This is a summary of links recently featured on Quantocracy as of Monday, 02/02/2026. To see our most recent links, visit the Quant Mashup. Read on readers!
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More Bootstrap Simulations with Portfolio Optimizer: the Autoregressive Online Bootstrap [Portfolio Optimizer]In a previous article, I described several classical bootstrap techniques i.i.d. bootstrap, circular block bootstrap, and stationary block bootstrap and showed how the stationary block bootstrap could be used to simulate future price paths for financial assets by following the methodology of Anarkulova et al.1. In this blog post, I will detail another bootstrap technique called the
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Sampling Stock Prices Directly from Option Prices [Sitmo]For a single maturity, European call prices encode the risk-neutral distribution of the underlying. You can turn them into Monte Carlo samples without fitting a model or estimating a density. For strikes K_0 < < K_n with call prices C_0, , C_n, define [F_i = 1 + e^{rT} frac{C_{i+1}-C_i}{K_{i+1}-K_i}, quad F_0 = 0, quad F_n = 1] This is a discrete approximation of the cumulative
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Member Note: Our Approach to Selecting Strategies for the Platform [Allocate Smartly]A long-time member who has been a valuable source of feedback over the years sent us the following note about the most recent strategy added to the platform: Gold Cross-Asset Momentum. The strategy has performed poorly relative to other strategies on the platform. Youve turned down other stuff that was marginal like this, so Im surprised it made the cut. Hes right. Viewed in isolation,
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Do S&P500 0DTEs Options Increase Market Volatility? [Quantpedia]Recent market action has once again underscored how rapidly volatility can surface across asset classes, as evidenced by pronounced price swings in gold, silver, and cryptocurrency markets. Such episodes routinely revive debate within the quantitative community about structural drivers of intraday instability, with particular attention paid to the growing prominence of S&P 500