Investors are not traders. Investors focus on the capital return potential of assets, adjusted for a discount rate. Traders focus on capturing the movement of assets. An investor may trade, to swap into a more appealing capital return or asset. But a trader would rarely invest - as that would suppose capital returns made up a higher percentage of an asset’s return profile than its movement. This is seldom the case. For example, the S&P 500 routinely moves more in 1 day than its annual dividend payment.
The concepts that define investing are relatively well known and widely discussed. At their core, an investment analyst seeks to answer the question, “Is this an asset I would be happy to own for a long time, or until maturity?” This essentially boils down to comparing valuation relative to growth, business quality and industry/ country risk. Due to long hold periods, investors are more likely to concern themselves with the day to day affairs of the businesses they own - in the extreme case (Berkshire Hathaway), taking them private, owning them outright or operating them.
I am writing this because while trading is ‘widely discussed’, it is done so in disjointed contexts unlikely to generate a return
There are two types of trading. I will use the terms common in regulatory frameworks - market making, and proprietary trading. Market makers focus on providing liquidity to traders or investors and get paid the bid-offer for doing so. Most market makers have extremely low hold times - micro-seconds in the case of equities - but longer in less liquid assets such as over the counter fixed income.
Like investing, market making is widely discussed. Calling it formulaic would be insulting to its practitioners. There is much art to successful execution, including procuring data that may provide an edge (payment for order flow being an example) and often impressive math involved hedging exposures in real time. The coding acumen and technical expertise to implement millions of small orders a day and reduce risk in near real time similarly merits much discussion. At its core however - a market maker aims to provide the market with the lowest spread possible, as many times as possible, without getting “run over” (which basically means trading against someone who likely has better information than you do).
I am not a market maker and only described it to differentiate it from proprietary trading (what I do). I am sure my description was insufficient, or even partially inaccurate - so take it with a grain of salt.
Thus - to summarize, what I will now describe is neither market making, nor investing, but rather something in between. It could be called “prop trading” but I prefer to call it short term speculating. I will simply call it “speculating” and myself a “speculator”.
At its core, speculators attempt to predict asset movements, take positions before they happen and sell shortly after a set of conditions are met. Investors focus on terminal value. Market makers focus on providing liquidity. Speculators focus on taking liquidity.
Because speculators frequently cross bid-ask spreads, this means a speculator must transact much less frequently than a market maker.
If a speculator’s job is to predict short term asset movements, then the study of asset movements is an important part of the job. Assets move for four major reasons that are useful to a speculator.
First - a repeated, price insensitive buyer such as a corporate hedger, passive index, central bank, is transacting in a particular way. I call the study of these price insensitive buyer “Flows.” Flows happen on a daily basis, but their nature depends heavily on the mechanisms of the actor. Indexes have a rebalance calendar, for example - that might determine a “flow”.
Second - an asset will release important news relevant to its fundamentals. This is typically an earnings release or an investor day for a stock, or a data release for a currency. The work done to prepare for such events I term “Pre Catalyst. An asset will typically begin adjusting or moving in anticipation of a catalyst approximately 14 days before an event.
Third - the gap after an event described as the catalyst, requires both an immediate fast movement and a subsequent realignment. I call the rapid response to an event and readjustment “Post Catalyst”. Assets adjust rapidly within minutes or seconds of most catalysts, but the subsequent readjustment after an event frequently takes a full 72 hours.
Fourth - while flows and catalysts could exist without problem in a single economy - their existence across global markets becomes messy. Central banks and global indices fail to coordinate, or even come into conflict. A catalyst for a company in one country can drive its central bank to bail it out - which might affect a company in another country where the central bank cannot intervene legally. Because these asymmetries take a long time to rectify, they create useful trends and dislocations. This is the basis for the fourth type of trading I call “Macro”.
So far I have only described fundamental trading. Everything described so far is best put as an “equilibrium condition”. In a normal economy - corporates will hedge, indices will rebalance, central banks will act in particular ways to respond to these things which will cause occasional trends and imbalances that can be “harvested” by speculators. These gentle flows will be punctuated by occasional violent readjustments triggered by catalysts. But for the most part, the violence is “expected” because it happens at pre-ordained times such as Non Farm payrolls.
The term fundamental trading implies the existence of “non fundamental trading”.
Non fundamental trading arises when the system described above enters ‘disequilibrium’. “Bubbles” are the most common type of non fundamental trading - and typically arise when a regulator or well capitalized entity does something extreme that creates a “free lunch” for market participants. George Soros famously posited that bubbles and ‘far from equilibrium’ situations are innate to capital markets because people A] believe markets are a natural system B] markets are not a natural system because they are comprised of the beliefs of their participants which change in response to the market itself. C] regulators cannot properly account for A and B so operate in a perpetual state of pretending their own presence is part of the natural system, when, in fact - their perennial bailouts happen because the system fails.
There are two types of non fundamental trading - non fundamental macro trading – betting on the formation, and collapse of bubbles, and non fundamental flow trading – betting on stampede behavior of irrational investors (typically retail, typically using leverage).
Thus there are six basic market regimes - four which happen when the market is in equilibrium (flows, pre catalyst, post catalyst, and macro) and two when the market is in disequilibrium (non fundamental flows, non fundamental macro).
You will note that catalysts are absent in disequilibrium states. One useful definition of the market being in disequilibrium condition is when the variance of day to day random moves dwarves the moves when there is a catalyst for an asset. For example, before AMC was a meme stock, it had larger moves during its earnings releases. After it became a meme stock, it realized large moves for little to no reason at all.
Some assets are in a perpetual state of disequilibrium by their very nature. A non controversial example might be Dogecoin - which is quite literally a joke currency with no scaling plan and no terminal value. A more controversial example would be Gold - which has monetary value due to being a perceived alternative to an existing system (that is to say, Gold is almost entirely a belief driven asset).
Most assets fluctuate between states of equilibrium and disequilibrium.
This concludes the description of the market which opens the way for a description of what exactly a speculator does. I believe this is composed of 8 essential parts.
First - quantify flows that repeat, using data, analysis and quantitative due diligence. Map non price sensitive actors to anomalies. Create hypotheses for why flows might recur. Build systems that isolate exposure to flows, and conduct experiments out of sample to assess their repeatability.
Second - preview catalysts before they happen. This boils down to identifying low expectations, low valuation, and high “carry” (i.e. capital returns) disconnected from surprising business success as measured by data, superior knowledge / context, or competitive analysis. Then structuring and placing trades with appealing risk reward (high possibility of a payout and low worst case scenario).
Third - respond and trade post (after) the catalyst. This involves quantifying, in advance the likely trajectory of assets after a data or earnings release. This can be wide scale and systematic, or specific. Typically speculators will need a more nuanced view how to respond “post” catalyst if they have a large position “pre” catalyst.
Fourth - combine all of the above, combined with relevant sovereign indicators (such as interest rates, currency valuation, equity performance, economic performance, central bank commentary) to identify asymmetries in global foreign exchange, interest rate and commodity markets. This is well understood and called “macro” investing. It is worth noting that flows, pre catalyst, and post catalyst trading can be performed on macro instruments such as EURUSD, but macro trading focuses more on fundamental trends likely to persist or that can be expressed asymmetrically due to the impossibility of coordinating global monetary and fiscal policy.
Fifth - identify repeated price movements that exist outside fundamental flows, pre-catalyst, post catalyst and macro trading. Typically this will involve herd behavior, short squeezes, stampedes and retail trading driven nonsense. Yes, this includes internet memes. One way to think about this is that people are treating the markets like an online store. You are measuring an e-commerce checkout pattern and trading accordingly. This can be termed, detecting “non fundamental flows”
Sixth - Combine 1-5 with external data, market analysis, and regulator action to identify the presence of a “free lunch” or something that is likely to get completely out of hand. Create a hypothesis about how it will get out of hand, writing in advance why and what conditions it will likely go wrong, and bet on a bubble forming. This type of trading is the highest form of speculation, and at times can risk the very existence of markets themselves when speculators stampede over governments or central banks. This is called “non fundamental macro”. It is worth noting that non fundamental macro trading requires a high degree of hubris and perhaps is not best attempted by those not strongly executing on the first 5 pillars.
Seventh - Quantify the 6 potential sources of PNL. Manage risk at each strategy level. Only the macro strategy should have net market exposures in stocks, bonds, gold, oil or factors. If you do not have a quantified, and tracked view - do not have an exposure. Track performance over time and build robust systems to do so.
Eighth - allocate capital to the 6 potential sources of PNL, and allocate time, resources and personnel according to expected value at risk
This comprises the job of a speculator in a way that originates from the definition of speculation itself - the study of why assets move. Flows go into them day to day, when they’re not jumping about on catalysts. Sometimes bubbles come into play and all rules are thrown out the window.
Parting thought ½ : I wrote this partly out of annoyance at existing classifications of speculation. Short term speculation is studying and profiting from asset movement, as discussed definitionally - crossing spreads with the intention of gain. Long/Short equities, Macro, Quant, Merger Arb, etc - are sloppy categorizations because they do not - in their very essence, come from asset movement - but rather come from asset definition - which is arbitrary. Discourse on short term speculation also drifts with annoying frequency into market making - when they are in some ways opposites (taking vs providing liquidity)
Parting thought 2/2 : the idea of a “quant fund” while somewhat descriptive in the age of machine learning and “AI” is useful, but dangerous. In the framework above, Flows and Post Catalyst trading are innately more quantitative - and can even be reduced into machine learning or AI based strategies. In fact - with enough external data (imagine a full exhaust of Twitter or Google) - it might be possible to turn all of the above into “quant” strategies. But the core pillars, I’d argue - regardless of whether a human or machine implements them - come from first principles of how assets move. Also - the decision to allocate capital to something, and to turn a quant strategy on or off will likely (for better or worse) be made by a person. Or perhaps this is just the coping of an analyst who does not code well enough
This comprises my understanding of speculation. If I fail in my speculation, this diatribe will be easily discarded. If I succeed perhaps it will be of interest in the future - but from this perspective is best stated in advance. Pre-catalyst, if you will. Fin.