How To Be a Quant Trader – Experiments with QuantConnect

  This post presents an analysis of the SPY returns process using the QuantConnect research platform. QuantConnect is a strategy development platform that lets you research ideas, import data, create algorithms, and trade in the cloud, all in one place.  For this research, I’ve used their online research notebook, and it came preinstalled with all …

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Working with Tidy Financial Data in tidyr

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 …

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How to Hedge a Portfolio with Put Options

There are 2 good reasons to buy put options: because you think they are cheap because you want downside protection. In the latter case, you are looking to use the skewed payoff profile of the put option to protect a portfolio against large downside moves without capping your upside too much. The first requires a …

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Can you apply factors to
trade performance?

When tinkering with trading ideas, have you ever wondered whether a certain variable might be correlated with the success of the trade? For instance, maybe you wonder if your strategy tends to do better when volatility is high? In this case, you can get very binary feedback by, say, running backtests with and without a …

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Momentum Is Dead! Long Live Momentum!

In our inaugural Algo Bootcamp, we teamed up with our super-active community of traders and developed a long-only, always-in-the-market strategy for harvesting risk premia. It holds a number of different ETFs, varying their relative weighting on a monthly basis. We’re happy with it. However, the perennial question remains: can we do better? As you might …

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Demystifying the Hurst Exponent – Part 2

What if you had a tool that could help you decide when to apply mean reversion strategies and when to apply momentum to a particular time series? That’s the promise of the Hurst exponent, which helps characterise a time series as mean reverting, trending, or a random walk. For a brief introduction to Hurst, including …

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How to Create a Trading Algorithm: So You Want to Build Your Own Algo Trading System?

This post comes to you from Dr Tom Starke, a good friend of Robot Wealth. Tom is a physicist, quant developer and experienced algo trader with keen interests in machine learning and quantum computing. I am thrilled that Tom is sharing his knowledge and expertise with the Robot Wealth community. Over to you, Tom. Unlike …

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Exploring Mean Reversion and Cointegration: Part 2

In the first Mean Reversion and Cointegration post, I explored mean reversion of individual financial time series using techniques such as the Augmented Dickey-Fuller test, the Hurst exponent and the Ornstein-Uhlenbeck equation for a mean reverting stochastic process. I also presented a simple linear mean reversion strategy as a proof of concept. In this post, I’ll …

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