This is a summary of links featured on Quantocracy on Thursday, 05/13/2021. To see our most recent links, visit the Quant Mashup. Read on readers!
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Learning Candlestick Patterns [Tr8dr]In the previous posts I described an Reinforcement Learning approach to Learning the Exit part 1, part 2. My initial conclusions there have been: reward smoothing (with the labeler) leads to more robust results than a reward on position exit without smoothing the learning process struggled and had more volatility from epoch to epoch obtained the best results with smoothed reward obtained
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The Rust Programming Language [Mark Best]I love programming! There is something really satisfying about solving a complicated problem concisely. That said I see programming languages as a tool to solve a problem rather than purely coding for coding sake. I have used a lot of programming languages over the last 20 years namely Java, R, Matlab, Python, C++ and now Rust. It is pretty common to read articles about language wars and which one
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Fixed income when you re between a rock and a hard place – Part 2 [Alpha Architect]In Part 1, we defined fixed income factors. But factors alone will not solve each investors problem. Below, we extend the discussion by walking through a case study that shows how an asset allocator might use factors to solve a common problem: how to invest in a low yield environment given the practical constraints faced by many investors. Or, how can factors help investors stuck between a rock