In this post, we explain how to use SQL to extend back ETF price data with total return data from mutual funds or indexes. On Zero to Robot Master Bootcamp, we teach how to build a portfolio of three automated systematic trading strategies. One of them is a long term Risk Premia Harvesting strategy …
Nearly everyone starts trading with unrealistic expectations. “If I make a 0.5% returns every day I can make over $100k in a year on 20k of starting capital.” 0.5% return every day sounds realistic, right? Wrong. Let’s sense check that… If we could make 0.5% returns every day… then our 20k would be worth: $123,000 …
In the Robot Wealth Pro Community, we’ve started doing weekend “quant-teasers” where we discuss the solutions to quant problems. Here is a recent one… Why aren’t calls more expensive than puts for an asset which is more likely to go up than down? We have an asset trading at $100 for which the distribution of …
In the world of Big Data, there are lots of tools and technologies to choose from. Choosing the “right” one depends on the things that you are building and the problems you are trying to solve. Trading firms have skilled teams that monitor and deploy data pipelines for their organisation and the technical overhead that …
Holding data in a tidy format works wonders for one’s productivity. Here we will explore the tidyr package, which is all about creating tidy data. In particular, let’s develop an understanding of the tidyr::pivot_longer and tidyr::pivot_wider functions for switching between different formats of tidy data. In this video, you’ll learn: What tidy data looks like …
Anyone that’s been around the markets knows that the monthly release of the United States Department of Labor’s Non-Farm Payrolls (NFP) data can have a tremendous impact, especially in the short term. NFP is a snapshot of the state of the employment situation in the US, representing the total number of paid workers, excluding farm …
Here’s a round-up of our new articles this week. They cover crash protection, sloppy, noisy regressions, and data-munging skills. Finding Options for Effective Crash Protection Large capital losses can be devastating to your trading account. A couple of weeks ago, we explained how you can use SPY put options to protect your portfolio against severe market …
When data is too big to fit into memory, one approach is to break it into smaller pieces, operate on each piece, and then join the results back together. Here’s how to do that to calculate rolling mean pairwise correlations of a large stock universe. Background We’ve been using the problem of calculating mean rolling …
When you’re working with large universes of stock data you’ll come across a lot of challenges: Stocks pay dividends and other distributions that have to be accounted for. Stocks are subject to splits and other corporate actions which also have to be accounted for. New stocks are listed all the time – you won’t have …
One way we can quantify a stock’s movement relative to the market index is by calculating its “beta” to the market. To calculate the beta of MSFT to SPY (for example) we: calculate daily MSFT returns and daily SPY returns align the returns with one another regress MSFT returns against SPY returns. This shows the …
