This is the fourth part of our Market Frameworks series. The topics discussed below build on the foundations from our Reflexivity, Liquidity Cascades, and Inelastic Markets reports. If you haven’t already, we highly recommend checking them out, as they’ll give you the background understanding and philosophical underpinnings behind many of the concepts and methodologies applied to financial markets throughout this report. Enjoy!

Introduction

When playing a new game, the first thing people usually do is learn the rules and game mechanics. Sometimes there are very few rules and the mechanics are simple. Other times, the game is more dynamic, accompanied by more complex rules and mechanics. Certain games even have different rulesets for different players. Sometimes the rules change as the game progresses. In other words, it is nearly impossible to expect a positive outcome from the game if you aren’t aware of the rules and mechanics governing it.

Choose your favorite example, and you will likely agree with the previous statement; one of my favorites is Settlers of Catan. If you are unaware that rolling a 7 has the potential consequence of “halvening” (heh) your resource pile, you are going to have a bad time. Ditto if you are unaware of the existence of trading ports or development cards.

Financial markets are nothing more than one of the most dynamic games in existence, with the smartest and most well capitalized players in the world participating. However, if we look at crypto markets over the last 12 months, it has become clear that the most well capitalized players are hardly the smartest.

There are many types of financial markets, none of which are exactly the same. Each one is governed (has rulesets) by external factors. These rulesets vary across markets (think equities, bonds, crypto, etc.). Within each market, there are many different types of players (think “retail/uninformed” players, or “professional/sophisticated” players like money managers, banks, hedge funds, market makers, pension funds, etc.). Perhaps the biggest players of all are Central Banks, a relatively new active-market phenomenon. These players also have rulesets, dictating how and when they can interact with the market (think investment/trading mandates, rebalancing requirements, size restrictions, compliance & regulatory processes, etc.).

Unsurprisingly, there are different rulesets for each type of player in the market (think about how the parameters that govern retail and institutional players differ). Even the way in which price changes within a financial market also has specific rules, irrespective of the players interacting within it (consider a prevailing theory like the efficient market hypothesis, or an alternative view in the inelastic market hypothesis).

Having a conceptual framework and understanding of the financial market game, the different players and rulesets involved, and a way of fitting these moving pieces together is paramount when trying to survive and thrive in markets.

Part one of this report series, Reflexivity & the Fall of the Efficient Market Hypothesis, focused on developing a high-level conceptual framework for how markets generally function, along with the high-level relationships at play between market participants. Part two of this series, Liquidity Cascades & the Evolution of Financial Markets, focused on understanding how financial markets have evolved over time and how these evolutions have created inevitable market dynamics. Part three of this series, Volatility, Order Flow, & the Inelastic Market Hypothesis, focused on understanding the processes and ways in which prices actually change from one moment to the next and why data suggests it is due to order flow and not fundamental changes in value. This fourth report aims to provide readers with an understanding of how one may begin to parlay these concepts into direct financial market applications.

Setting Expectations

I was quick to come to the realization that if you want to extract some kind of edge from the market, you either have to be faster (doubt), smarter (doubt), or use information that others may not be using and look to compete in places and ways where others cannot (bingo). Another way of thinking about it: you should try to look at things that others are not, and you should likely avoid doing things that the majority of people are doing.

For argument’s sake (why else would you be here?), if we are to accept the findings from each of the previous reports, the next question is straightforward. What are the practical applications of these concepts and findings? For example, how can participants take advantage of an inelastic market view and phenomena such as liquidity cascades that are seemingly recurring features within modern financial markets?

If markets are reflexive and inelastic in nature, and if order flow mechanics are the determining factor in what drives price movements from moment to moment, it stands to reason that the most useful data is the order flow data itself.

The idea is to introduce an alternative w