Exponential weighting schemes can help navigate the trade-off between responsiveness and stability of the inherently noisy estimates we make from market data. We previously saw examples of calculating the exponentially weighted moving average of a vector, and estimating the correlation between SPY and TLT using an exponential weighting scheme [link]. In this article, we’ll implement …
Using Exponentially Weighted Moving Averages to navigate trade-offs in systematic trading A big part of the job of the indie trader is data analysis. We’re always looking in the past data to validate (or more often, invalidate) a hypothesis about what might predict future returns. And one could argue that recent data is more useful …
I’ve previously discussed the Volatility Risk Premium (VRP) and how it differs from the Equity Risk Premium (ERP). Probably the most interesting difference, from the perspective of the trader, is that the VRP may be somewhat amenable to timing – more than the ERP at any rate. In this article, I’ll use some of the …
I felt like doing something a little more lighthearted than usual. I’ve been deep in data engineering land these last couple of weeks, building data pipelines for processing a ton of options data for a trade we’re researching (the straddle-over-earnings trade). So I took some time out to mess around with something fun – building a …
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 …
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 …
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.)
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 …
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 …
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 …
