./mdx_sources/SampleWeights/sample_weights.mdx

How to use sample weights to address the problem that observations are not generated by (IID) processes.

What's the distinction between organized and unstructured data? We will learn how to work with unstructured financial data and then transform it into a structured dataset that can be used by $mathrmML$ algorithms. In general, you should avoid consuming someone else's processed dataset because you will most likely find what someone else already knows or will figure out shortly. Ideally, your starting point will be a collection of unstructured, raw data that you will analyse in order to generate relevant characteristics.

Sample Weights

Explain a procedure for reducing the noise and enhancing the signal included in an empirical covariance matrix.

Denoising

./mdx_sources/EntropyFeatures/entropy_features.mdx

When markets are not perfect, prices are formed with partial information, and as some agents know more than others.

Entropy Features

./mdx_sources/PortfolioConstruction/portfolio_construction.mdx

In practice, mean-variance optimal solutions tend to be concentrated and unstable. How to deal with the instability caused by the noise contained in the covariance matrix?

Portfolio Construction

./mdx_sources/DangersOfBacktesting/dangers_of_backtesting.mdx

A common misunderstanding is to think of backtesting as a research tool. Researching and backtesting is like drinking and driving.

Backtesting Dangers

./mdx_sources/StructuralBreaks/structural_breaks.mdx

Structural Breaks

Structural breaks, like the transition from one market regime to another, is one example of such a confluence that is of particular interest.

Sat Mar 05 2022

Structural Breaks

TODO