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Quantocracy’s Daily Wrap for 01/15/2021

This is a summary of links featured on Quantocracy on Friday, 01/15/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • How To Create A Fully Automated AI Based Trading System With Python (h/t @PyQuantNews)

    A couple of weeks ago I was casually chatting with a friend, masks on, social distance, the usual stuff. He was telling me how he was trying to, and I quote, detox from the broker app he was using. I asked him about the meaning of the word detox in this particular context, worrying that he might go broke, but nah: he told me that he was constantly trading. If a particular stock has been going
  • How to Get Historical Market Data Through Python Apis [Quant Insti]

    As a quant trader, you are always on the lookout to create and optimise your trading strategies. Backtesting forms a very important part of this process. And for backtesting, access to historical data is a necessity. But its a very daunting task to find decent historical price data for backtesting your trading strategies. While a simple google search can give you the end of day data for any
  • Research Review | 15 January 2021| Forecasting [Capital Spectator]

    Long-Term Stock Forecasting Magnus Pedersen (Hvass Laboratories) December 17, 2020 When plotting the relation between valuation ratios and long-term returns on individual stocks or entire stock-indices, we often see a particular pattern in the plot, where higher valuation ratios are strongly correlated with lower long-term stock-returns, and vice versa. Moreover the plots often show a particular

Filed Under: Daily Wraps

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