Don't Trade Before Reading This

Malt Liquidity 71

Checkers, not Chess

A common misconception surrounding trading is that to trade, you have to be some sort of god quant and/or 10x programmer. While those skills obviously have high utility and are worth learning if you’re capable, that isn’t the focus of this post. Instead, I want to focus on the methodology and philosophy behind how to generate ideas intuitively.

Of course, building up a knowledge base is required. Understanding the market’s structure, its general participants, and their intentions is a prerequisite. I’ve flogged enough people with this recommendation, but for those of you who have yet to receive it, I find Trading & Exchanges to be the best resource to bring yourself up to speed. Just as important is understanding the products in the market — how they move, what role they play, and how they relate to other products in the system. If you want to trade options, you’d better have some understanding of how derivatives work and how they move relative to the underlying. Otherwise, you might as well be playing poker without knowing the hand ranks.

The next step is to understand what a good trade consists of. Buying a stock and waiting for it to go up is not trading, nor is entering a position because some form of a moving average told you to. A good trade has two components — positive expectancy and managed risk. A cursory understanding of expected value and optimal bet sizing is enough here. That’s all the math we’ll need on a high level — modeling or calculating anything precisely won’t be necessary here.

The last essential requirement is understanding yourself. How much can you risk while being able to keep your head straight? What size bankroll are you planning on trading with? As we will see later, sizing can be one of the most efficient tools to generate returns, or a massive hindrance. Once these requirements are taken care of (though your knowledge base should always be growing, ideally), we can start to think about where we fit in.

Poker has a deep lore in the trading world, and it’s a pretty good simplification of the mindset we’ll want to have as we start to look for opportunities. Poker has an alpha problem. To consistently win, you need to out-skill other players over the long run. At first, you can do this by upping your knowledge and cleaning your execution of game theory optimal strategy. Over time, though, your ability to improve hits a hard cap — there is only so much optimization around chance that you can do — and the median ability of the overall playerbase starts to catch up. The players around you are getting better and better, and your edge is fading. This happens to any game where an optimal theory develops and spreads in the information age — in Magic the Gathering, the best players barely break 60% win-rates as the skill level goes up, as there is a cap on how efficiently one can play and they’re all hitting it. The only way for MtG players to increase their win-rate would be to play worse players. Now, they probably don’t do that because it kills the fun — like how playing chess with 99% of you guys is no fun at all for me — but poker has a profit incentive that its alpha comes with. The edge is much slimmer in pushing your skill further than in selecting the proper game with whales instead of sharks. I am in no way an optimal poker player, but the power of picking the proper venue to seek edge is a powerful concept to retain.

The type of venue I’m thinking about in the stock market is not Wall Street or the New York Stock Exchange, or even specific indices or stocks. The dizzying array of options across stocks that make up ETFs that track tradable indices whose volatility composes non-tradable indices that make up ETPs provide us with an enormous amount of venues in the form of every single order book for every single strike or stock. Each order book retains characteristics — let’s call them liquidity profiles — that market participants who wish to transact in them have to take into account. Here’s where size comes into play — the market participants with the most size are going to shy away from the less liquid order books, or at least disguise and mete out their flow into them. They’re going to seek the deepest areas of the market to transact in — as opposed to poker, you want to stay out of the way of whales in the markets. The most sophisticated players will aggregate around ES futures, AAPL stock, and other robust, highly liquid instruments as they try and take each-other out. While there are still ways to trade these products profitably in our smaller size, it’s like being plankton drifting along with the current, where you can find yourself blown out and sucked up into a whale’s mouth in the blink of an eye. However, size does transact out of the depths of liquid books, and when it does, it tends to be a little clunky. The liquidity profile of, say, stock #393 in the S&P 500 is nowhere near what #2 is. If, with our small size, we can bite off a sliver of the liquidity they will demand and flip it back to them, well, that’s a pretty good trade, isn’t it? It’s a very simple start to building up a trading strategy — find the places where the size impacts the book, piggyback in front of it, and ride off their market impact in the direction you want to go.

Obviously, once you start to have an idea, you do have to start getting into the weeds a bit and figure out how you’ll implement and execute and account for the risks you’ll be taking. But we’ve taken our tools — our smaller, easily-executable trade size and risk profile — and found a potentially better venue to take it to, solely out of looking at market participants and the products they might transact in. And in fact, one of the earliest option strategies I came up with fell along these lines. I’d go look for relatively wide spreads that were seeing some volume, and try and walk the book in on either side, while avoiding the midpoint. If I got a fill, that’s a bit of edge in and of itself, and I’d try and work the fill alongside price movement across the book to get out. It was LFT — shitty, unhedged low frequency trading. Obviously, it was a little more refined, but I’ll spare the details to recount over a drink. (Note: I did this in markets that at the time were categorized by VIX being taken behind a shed and blasted with a shotgun for months at a time. DO NOT DO THIS in stocks realizing actual vol.)

Once the idea is crystallized, we want to look at what will make it not work. The obvious risk in our example above is adverse price movement, including gap risk. I still remember walking the book up and down on illiquid KC futures at 4:30 in the morning out of boredom and getting caught long as the price cratered out of nowhere. If two lots pushes the price up and down when nothing is happening, when someone actually needs to trade… well, shit’s gonna get hit. And no, stops don’t mitigate gap risk. The way stops are talked about by retail trading “gurus” is like how Russell Wilson talks about water that cures concussions. “Percentage thresholds” for stops are overwhelmingly used arbitrarily, and a stop loss that triggers when the price gaps through turns into a market order, which almost certainly won’t fill at anywhere near the price you wanted to. A stop limit that gets gapped through probably won’t even transact and you’ll be stuck with your position anyway. And, as a rule of thumb, unless you’re iceberging an order wayyyy down in the book, don’t leave resting orders as a fail-safe stop on a thin book. It’s just begging to get eaten up, and you’ll find yourself flat, having realized a loss for no real reason while the price rebounds to where it was just at. So, we need some sort of contingency plan — a method of execution to get out when things are going awry. This is a good time to check if your trading idea is even worth it by estimating expectancy. If you’re going to cap your gains at some low multiple of the spread but let your losers nosedive to yo-yo so they can potentially rebound, it’s probably not looking that good. Furthermore, here’s where size can become a tricky issue — if your trading capital is too small, even a few blown trades can cause a real risk of ruin.

The other primary concern is also execution related — what is the most size I can take on and still be able to exit relatively seamlessly? What is the general order size this order book supports? The last thing you want to do is to own too large of a chunk of the OI and find that you can’t exit any of your position without crossing the very spread we hoped to profit from, if it’s even possible to. And depending on how wide the option is, you might have to break up your orders into chunks. Remember, showing relative size — a demand for liquidity that exceeds what the book is providing — is going to bring other edge traders in to demand that you pay up for exit liquidity, or move the book even further away from you and cost you some of whatever you have made.

Once we have concrete thoughts on all these elements — an idea, a venue, ideal execution, loss mitigation execution, rough expectancy, and potential scale — and it’s still looking like it might be worth your time, well, it’s time to start testing. Might be time to slide into that quant or 10xer’s DMs. Ah, fuck it — we’ll do it live.