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Quantocracy’s Daily Wrap for 06/13/2022

This is a summary of links featured on Quantocracy on Monday, 06/13/2022. To see our most recent links, visit the Quant Mashup. Read on readers!

  • Slava Ukraini! Latest from Only VIX, Quantocracy contributor in Ukraine: Modeling Implied Vol Surfaces of Crypto Options [Only Vix]

    This is a quick follow-up to my previous post with comments on Artur Sepps's video. From the start Mr Sepp sets up the practical problem familiar to anyone in the crypto options space. The leader is Deribit – an exchange that I wrote about extensively in this blog with ~ 89% market share. The next biggest is CME with ~ 6% market share, and expected to grow. One would naturally want to trade
  • A Rare Inverse Zweig Breadth Collapse Triggers [Quantifiable Edges]

    A few years back I wrote about Zweig Breadth Thrusts in some detail. The Zweig Thrust takes a 10-day exponential moving average of the NYSE Up Issues %. It looks for a move from Over the last 3 days we have essentially what could be considered the inverse setup trigger. The NYSE Up Issues % 10ema has fallen from above 61.5% to under 40% in 10 trading days. Rather than a breadth thrust, we have
  • Ehlers Loops [Financial Hacker]

    Price charts normally display price over time. Or in some special cases price over ranges or momentum. In his TASC articles in June and July 2022, John Ehlers proposed a different way of charting. The ratio of two parameters, like price over momentum, or price A over price B, is displayed as a 2D curve in a scatter plot. The resulting closed or open loop is supposed to predict the future price
  • Sector versus Factor Exposure Analysis [Factor Research]

    Investors tend to talk more about sector than factor performance However, few investors conduct a regression-based sector exposure analysis The high correlations of sectors, even if structured market-neutral, makes this less meaningful INTRODUCTION Switch on CNBC or Bloomberg TV during US stock trading hours and there is a good probability of listening to a lively discussion on current sector
  • Six ways to estimate realized volatility [SR SV]

    Asset return volatility is typically calculated as (annualized) standard deviation of returns over a sequence of periods, usually daily from close to close. However, this is neither the only nor necessarily the best method. For exchange-traded contracts, such as equity indices, one can use open, close, high, and low prices and even trading volumes. These provide different types of information on

Filed Under: Daily Wraps

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