In Australia, if you’re serious about getting the job done effectively and efficiently, you might say: “I’m not here to f*** spiders.”
Many traders act like they are, indeed, here to f*** spiders.
If you’re making soup, you first need a good stock. Stock isn’t exciting. Everyone has stock. Garnish is exciting, but you can’t make soup from just garnish.
Similarly, you need some stock in your trading portfolio. You need at least one reliable, stonkingly obvious way to get paid.
Here’s a non-soup analogy. If you start a business venture, it’s clear that you need an obvious, reliable way to make money. You wouldn’t just try to blag it. “I am smart and hard-working” is not a business case. You need a stonkingly obvious way to get paid.
Drawing lines on a chart and hoping you can figure out when to buy and sell is not a stonkingly obvious way to get paid. You’re putting a huge amount of confidence in your discretion and skill there. It’s a lousy business case. I wouldn’t lend you money to do that.
Throwing features into a machine learning algorithm and hoping it can figure out when to buy and sell is a similarly lousy business case. There’s no reason to think that would work. Why would you expect to get paid for that? I wouldn’t lend you money to do that either.
So what IS a stonkingly obvious edge?
We’ll go through some examples. First, we’ll start with things you almost certainly can’t do, because they illustrate some important points I want to make. Then we’ll look at similar stuff that you actually can do.
Some Exchange Traded Funds (ETFs) appear to be rather illiquid. They don’t trade that much and their order books are thin. But if you put in a limit order at a good price for a large number of shares, you often get filled quickly. Why?
Because some traders (called APs) can assemble new ETF shares for you out of bits of the assets the fund holds, and then sell those new shares to you. This is a useful thing for you.
Due to this, you can buy the ETF for a good price without having to buy all the bits.
The trader makes money if she can buy the bits for cheaper than she can sell you ETF shares she made from those bits. This is a familiar business model. The trader provides something useful, takes on some inventory risk, and gets paid if they are running things well.
It works the other way around too. The same trader can buy the ETF shares off you, disassemble them, and sell the bits on the market. She makes money if she can sell the bits for more than she paid you for the ETF shares.
You can’t do this (you’re not an AP), so why am I telling you this?
Because it is a great example of a stonkingly obvious edge you can build a business case around. You get paid for:
- providing a useful service (liquidity at good prices for ETF shares)
- taking on risk
- doing the work well
What other things look like this?
Market making looks like this too. Market makers provide a useful service: giving traders the ability to instantly buy or sell an asset at good prices.
In doing that, they take on some risk: they accumulate inventory and tend to be on the wrong side of big moves. If he does the work well, the MM manages these risks and makes some of the bid/ask spread on each trade, on average.
As before, the MM gets paid for:
- providing a useful service (immediate trading)
- taking on risk (inventory risk)
- doing the work well
Commodity Futures carry (with a time machine)
If you jumped in a time machine and went back to the 1980s, you might notice that commodity futures tended to trade significantly cheaper than the spot value of the commodity itself.
This was because the commodity futures market was dominated by producers looking to hedge against lower prices. Commodity producers were selling futures contracts to lock in guaranteed future prices.
But a futures contract needs a buyer and a seller. Who was buying?
Traders. Traders realised that they could take the other side of these flows at a discounted price (they were less desperate to trade.) The excess “supply” of futures contracts from commodity producers’ hedging created “demand” from traders exploiting the imbalance.
It might not seem that way at first, but traders were providing a useful service to the producers. They provided them with someone to trade with – and the demand from these traders competing for the opportunity resulted in better prices for the producers’ hedges.
So there was a stonkingly obvious opportunity here for traders to take the other side of hedging flows. This was exploited by:
- commodity carry trading
- securitization of commodity futures into wealth management products (ultimately killing the trade in the mid 2000s)
The business case for the trade was the same as before. Traders fading these flows were:
- providing a useful service (liquidity to hedgers)
- taking on a bit of risk (M2M risk)
- doing the work well (systematic rules, risk management)
A Recent Example – Crypto
Here’s a similar and bang-up-to-date example from the cryptocurrency markets.
The FOMO demand for leveraged long exposure to crypto is enormous.
Massive demand from relatively price-insensitive bullish traders has resulted in BTC futures trading far above the spot price. This is the opposite situation to commodity futures in the 1980s.
There’s a stonkingly obvious edge here. You take the other side. You sell BTC futures to the rampant YOLO trader demand, and you hedge your directional exposure by buying an equivalent amount of spot BTC.
The business case for this looks reasonable:
- providing a useful service (YOLO traders need someone to trade with)
- taking on risk (basis risk, blow up risk)
- doing it well (hedging, smart margin management because you can’t collateralise short futures with the long spot leg)
Risk Premia Harvesting
A classic stonkingly obvious high probability edge that nearly everyone should harness is Risk Premia Harvesting.
Assets that are sensitive to certain risks are unattractive compared to those that are not.
This means simply being the person prepared to hold these assets is a useful service. It’s a win-win situation where:
- you, as a person prepared to take the risk, get paid in excess returns (higher yield)
- the risk-averse person is happy to hold less risky stuff instead
This thread presented a very simple risk premia harvesting strategy.
This stonkingly obvious edge has provided a tailwind to macro traders (“spoos and blues”) and wealth management for decades. And it’s not too good for you either.
As with the other examples, the business case stacks up. Returns come from:
- providing a useful service (demand for risky assets)
- taking on risk (inflation, real rates, credit, growth, etc)
- doing it well (manage risk, sit on hands, don’t chase returns)
If you’re serious about making money trading you need some stuff you can really rely on. You need at least one stonkingly obvious business cases that stacks up. Otherwise, you’re just LARPing around. To make soup, you first make stock. Garnish is last.
So put away your vanity projects and get serious about this first. You get paid for:
- providing a useful service (often providing liquidity to more desperate or constrained traders)
- taking on risk (otherwise everyone would do it)
- good implementation
Don’t be a hero. You want good solid business cases: obvious things that it is reasonable to think someone would pay you for.