This is a summary of links recently featured on Quantocracy as of Thursday, 06/19/2025. To see our most recent links, visit the Quant Mashup. Read on readers!
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Model: Clustering [Trading the Breaking]Alright, lets establish first principles. Before deploying capital into algorithmic strategies, one must confront the paradigm shift that distinguishes durable firms from those erased by structural blind spots: financial markets are not monolithic stochastic processes but non-stationary systems governed by latent regime dynamics. This is not heuristic philosophyits an empirical reality
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I Used a Thermostat s Logic to Control My Portfolio And Achieved 24% CAGR [Paper to Profit]As traders, we scour the internet, books, and articles for industry specific information to create our new fancy algorithms. The Black-Scholes model, Markowitz Mean-Variance portfolio optimization, the Capital Asset Pricing Model (CAPM) These are all systems designed for investment purposes solely. derivatives – Proof Black Scholes Theta – Quantitative Finance Stack Exchange Enough of this math
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Deep Reinforcement Learning for Portfolio Optimization [Gatambook]We wrote a lot about transformers in the last three blog posts. Their sole purpose was for feature transformation / importance weighting. These transformed and attention-weighted features will be used as input to downstream applications. In this blog post, we will discuss one such application: portfolio optimization via deep reinforcement learning. We will based our example on a paper by Sood et.
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Weekly Research Recap [Quant Seeker]Decoding the Bond Market (Haghani and White) Investors often look to bonds for clues about future interest rates and inflation. This paper explains how to extract such signals from current market yields. After adjusting for convexity and risk premia, the authors find that markets expect long-term real rates to be near 1.75% and inflation to be around 2.1%. Given the low compensation for risk,
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Why Most Markets and Styles Have Been Lagging US Equities? [Quantpedia]Over the past decade and a half, the US equities have set the hard-to-beat performance benchmark. Nearly all of the other countries, no matter if small or big, emerging or developed, have lagged behind. However, what are the forces behind this outperformance? Why did most of the other markets and even investing styles bow to the US large-cap growth dominance? A new paper written by David Blitz
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Using Skewness and Kurtosis to Enhance Trading and Risk Management [Relative Value Arbitrage]Skewness is a measure of the asymmetry of a return distribution. In this post, Ill discuss the skewness risk premium and how skewness can be used to forecast realized volatility. Skewness Risk Premium in the Options Market Skewness of returns is a statistical measure that captures the asymmetry of the distribution of an assets returns over a specified period. It is particularly important in