Dirty Crypto Carry Part 3: The Money's in the Middle
Forward returns over equity curves, and what funding really tells you about price.
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Hey friends,
Over the past few articles, we have been working on this “dirty carry crypto trade (part 1 and part 2)”. The first model was inefficient because we didn’t care that much about the signal itself which made it turnover 100x+ of capital a year, which is A LOT for these sorts of models, and my intuition tells me that our signal isn’t that strong to be turned over so often.
That poses an interesting question, how really does the signal behave, and what other variations tell us about the signal?
Well, let’s look at it.
How should we think about a signal? To me, certainly not from the traditional online backtestoors perspective, where a signal is used merely as a rule to buy above or below, and hope for the equity curve to be heading towards the top right corner of the screen.
Backtests alone are prone to problems like path dependency and pure luck. But looking at what a signal on average should yield, well, that’s a better way of looking at it in my opinion.
This is a recent podcast I listened to, where liquiditygoblin touches on that topic for a bit, which I completely subscribe to – having a defined forecast horizon and sticking to it. It’s not just about did this backtest made money or not. It is about what does this signal yield in a forward looking period.
If you do a backtest of a random buy of the S&P500 and hold it for the next 10 days, it’d probably made money over the past decade, and no one would say that strategy has an edge right?
The idea of starting from a forward return perspective is having something that is expected to make money over a future horizon on average, and then decomposing it from known market returns (a topic for another day).
How can we define that horizon for ourselves?
Well in the last piece of these series we noticed how funding is so sticky in that first 5 day window, and so that should be our initial threshold.
Let’s begin there before we think about anything else. What’s the expected price movement in the first N days after the signal?
I want to reinforce the idea that this is PRICE MOVEMENT that we’re measuring. Why am I making that a point? Well, this is a carry trade, so we expect to get paid that carry, but there’s a whole directionality thing we have to solve for. If we go long BTC and short DOGE, these things don’t move together ALL the time, so we need to think carefully about that later on. Also we want to be measuring apples to apples right? So how do we define our forward return given that DOGE has a way differently volatility profile than say BTC?