Optimization

One Year Later: Is ChatGPT Finally Worth Using for Quantitative Analysis?

1.April 2026

One year ago, in our article “Can We Finally Use ChatGPT as a Quantitative Analyst?”, we explored the feasibility of leveraging ChatGPT for quantitative analysis. Since then, a lot has changed: newer models are now available (from OpenAI and also other vendors), and the ecosystem around AI-assisted analysis has evolved significantly. Back then, we encountered numerous challenges, ranging from model hallucinations and faulty code generation to excessive overfitting. In this article, we revisit these issues to assess what has improved and what remains unresolved, with the goal of finally answering whether we can use LLMs to assist with quantitative analysis tasks.

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Finding and Integrating Crisis Hedge Strategies: Improving Equity Portfolio Resilience

6.March 2026

Most systematic trading strategies are pro cyclical by nature. They perform best when markets trend higher and volatility remains contained. During broad market expansions, equity risk premia, momentum and trend following approaches tend to generate stable positive returns.

However, during market crises or extended bear markets, many of these strategies become synchronized. Correlations increase, volatility spikes and traditional diversification weakens. In such environments, portfolios built primarily from pro cyclical strategies may experience simultaneous drawdowns. This creates a structural need for strategies that behave differently during stress periods.

Crisis hedge strategies represent such a subset. They are designed to deliver diversification benefits specifically when equity markets decline. Because of their specialized behavior, they represent only a small fraction of the overall strategy universe.

This analysis demonstrates how crisis hedge strategies can be identified, evaluated and integrated into a model portfolio using the Quantpedia Pro framework.

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