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Quantocracy’s Daily Wrap for 10/13/2019

This is a summary of links featured on Quantocracy on Sunday, 10/13/2019. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Modelling Bid/Offer Spread In Equities Trading Strategy Backtest [Python For Finance]

    In this blog post I wanted to run a couple of quick experiments to see how clearly I was able to highlight the importance of incorporating various elements and components into a backtest that I admittedly often overlook in most of my posts that is I make the assumption that they will be dealt with by the reader at some point down the line, but choose not to include them for sake of simplicity.
  • Another Method of Creating Synthetic Data [Dekalog Blog]

    Over the years I have posted about several different methodologies for creating synthetic data and I have recently come across yet another one which readers may find useful. One of my first posts was Creation of Synthetic Data, which essentially is a random scrambling of historic data for a single time series with an attempt to preserve some of the bar to bar dependencies based upon a bar's
  • Crowded trades: measure and effect [SR SV]

    One measure of the crowdedness of trades in a portfolio is centrality. Centrality is a concept of network analysis that measures how similar one institutions portfolio is to its peers by assessing its importance as a network node. Empirical analysis suggests that [1] the centrality of individual portfolios is negatively related to future returns, [2] mutual fund holdings become more similar

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