This is a summary of links featured on Quantocracy on Wednesday, 07/29/2020. To see our most recent links, visit the Quant Mashup. Read on readers!
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Connecting to the Interactive Brokers Native Python API [Quant Start]Interactive Brokers has always been a popular brokerage with systematic traders. Initially this could partially be attributed to the fact that IB provided an Application Programming Interface (API) that allowed quants to obtain market data and place trades directly in code. Many competing brokerages took some time to develop their own APIs, allowing IB to gain a reasonable early-mover advantage in
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Introduction to NLP: Sentiment analysis and Wordclouds [Quant Dare]I think one of the most interesting areas in the data analysis field is Natural Language Processing (NLP). These last years this discipline has grown exponentially and now its a huge area with a lot of problems we can attempt to solve, like text classification, translations or text generation In this post, I will show one of the simplest ways to approach to text processing. Im going to focus
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Detailed Logging with a Low-Level CBT [Quant For Hire]Recently a student of my CBT course asked why he wasnt seeing the usual output (including dates) when he selected AmiBrokers Detailed Log option and ran a backtest that utilizes a low-level CBT. The answer is that much of the Detailed Log output comes from AmiBrokers ProcessTradeSignals method, which isnt used in a low-level CBT. However, its fairly straightforward to add your
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Are Asset Class Correlations At A New Permanently High Plateau? [Capital Spectator]The coronavirus crisis reordered many things in economics and finance and you can add asset correlations to the list. After markets crashed in March, followed by a strong (so far) rebound, asset classes have continued to move with an unusually deep and broad degree of unison. High, or at least higher return correlations arent unusual around periods of severe market corrections. The question is