This is a summary of links recently featured on Quantocracy as of Saturday, 06/06/2026. To see our most recent links, visit the Quant Mashup. Read on readers!
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The crossword puzzle of fitting – why across and then down? [Investment Idiocy]This will be the first in a series of posts about portfolio optimisation. Main reason being I'm planning to write a book about backtesting, and that will include a big chunk of material on optimisation. Yes, I know, my latest book isn't out yet (it's out in December – in time for Christmas). But this backtesting book is going to be quite deep (and probably long!) so I need to start
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The Non-Linear Costs of Trading [Concretum Group]At Concretum Group, a relevant part of our research effort goes into developing strategies for external clients, each arriving with different requirements about what market behavior to model and, just as importantly, about how much capital a given strategy is meant to run on. This brings us to a very delicate part of our work, which might not seem exciting at first, but becomes crucial before
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How Wise is the Crowd in Prediction Markets [Quantpedia]If youve ever scrolled through Polymarket or Kalshi wondering whether the wisdom of crowds is actually wisdomor just organized noiseyoure not alone. A new paper, How Wise is the Crowd? Bias and Edge in Prediction Markets, tears into the microstructure of modern prediction markets to ask a practical question: Whos actually making money, and whos just paying for the
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Research Review | 5 June 2026 | Risk Management [Capital Spectator]Measuring Bubbles via Put-Call Disparity: A Model-Free Approach Robert A. Jarrow (Cornell U.) and Simon Kwok (U. of Sydney) May 2026 This paper introduces simple, model-free lower and upper bounds for measuring the size of asset price bubbles. Assuming only that the market satisfies no-free-lunch-with-vanishing-risk and that all trading strategies are admissible, our framework avoids restrictive