a software bug, but I think that there is much more than that in the darkness.

My hypothesis is that a proper way to analyze the market is to analyze it as a multidimensional phase space of possible solutions. And what happens? It happens that sometimes this phase space is not too difficult, or in other terms is in the reach of the computing capabilities of the high frequency algorithms. What happens then? It happens that those machines combines their effort and start to cooperate together and all this in a blink of an eye. This is a hypothesis could be valid only when we have many competitive machines and not only one mega machine dominating the whole market.

Risk 2: Point of no return. Are we there?
We have to cope with this new reality. This is true because if they get out of the market the market will collapse in a blink of an eye.

Prediction versus Observation

A modern market approach consists in not trying to predict based on the gut feeling, technical analysis or even fundamental analysis.

The idea is to try to predict not the market direction but the market state.

1. Cluster the market states:

All the successful traders have in common that they try to distinguish the market state.
A common approach is to use the relationship between the time of the day in the forex markets and the corresponding volatility.

2. Appropriate Use of an adapted system for the period

So when a market state is identified it is necessary to use an adapted system for this market state.

Traditionally there are:

2.1 Intra-day Trend following system

A Moving average strategy is the archetype of those systems.

Neural nets perform very bad as a trend following systems (with some exceptions for Neural Nets specially tuned for those conditions).
Digital filters with genetic optimization do much better


2.2 Intra-day Range Bound system

Oscillator based strategy is the archetype of those systems. Modern oscillators appears to be much smoother but still all the oscillators shares a collinearity.

The neural nets perform well in those conditions.
Statistical indicators performs very well too. In fact the phase space is so big under such conditions that it is more appropriate to model it statistical instruments. The Bollinger bands as a rudimentary statistical instrument is a classic player in the Intra-day range bound systems.


2.3 Break - out system after a contraction of the volatility

Those systems are particular. For example a Neural Net cannot never ever predict a break-out in the forex market.

How to distinguish between those market conditions:

Well the obvious reason is practice, practice, practice and experience, experience, experience
The human mind and the human perception abilities are much more suited to distinguish those states than any machine. For example an image recognition, the machines are still not capable of doing it for now.

There are some methods and some new ones that will be covered later.

My opinion is that the human mind is appropriate to distinguish between the market states. We believe that when a market state is identified it will continue for a while.

Second we use statistical instruments and methods to help us.

And third once a state is identified we use the appropriate tested methodology. For me a tested algorithmic system appropriate for a particular market state outperforms the average human trader.

So we should not try to predict the future. Even if we try to predict this will destroy our capacity of observing. This phenomenon happens because we select and choose to observe only what conforms our hypothesis.

When the prediction is useful?

In fact the prediction is useful when you manage your position once the position is open.

Example 1: Trend prediction

You open a trade in a trending environment for example after a break - out. Your setup was good (a setup is a setup) and once your position is opened and the stop loss is returned to zero, your prediction game starts.

Now you are trying to predict the market, what is going on, what will happen in order to manage a position.

Remember, this is like chess game. Your little position can be like a spawn that can turn up to be a queen, when it reaches the end of the chess board. And in order to be a queen you have to push it forward. And as in the Chess a group of spawns have a better chance to reach their goal, to become a queen.

And vice versa as Glenn Neely observes even if you have a very good prediction capability this will not help you in your trading (even if you are right maybe your timing was wrong, or the stop was hit just before your prediction come true). You need a good setup.

Example 2:
You have a setup in a ranging environment. You buy at an oversold level. Logically you predict that it will reverse when it goes up at an overbought level. And this is prediction after you have opened a position.

Conclusions:
There are two types of trading styles. Those strategies have advantages and disadvantages.

One trading style is based on the prediction: Elliott wave analysis is the best example.

The second trading style is based on a behavior of the market with statistical tools: the price action setups are one of the best examples. For example a break - out strategy in a period with high volatility.

A third strategy is a mixed strategy between a behavioral and prediction. You use your setups as a behavioral strategy and try to manage your winning positions by a prediction strategy.

The advantage of the behavioral strategies is the good win to loose ratio.
The advantage of a prediction strategy is the good R/R ratio.

A mixed strategy tries to combine both.

New dimensions in the trend following philosophy

I personally think that the old school of technical analysis is unproductive in today Forex markets.

The only thing that remains valid is the trendiness. The markets looks similar but it isn't.

In order to use the power of the trend a mechanical and algorithmic system is necessary. It is necessary to have mechanical signals for a trend following strategy. And those signals need to be back tested.

This is not new and a lot of systems work on that basis. What is difficult is to be in the trend and to spot a trend as early as possible.

A recent idea is to use the fractal dimension as a market sentiment indicator. Classically it is used the ADX. But the ADX gives us just a measure of the actual state of the market. It does not see the future in the forex market or whatever market.

The fractal dimension indicators give us probabilities and how they change. This approach is new in the domain of the market following methodology. And we have to use it at its full extent.

We have an experimental system that tries to do that. You can download it from this blog:

http://microhedgefund.blogspot.com/