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Quantocracy’s Daily Wrap for 06/26/2024

This is a summary of links featured on Quantocracy on Wednesday, 06/26/2024. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Rolling regime [OSM]

    Our last post finished up examining the three different methods used to predict market regimes in the Gold Miners ETF, GDX namely, clustering, Gaussian Mixture Methods (GMMs), and Hidden Markov Models (HMMs). We found GMMs performed the best in terms of proof-of-concept. But there was a lot of work to do to go from backtest to viable trading strategy. In the next few posts, well look at
  • Volatility Forecasting: HAR Model [Portfolio Optimizer]

    Among the different members of the family of volatility forecasting models by weighted moving average1 like the simple and the exponentially weighted moving average models or the GARCH(1,1) model, the Heterogeneous AutoRegressive (HAR) model introduced by Corsi2 has become the workhorse of the volatility forecasting literature3 on account of its simplicity and generally good forecasting

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