Given a portfolio and an optimizer, can we find a ‘better’ portfolio using atoti? It’s a classic situation: you versus a benchmark portfolio. Maybe you’ve built your own portfolio optimizer or maybe you found an optimizer online. Either way, once you have your optimized portfolio output (or outputs!), you still...
Using Twitter to forecast cryptocurrency returns #3 – A time series analysis using VAR
Find out which features can forecast the returns with Granger Causality Test If you have followed my first article, it’s tough scraping Twitter for the sentiment analysis. Here are my initial thoughts: A Tweet can be super positive but has no impact if there are no followers on the TweetA...
How to explain non-additive measures, Part 3: order-statistics decomposition
Interactive decomposition with atoti This article is a part of a series. Check also: Part 1: Pro-rata allocation for a generic example of allocation into additive components and Part 2: Marginal contribution for an incremental analysis example. In this post, we’ll explore a technique which is handy for historical VaR...
Market risk analytics in python: Interactive rolling VaR
The Recipe for Stressed VaR calibration In this post, I want to illustrate how to create an analytical application with atoti and Python that can help to visualize and interactively slice-and-dice the impact of increasing volatility on the Value-at-Risk (VaR) metrics of an investment portfolio. This might be particularly interesting...