Educational on markets and quantitative methods.
A user-friendly and mathematical guide to the ETF portfolio simulator: how it works, what metrics it uses (Sharpe, Sortino, drawdown), assumptions and limitations. Educational tool to evaluate PIC and PAC and the risk/return relationship.
How to build an efficient ETF portfolio using correlations and hierarchical clustering. Practical examples, figures and a Colab notebook to replicate the analysis.
A comprehensive guide to economic regimes with the Investment Clock: definitions, indicators (real GDP, core inflation), allocations for each phase and links to Colab notebook and video. Includes a figure and two explanatory tables.
What independent financial advice is according to TUF and MiFID II, differences from traditional advice, principles, practical advantages and institutional references (OCF, CONSOB, FCA).
What deep learning is, how it applies to multi-asset tactical allocation, strengths relative to traditional ML, risks, governance and institutional references (ECB, PRA/BoE).
Global version of the DL allocation model: pipeline, architecture, backtest, two simulation methodologies (historical replay and correlated synthetic returns), bull/Covid/Financial crisis scenarios and conclusions.
The most common biases (confirmation, anchoring, recency), how they influence investment decisions and how to mitigate them with disciplined plans and diversification.
Hedged or unhedged? What currency hedging is in ETFs, pros and cons, and a quantitative analysis with Python (Colab) on S&P 500, MSCI World and 20+ year Treasuries.
What human capital is, how to value it and how to integrate it into asset allocation: theory, formulas and two practical examples (family with stable income and entrepreneur with volatile income).