This is a summary of links featured on Quantocracy on Thursday, 03/09/2017. To see our most recent links, visit the Quant Mashup. Read on readers!
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Forecasting Stock Returns using ARIMA model [Quant Insti]Prediction is very difficult, especially about the future. Many of you must have come across this famous quote by Neils Bohr, a Danish physicist. Prediction is the theme of this blog post. In this post, we will cover the popular ARIMA forecasting model to predict returns on a stock and demonstrate a step-by-step process of ARIMA modeling using R programming. What is a forecasting model in
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Playing with Prophet on Financial Time Series [Quant Dare]Two weeks ago, Facebook launched Prophet, an amazing forecasting tool available in Python and R. Heres a bit of info from the Facebook research website: Forecasting is a data science task that is central to many activities within an organization. For instance, large organizations like Facebook must engage in capacity planning to efficiently allocate scarce resources and goal setting in order
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What hand traders can learn from system traders, and vice versa w/ @AdamHGrimes [Chat With Traders]Adam Grimes has been a trader for more than 20-years, hes traded all major asset classes, across various timeframes. Hes traded independently, with a prop firm, and hes run other trading businesses also. The main focus of this episode is to explore some of the things which discretionary traders can adapt from quantitative traders, and vice versameaning, what things can quants take from