Your job, as a trader, is to take all the information we have available now and make a judgment on whether something is trading at the right price or not, given things you can know here: Is it the wrong price? Can we buy it too cheap, or sell it too rich? Let’s say we …
Lately, I’ve been thinking a lot about the Volatility Risk Premium (VRP). The VRP makes much more sense (to me, at least) when I have the Equity Risk Premium (ERP) for context and comparison. So, in this article, I want to discuss the ERP and the VRP, their similarities and differences, and how I seek …
I want to discuss a couple of simple trade-off considerations around quant trading signals that may not be obvious. Here’s the price of some asset: Our main job is to predict how it’s likely to move. To do this, you use information about it that you think is predictive. And at any point in time: …
If you try to teach yourself quant trading from the internet or from scientific papers, you run the risk of spending a lot of time majoring on minor stuff. You see it on Twitter all the time. Well-meaning beginner kwants are spending time worrying about niche modelling or inference techniques rather than trying to understand …
In 2021, James, I, and a small team decided to set up a crypto trading venture. We faced several problems, but knowing almost nothing about crypto was the most significant. We sensed that the fractured, developing nature of the crypto market would likely be a good place to seek out inefficiencies, but beyond that, we …
When you do anything with data, you should think about the intuition of each thing you do, and what it represents “in the real world”. Let’s take the example of log returns, which some people tell me they find confusing. Consider an asset whose price goes from $100 to $200 Assume there are no other cash …
Alpha isn’t just about finding people willing to trade at bad prices. Although that’s a necessary condition, it’s not enough. We also need to know why people are willing to buy too expensive or sell too cheap. The reasons are pretty simple: The first reason requires the existence of other uninformed traders, or what some …
Towards the end of last year, we ran a couple of free Zoom webinars on: Here are the recordings: Basics of Edge Extraction Data analysis for Traders The colab research notebook for the second session can be found here. (To make sense of it you’ll want to watch the video.)
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 …
Many beginner traders don’t realize how variable the p&l of a high-performing trading strategy really is. Here’s an example… I simulated ten different 5 year GBM processes with expected annual returns of 20% and annualized volatility of 10%. (If you speak Sharpe Ratios, I’m simulating a strategy within known Sharpe 2 characteristics.) I plotted the …
