If you trade liquid stocks or futures contracts, the first thing you will notice about equity options trading is that the contracts are illiquid and the bid/ask spread is wide. This sucks, but it makes perfect sense. There is only one AAPL stock to trade, but there are a ton of different options contracts trading …
Here’s a thing that I suspect will make money, but that I haven’t yet tested (for reasons that I will explain shortly): Every day, at the start of the trading day, get the SPX straddle price and convert it to an expected SPX price move. Then at the end of the trading day, take the …
Navigating Tradeoffs with Convex Optimisation This is the final article in our recent stat arb series. The previous articles are linked below: A short take on stat arb trading in the real world A general approach for exploiting stat arb alphas Ideas for crypto stat arb features Quantifying and combining crypto alphas A simple and …
This article continues our recent stat arb series. The previous articles are linked below: A short take on stat arb trading in the real world A general approach for exploiting stat arb alphas Ideas for crypto stat arb features Quantifying and combining crypto alphas A simple and effective way to manage turnover and not get …
Modeling features as expected returns can be a useful way to develop trading strategies, but it requires some care. The main advantage is that it directly aligns with the objective of predicting and capitalising on future returns. This can make optimisation and implementation more intuitive. It also facilitates direct comparison between features and provides a …
Every time we trade, we incur a cost. We pay a commission to the exchange or broker, we cross spreads, and we might even have market impact to contend with. A common issue in quant trading is to find an edge, only to discover that if you executed it naively, you’d get killed with costs. …
In this article, I’ll take some crypto stat arb features from our recent brainstorming article and show you how you might quantify their strength and decay characteristics and then combine them into a trading signal. This article continues our recent articles on stat arb: A short take on stat arb trading in the real world …
This article continues our recent articles on stat arb: In this article, I’ll brainstorm some ideas for predictive features that you could potentially use in a crypto stat arb model. The ideas draw insights from recent discussions and market observations, but of course, you should do your own research. In future articles, I’ll pick some …
Last week, I wrote a short article about statistical arbitrage trading in the real world. Statistical arbitrage is a well-understood concept: find pairs or baskets of assets you expect to move together, wait for them to diverge, and bet on them converging again. Simple enough. But making it work, especially at scale, is a little …
In textbooks, one often sees pairs trading algorithms start by regressing prices of Asset A on Asset B to calculate a hedge ratio. I’ve rarely seen anyone actually do this in the real world. That’s because it is a very unstable thing – especially for a pair of volatile assets, and especially over a large …
