Luigi Piva, CQF — Quanthedge AI (research arm of AlgosWorks AI Ltd) All code in this article is runnable as-is. The example track record is synthetic and fully specified, so every number is reproducible; Search for “Monte Carlo simulation trading strategy” and you will find, with remarkable consistency, the same recipe: take the list of […]

Read More

Beyond Univariate: VAR, VECM, and Cointegration in Energy Markets

  • Luigi Piva, CQF
  • August 20, 2026
  • 11 min read

In the quantitative analysis of financial markets, the leap from univariate to multivariate time series analysis is not just a statistical exercise — it is a necessity dictated by the inherently interconnected nature of global markets. In this article I revisit and expand my Module 6 project for the Certificate in Quantitative Finance (CQF). We […]

Read More

Uncertain Volatility

  • Luigi Piva, CQF
  • August 12, 2026
  • 12 min read

  QuantHedgeAI · Research Note Derivatives · Numerical Methods No. 001 — Uncertain Volatility Pricing a Binary Option Under Uncertain Volatility The full nonlinear PDE, a gamma-sign volatility switch, and an explicit finite-difference scheme — worked end to end, with runnable code. Luigi Piva, CQF  ·  QuantHedgeAI  ·  Research Note 001 The Black–Scholes framework treats […]

Read More

Regime-based exposure scaling: what works, what doesn’t

  • Luigi Piva, CQF
  • August 11, 2026
  • 5 min read

Luigi Piva — ALGOSWORKSAI LTD This is the complete, honest account of a week of testing on a simple question: can you use a statistical measure of market stress to improve an equity portfolio, exiting into turbulence and re-entering into calm? The short answer is “yes, but.” The long answer — with the dead ends, […]

Read More

Luigi Piva — ALGOSWORKSAI LTD This article is the complete, technical version of an idea I introduced elsewhere: how to measure market stress with the Mahalanobis distance, how to implement it in Python without fooling yourself, and what to expect when you use it. It contains working code and the methodological discipline that separates a […]

Read More

Implementing a Multi-Strategy Portfolio End-to-End

  • Luigi Piva, CQF
  • July 13, 2026
  • 11 min read

The math is the easy part. The operational discipline is where multi-strategy portfolios live or die. From notebook to live capital The previous two posts in this series argued for multi-strategy investing on mathematical grounds and walked through the allocation methods. This post is about everything that happens between “I have N candidate strategies and […]

Read More