Introduction

I wanted to write something for the forum – actually I wanted to use the forum members for a sounding board to see where I need to tighten up the text or explain things better before I use it somewhere else. It might appear as an article somewhere, or if I can finagle a sabbatical I might write a book with it.

You’ll note this isn’t in the beginner’s section, but I don’t mind beginners looking at it and commenting. I’m hoping that some of the experienced characters around here who get what I am talking about might like to challenge, add to or otherwise comment. I’m not sure how much time I will have to answer questions in this thread but will do my best. What I’m hoping to share with you is an extended epiphany that I had a few years ago in relation to the market, which has governed my investment styles since that time.

A word of warning however… this is going to get complex pretty damn quick before it gets easier and before you get to the piece I write on application I’d like you to understand the concepts I’ve spoken about around economic cycles. That information will be a useful starting point before I get to the really meaty stuff. If you haven’t read my newbie thread and the section on economic cycles you can find it in my signature.

Finally I will be breaking this into several parts, because the amount of time I can devote to this is not exhaustive and will write it a piece at a time, when I can – expect long delays. I’ll be pausing for flames, na-uhs, grammer nazis (see what I did there ), the peanut gallery and anyone that wants to contribute after each part and really hope to stimulate some interesting discussion. My thanks to Joe who agreed to put a sticky on this as well.

The Markets are Chaotic – Part I

The older I get the more I realize exactly how chaotic the financial markets are, not because we are currently experiencing some volatility in world markets; more because of what kind of behaviour it exhibits both in macro and aggregate scales as well as micro and individual scales. Behaviour that is unmistakablychaotic, if you know what to look for. The fact that you can see it across both large and small applications is one of the signs that indeed the market corresponds to chaotic principles. Hopefully you will join me on this journey of discovery and by the time we get to the end of this, you’ll know three important things, what chaos means for the market, why I applied it to the way I invest personally and how you can apply it as well.

Chaos doesn’t mean what you might think. When I talk to a lot of my peers in the financial services industry, their eye’s glaze over because chaos is a fundamentally different field of mathematics than what they learnt to become financial planners or stockbrokers or accountants or analysts or whatever. When you become a financial adviser you learn to read boring maths really well…balance sheets, profit and loss, cash flow statements, things like that. I’m not saying that you don’t need to know those things, because it’s important for every financial adviser to understand the drivers and influencers behind a good business as opposed to bad one.

A good financial adviser might also learn some probability and how to apply it, standard deviation, variance, that sort of thing. Ultimately however this kind of math hasn’t progressed beyond Newtonian math, which is fundamentally flawed when dealing with chaos. It’s important to still know these things though because good fundamental analysis ultimately operates inside of a framework that is governed by chaos. I know that might be a challenging statement for some, but economics doesn’t exist independently of chaos. It’s not “special” and magically separate; chaos (and the corresponding order that emerges from it) permeateseverything.

The kind of math associated with fundamental analysis however does tend to make the mind think in terms of duality. Profit and loss, assets and liabilities, top-down, bottom-up, things like this tend to train the mind that the market is very two dimensional in nature. Most advisers unconsciously realise that there are multiple dimensions, our relationships to markets independent of our own for example, with varying degrees of correlation, but then always seem to flounder and for some reason say it’s “just economics”, and economics my friends is very firmly rooted inNewtonianmath.

Just what the hell is Newtonian math?

Sir Isaac Newton’s development of calculus and the laws of classical mechanics began in the 17th century, where it became accepted dogma. It gave scientists and mathematicians tools to determine the dynamics of bodies by simple equations. How great was that! If you only knew what the simple equation was that governed a particular action, if you knew the starting position or initial set of circumstances, you couldpredict the future. Newtonian math was massively useful in all manner of mechanical applications. This is the math that spawned the industrial revolution. With this math you could design a machine and know that it would endlessly replicate the same action in a repeatable and predictable way.

Newtonian math evolved the concept of Determinism, namely the belief that the past completely determines the future. Problems arose for the Determinists towards the end of the 1800’s when some very difficult equations (non-linear differentials) proved impossible to solve with Newtonian Math and a whole new branch of mathematics emerged, which would ultimately become what we know of today as Chaos.

Can you see where I am going with this? As investors into the financial markets we attempt topredict the futureevery day, based on some simple equations that try and identify the dynamics of the market. These equations might be fundamentally orientated; that X share, after subjecting it to a myriad of financial modelling has an intrinsic value of $ and is therefore cheap or expensive. We then take a position based on our calculated intrinsic value and attempt topredict the future. If we are technical analysts, we use things like Standard Deviation, Moving Averages, Oscillators and Volume and attempt to use the past price and volume data topredict the future.

We might do this with varying degrees of success, depending upon how much money we have, what the equations we use are; what risk minimisation techniques we use, what positional sizing we employ and how carefully we conduct our money management. Every so often however, chaos comes along and kicks our carefully constructed sandcastle of equations and strategies in our face, and we are left trying to pick up the pieces and wonder what we did wrong, why didn’t it work? It’s as if the machine threw a cog and what was once almost certain, becomes undeniably uncertain, because of one of the fundamental principles behind chaos.

We go searching for more data, we seek to validate our strategies with extensive testing and modelling and say things like "It's not statistically relevent until you've done it a few thousand times and come up with a positive result". We argue, we sometimes share what works with others, and keep closely guarded secrets close to our chests.

Good traders and investors learn to shrug chaos off, they say things like “It doesn’t matter if you are wrong, just how long you stay wrong for.” Or “The market can stay irrational longer than you can stay solvent”. If they have protected their investments in the armour of money management, positional sizing models, trailing stop losses and the like these knights can take a hit and keep on moving through the chaos of constant battle in the quest for alpha returns.

These traders simply deal with chaos by acknowledging that it exists, that they cannot do anything about it beyond taking it on the armoured chin and moving on to the next opportunity to test their mettle in battle. What if I told you however that there are ways to make chaos workfor yourather thanagainst you. That chaos has principles and that if you are aware of what these principles are and how you can apply them to your personal trading you can use them to add another layer of armour.

Part II – Principles of chaos – coming soon

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