This is a summary of links featured on Quantocracy on Thursday, 06/24/2021. To see our most recent links, visit the Quant Mashup. Read on readers!
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Introducing: Arbitragelab Tear Sheets [Hudson and Thames]Pairs selection is the first crucial step to building a pairs trading strategy. And it is no surprise, to perform it correctly, one must diligently examine, compare and contrast numerous test results, graphs and characteristics. For example, cointegration analysis alone can be performed in one of two methods utilizing the Engle-Granger approach or the Johansen approach. To truly have the
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Return based quality factor on Warsaw Stock Exchange [Mateusz Dadej]Recently I ran across an interesting paper published by National Bureau of Economic Research entitled Return Based Measue of Firm Quality. I happen to have a suitable data and thought why not reproduce it on data from polish stock exchange in the free time. It turned out not so bad and thanks to being not filled with boring mathematical formulae I guess its also pretty accessible. At the
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An Introduction to Unsupervised Learning for Trading [Quant Insti]In the previous blogs, we examined supervised learning algorithms like linear regression in detail. In this blog, we look at what unsupervised learning is and how it differs from supervised learning. Then, we move on to discuss some use cases of unsupervised learning in investment and trading. We explore two unsupervised techniques in particular- k-means clustering and PCA with examples in Python.
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A Sensible Approach to Bitcoin [Dual Momentum]Last year when bitcoin had its fourth drawdown of 80% in the past ten years, I thought It might be a good time to reenter that market. Having traded digital assets in 2017, I was familiar with the reasons for owning bitcoin. I wont reiterate them here. You can find information on bitcoin, blockchain, and decentralized finance (DeFi) here, here, here, and here. Every disruptive technology, like