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 …
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 …
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 …
If you have some factor that you think predicts future stock returns (or similar) and you are making charts like below, then here are some tips… We’ll go through an example of trying to “time” SPX with the level of VIX. You get daily SPX index prices and daily VIX close data You align them …
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 …
I’ve been helping a family friend with his trading. I’ve given him a simple systematic strategy to trade by hand. First, we set expectations We can plot the distribution of historic trade returns from past trading or a backtest as a histogram. This is useful because it gives us a hint as to what …
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 …
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 …
I have been sharing examples of simple real-time trading research on my Twitter account. I do this kind of thing a lot in the training program of our trading group – and I’m sharing in the hope that it might also help a wider audience. Here’s a piece of analysis I did recently on a really …
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 …
