lisson.constantin

Teaching

Lecture slides from an undergraduate data science course.

• Linear Regression
• Classification
• Multiple Testing & Resampling
• Model Selection & Regularization
• Tree-Based Methods
• Unsupervised Learning

Writing

• Using Prospect Theory to Determine Investor Risk Aversion
  In: Liermann, V., Stegmann, C. (eds). The Impact of Digital Transformation and FinTech on the Finance Professional. Palgrave Macmillan · 2019
• Robust Filtering for Financial Time Series
  Master thesis · SSRN · 2017

Experiments

• Meaningless Price Path

  A freshly generated meaningless price path, based on a Brownian Motion with drift — the model that says markets are efficient and your stock picks are pure luck. Consider it an invitation to meditate on how false pattern recognition may lead one astray.
• 字 Radix — Learn characters without brute force →
  An app Claude and I built for learning Chinese and Japanese characters without spaced repetition and without rote visual memorization. Built for my own study, shared because it might help someone.
• Game of Life →
  Conway’s cellular automaton — a few rules about birth and death on a grid, out of which gliders, oscillators, and deterministic chaos emerge. Cells are coloured by how crowded their neighbourhood is.
• Shrinkage — Lasso, Ridge, and Elastic Net →
  An interactive version of Tibshirani’s “Lasso Picture” to illustrate what the penalty parameter does in regularized regression and how shrinkage and variable selection are special cases of the elastic net idea.
• CLT — the Central Limit Theorem on a Galton board →
  Drop balls through a quincunx and watch a bell curve assemble itself, with a live histogram, kernel density estimate, normal fit, and a Kolmogorov–Smirnov test. A second mode shows the same bell emerging no matter how lumpy or skewed the underlying distribution is.

Elsewhere

Find me on LinkedIn, book a time to talk, or write to public@lisson.co.