FactorsQuant tradingThink like a trader
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:
DataRTools of the trade
Traders typically have many ideas for trading strategies – more than they can ever implement in practice! Therefore it’s useful to be able to move quickly in the early research phase. You want to disprove things as quickly as possible so that you can move onto the next thing. Obviously there is immense value in
Quant tradingThink like a traderTrading as a businessTrading strategies
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
Think like a trader
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
DataRTrading infrastructure
In this blog post, I will demonstrate how to work with stock price data using the DuckDB database management system in R. DuckDB is a fast and lightweight analytical database engine that is designed to work with various programming languages, including R. You can use Duck DB from the command line or from a client
Think like a traderTrading as a business
Independent traders don’t have the same resources, speed, or balance sheets as large institutions. But that doesn’t mean they can’t compete. The key is to avoid crowded battles and instead focus on niches where the playing field is uneven. Alpha, consistent trading profits above the market, comes from exploiting these edges. Why Traders Buy and
RTools of the trade
dplyr 1.1.0 was a significant release that makes several common data operations more syntactically intuitive. The most significant changes relate to joins and grouping/aggregating operations. In this post we’ll look at the changes to joins. First, install and load the latest version of dplyr: install.packages("dplyr") library(dplyr) A new approach to joins The best way to
Data
The changing face of market data providers Over the last few years, a number of new market data providers have come online. They tend to have modern websites, broad coverage, and well-documented RESTful APIs. Their services are often priced very competitively – especially for personal use – and usually have generous free tiers. One such
Quant tradingTrading as a businessTrading strategies
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
Quant trading
rsims is a new package for fast, quasi event-driven backtesting in R. You can find the source on GitHub, docs here, and an introductory blog post here. Our use case for rsims was accurate but fast simulation of trading strategies. I’ve had a few questions about how I made the backtester as fast as it
Quant trading
rsims is a new package for fast, realistic (quasi event-driven) backtesting of trading strategies in R. Really?? Does the world really need another backtesting platform…?? It’s hard to argue with that sentiment. Zipline, QuantConnect, Quantstrat, Backtrader, Zorro… there are certainly plenty of good options out there. But allow me to offer a justification for why
Quant trading
It’s easy to lose money trading if you do certain things: Trade too much (paying fees and market impact on each transaction) Size positions too big (high volatility hurts compounding ability, and in the extreme can cause you to blow up) Short positive drift/risk premia Perhaps surprisingly, it’s actually quite hard to lose money consistently
Think like a trader
Think like a trader
Think like a trader
Trading strategies
Trading strategies