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
Quant trading
Broadly, there are three types of systematic trading strategy that can “work.” In order of increasing turnover they are: Risk premia harvesting Economically-sensible, statistically-quantifiable slow-converging inefficiencies Trading fast-converging supply/demand imbalances This post provides an overview of each. 1. Risk Premia Harvesting Risk Premia Harvesting is typically the domain of wealth management, but it’s important to
RZorro
Earlier versions of Zorro used to ship with a script for converting market data in Zorro binary format to CSV. That script seems to have disappeared with the recent versions of Zorro, so I thought I’d post it here. When you run this script by selecting it and pressing [Test] on the Zorro interface, you
Quant trading
Several years ago, I wrote about some experimentation I’d done with data mining for predictive features from financial data. The article has had several tens of thousands of views and nearly 100 comments. I think the popularity of the article lay in its demonstration of various tools and modeling frameworks for doing data mining in R
BacktestingFXRTime series modellingTrading strategiesZorro
I’m a big fan of Ernie Chan’s quant trading books: Quantitative Trading, Algorithmic Trading, and Machine Trading. There are some great insights in there, but the thing I like most is the simple but thorough treatment of various edges and the quant tools you might use to research and trade them. Ernie explicitly states that
Quant trading
Colaboratory, or Colab, is a hosted Jupyter notebook service requiring zero setup and providing free access to compute resources. It is a convenient and powerful way to share research, and we use it extensively in The Lab. What’s The Lab? The Lab is the RW Pro group’s portal for doing collaborative research together as a
Think like a trader
I recently listened to a podcast about one of the earliest human civilizations – the ancient Sumerians. Apparently, our system of minutes, hours, and days has been with us since the time of these ancient people, who developed it based on a simple base-12 counting system: There are three joints in each of the four
Quant trading
I was very sad to learn that Quantopian is shutting down its community services. Quantopian’s efforts to bring quant finance outside of institutions was a genuine game-changer. The educational content was solid, the tech was excellent, and the QuantCon conferences were professional, well-run, and inclusive in a way that you never see at the “finance
Think like a trader
Think like a trader
Think like a trader
CryptoData analysisThink like a trader
Think like a trader