Recent Quant Links from Quantocracy as of 08/12/2025

This blog introduces retrospective simulation, inspired by Talebs "Fooled by Randomness," to simulate 1,000 alternate historical price paths using a non-parametric Brownian bridge method. Using SENSEX data (20002020) as in-sample data, the author optimises an EMA crossover strategy across the in-sample data first, and then applies it to the out-of-sample data using the optimum

Two months ago, Robecos Amar Soehbag, Guido Baltussen, and Pim van Vliet posted a new empirical paper, Factoring in the Low-Volatility Factor. I consider Pim a good friend, and he is one of the initial low-vol portfolio managers, as he started his conservative fund at Robeco around 2006 (the others were Analytic Investors, Acadian, and Unigestion). He says he was introduced to the low-vol

Do you find yourself obsessing over p-values and t-stats when evaluating trading ideas? I get it. If you come from an academic or scientific background, statistical significance feels like the gold standard for determining whether something is real or just random noise. And in many fields, thats exactly right. But trading is different. Statistical tests arent useless in trading. I use

Is Social Media Information Noise or Fundamentals? Evidence from the Crude Oil Market (Ma, Tourani-Rad, Xu, and Zhou) Social media sentiment from Thomson Reuters MarketPsych Indices predicts crude oil returns, with a one-standard-deviation rise implying a next-day gain of roughly 21 bps. Positive sentiment reflects fundamentals, persisting for months and forecasting inventory changes, while

Stop loss is a risk management technique. It has been advocated as a way to control portfolio risk, but how effective is it? In this post, I will discuss certain aspects of stop loss. When Are Stop Losses Effective? A stop loss serves as a risk management tool, helping investors limit potential losses by automatically triggering the sale of a security when its price reaches a predetermined level.

Exploring alternative assets like GLD ETF options enhances portfolio diversification by tapping into distinct volatility profiles and correlation patterns, especially beneficial during volatile market environments. In this post, we examine a simple, yet effective Put-Write strategy applied to GLD ETF Options, demonstrating how precious metals can serve as source of options income. GLD for

In the previous article, we deconstructed the Iron Condor, a robust strategy for harvesting the variance risk premium in markets characterized by range-bound behavior. The Condor, with its constituent out-of-the-money credit spreads, offers a wide plateau of profitability, making it a forgiving instrument for general forecasts of contained volatility. It is, in many ways, the workhorse of

TL;DR Virtually all of crypto returns come outside of NYSE trading hours, more so for coins pulled from the top 100, more so than for ETH & BTC Overnight returns dominate the WallStreetBets meme stock pumps of 2021 This pattern could be a signature of a conspiratorial pump or the nature of risky asset returns The equity overnight puzzle refers to the fact that, since we had good data on

Most trading strategies fail because they assume the market behaves the same all the time. But real markets shift between calm and chaotic, and strategies must adapt accordingly. This project builds a Python-based adaptive trading strategy that: Detects current market regime using a Hidden Markov Model (HMM) Trains specialist ML models (Random Forests) for each regime Uses the most relevant model