This is a summary of links recently featured on Quantocracy as of Monday, 05/04/2026. To see our most recent links, visit the Quant Mashup. Read on readers!
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Deep Learning for Volatility Surface Repair [Jonathan Kinlay]A self-contained synthetic benchmark of a small mask-conditional CNN against calendar-projected linear interpolation and a per-slice SVI fit. A volatility surface marker is rarely a clean rectangle of quotes. Strikes go unobserved during illiquid hours, wings get crossed and then erased, broker stripes drop out across an entire maturity, and weeklies arrive at the desk with random missingness on
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New Contributor: Modeling Asymmetric Volatility With EGARCH [Krzysztof Ozimek]This post presents an accessible introduction to the Exponential GARCH (EGARCH) modela widely used tool in financial econometrics for modeling time-varying volatility in asset returns. Unlike standard GARCH models, EGARCH captures both volatility clustering and the leverage effect, whereby negative shocks tend to increase future volatility more than positive shocks of equal magnitude. The post
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A Strong Start to May Has Often Been Followed by a Short-Term Dip [Quantifiable Edges]May got off to a positive start. But a strong start to May has typically been followed by a dip in the next few days. This can be seen in the study below, which was featured in this weekends subscriber letter. Of the 25 instances that rose on the first day in May since 1987, 17 of them closed lower 4 days later. Below is an equity curve that shows how it has played out over time. Ill note
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Overfitting and Parameter Selection in Trading Strategies [Relative Value Arbitrage]The risk of overfitting is serious and can lead to significant losses. It has been discussed in previous posts. In this edition, we revisit the topic, given its continued relevance to quantitative strategy development. Formal Study of Overfitting in Trading System Design A serious problem when designing a trading system is the overfitting phenomenon, wherein the system is excessively tuned to