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Quantocracy’s Daily Wrap for 06/16/2021

This is a summary of links featured on Quantocracy on Wednesday, 06/16/2021. To see our most recent links, visit the Quant Mashup. Read on readers!

  • More ideas for ranking methods on a monthly S&P500 Stock Rotation Strategy [Alvarez Quant Trading]

    My last post on Different ranking methods for a monthly S&P500 Stock Rotation Strategy generated lots of emails on other ideas to try. Below are the results of these ideas Base Rules Backtest from 1/1/2007-12/31/2020. Buy It is the last trading day of the month Stock is a member of the S&P500 index Stock is above the 200-day moving average (spreadsheet has results without this rule) The
  • Automating cryptocurrencies investment [Quant Dare]

    Who has never heard about cryptocurrencies: Bitcoin, Ethereum, Cardano, or even the latest ones, such as Shiba or Safemoon? The investors are rapidly increasing their positions in those assets, although investing in them is usually a pain in the neck. These assets have a high volatility and their movements dont follow any traditional market rule and cryptocurrencies markets are not efficient.
  • Podcast with Ernie Chan (@ChanEP): Predicting profitability using machine learning [Better System Trader]

    Quant trader Ernie Chan from PredictNow.ai joins us to discuss how to predict the profitability of trades using machine learning, including: Unconditional probability and the problem with win% in backtest reports, Why conditional probability is much more useful for a trader and how to apply conditional probabilities to capital allocation, Why you should use Machine Learning for risk

Filed Under: Daily Wraps

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