A Theory of Market Action: Part I

[madspeculator 10]

Introduction

 

Every trader reaches a point when he strives to improve upon his trading – the unsuccessful in order to make money, the successful in order to improve their bottom-line, and the “were-successful” in order to start making money again.

 

It is at this time a fundamental question is raised: “Why is the market doing what it is doing?”

 

Although this question comes in different forms (“I wish I knew what was going on in the market at this point”), the underlying theme is the same: The quest to understand market internals.

 

A section of the trading population tries to avert this question by taking the so-called “self-analysis” route. Although self-analysis can be useful for the growth of a trader, such an approach in-by-itself, without a good understanding of the market internals, is almost useless; invariably, they will end-up in the other camp.

 

Within the other section of the trading population, some quit, while some resort to research to develop a better trading model. This article is targeted towards those who resort to research to improve their trading.

 

Peter Drucker, the famed management consultant, once wrote that there were two kinds of books from which knowledge can be gleaned: the what-to book, and the how-to book. Within the context of trading, the how-to book would teach one how to trade. This site has a number of good posts on that subject (e.g., JPerl’s posts on trading with market statistics); this post is not one of them. This post is about the what-to – what should one do in order to understand the market internals?

 

Need for a theory of market

 

The quest to understand market internals cannot start without a theory.

 

The problem with developing a trading system without a supporting theory is that such systems will stop working when the “market conditions change”. A good theory of market action should be able to prediction such “market condition changes” (prediction not in terms of exactness – which no one can do – but as a way of market operation). Statistical model builders who do not have a market theory to back their models up are (or at the least, should be) keenly aware of this problem. [Arbitrage models also stop working at some point in time, but for a different reason: competition leads to efficiency. Such a theory is very well established in the finance literature, and is out of scope of this discussion]

 

A discretionary trader trying to develop a system cannot do so with out a theory; nor can a systematic trader. Once a “tradable pattern” is found, the type of validation performed to determine long term viability of such “tradable pattern” might be different between these trading groups, but the type of research performed is the same – one rooted in one’s understanding of the workings of the market. The expectation that computers can automatically mine meaningful patterns from complex financial time-series without human guidance is all but based on naivety. [The author is not interested in a debate on which type of trading is better: discretionary or systematic. People do what they do because they are comfortable with what they do.]

 

In no other field is a good theory more important that in the realm of trading. Unfortunately, this is the very field where a good theoretical underpinning required to conduct structured research is lacking. Without such theory, the sheer amount of data will overwhelm the researcher.

 

Survey of existing theories

 

According to Wikipedia:

 

A theory, in the scientific sense of the word, is an analytic structure designed to explain a set of empirical observations. A scientific theory does two things:

1. it identifies this set of distinct observations as a class of phenomena, and

2. makes assertions about the underlying reality that brings about or affects this class.

 

In other words, a theory not only describes an observable phenomenon but also provides means to measure it. Without proper measurement, a theory cannot be falsified – a prerequisite proposed by the great philosopher Popper. Theories that cannot be measured are hypotheses; hypotheses are not very valuable for traders.

 

It is not that the field of trading is devoid of theories; it has its own share of theories. However, most of them are really hypotheses. Of the few theories floating around, they either do not provide enough detail to further one’s understanding of the market or that they are simply invalid. So, our first order of business before delving into our own theory of market action is to survey the existing theories of market internals.

 

In the light of the above definition, some so-called theories (like the Dow theory – which doesn’t describe why price moves in waves, or fractal market hypothesis (note not a theory) which doesn’t provide means of measurement) will not be discussed in this section.

 

There are two theories that are worth mentioning:

 

1. Theory based on supply and demand (e.g. Wyckoff’s theory of market action); and

2. Theory based on value (e.g. auction market theory, market profile)

 

In the next post, which I hope to post sometime towards the early part of next week, we will conduct a quick survey of these two existing theories and their shortcomings.

[DugDug 10]

Well worth adding the Soros theory of Relexivity - "The Alchemy of finance"

Very topical in recent years - however while it is certainly not typical or used by day traders, some of the general ideas can be applied.

This will be a very interesting thread.

[natedredd10 10]

Theories that cannot be measured are hypotheses; hypotheses are not very valuable for traders.

 

How do you intend to measure these theories then though to have any confidence that they are simply not untestable hypotheses?

[madspeculator 10]

How do you intend to measure these theories then though to have any confidence that they are simply not untestable hypotheses?

 

My next post should provide the answer to your question.