This is a summary of links featured on Quantocracy on Friday, 02/05/2021. To see our most recent links, visit the Quant Mashup. Read on readers!
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Copula for Pairs Trading: Sampling and Fitting to Data [Hudson and Thames]This is the second article of the copula-based statistical arbitrage series. You can read the first article: Copula for Pairs Trading: A Detailed, But Practical Introduction. Overview Whether it is for pairs trading or risk management, two natural questions to ask before putting copula for use are: How to draw samples from a copula? How should one fit a copula to data? The necessity of fitting is
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Improving time series animations in matplotlib (from 2D to 3D) [Quant Dare]Animating time series is a very powerful tool to show evolution over time, but matplotlib default animations are boring and they are not well suited for comparison purposes. Along this blog, animations are widely used: from explaining how neural networks train, to showing synthetic time-series statistics or indicating which funds are selected by the low volatility anomaly. Imagine that you want to
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Heatmap Plot of Forex Temporal Clustering of Turning Points [Dekalog Blog]Following up on my previous post, below is the chart of the temporal turning points that I have come up with. This particular example happens to be 10 minute candlesticks over the last two days of the GBP_USD forex pair. The details I have given about various turning points over the course of my last few posts have been based on identifying the "ix" centre value of turning point
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Do Security Analysts Follow the Academic Evidence? [Alpha Architect]As my co-author Andrew Berkin and I explain in our new book Your Complete Guide to Factor-Based Investing, there is considerable evidence of cross-sectional return predictability. Citing more than 100 academic papers, we presented evidence of predictability for both equity and bond factors. And since the research is well known, one would think that sophisticated professional investors would