At Ortec Finance we have been building and applying Economic Scenario Generator (ESG) models for decades, aimed at enabling people all over the world to manage the complexity of investment decision making. Over the years we have done a lot of R&D around this topic, and shared the results through various conference presentations. Although some cases are more than a decade old, the content of these “scenario modeling evergreens” is still very relevant today.

After VAR Models Do's and Don'ts, a second such presentation from 2012 covers the design of a special pass band filter. Filters are used to decompose macroeconomic and financial market time-series data into for example trend + cycle + seasonal + random components. The underlying idea of such decompositions is that different “forces” drive for example long-term economic growth compared to intraday trading effects on a stock exchange.

This pass band filter is central to the one-of-a-kind frequency domain methodology that we use for generating scenarios. We use it to separate trends from business cycle and monthly intra-year fluctuations. Together with Dynamic Factor Models (DFM) for each of these components it constitutes the “bi-orthogonal decomposition approach” which drives the time-varying risk and return across economies, asset classes and investment horizons in our scenarios.

Based on 10 years of practical experience we have improved it along the way but essentially we still work with this very same filtering approach. We are happy to share its workings with you by means of this presentation. Click here to find out more about our Economic Scenario Generator (ESG) models.

Download your copy

By submitting my contact information, I confirm that I have read the Ortec Finance Privacy statement, which explains how Ortec Finance collects, processes and shares my personal data. I consent to my data being processed with Ortec Finance's Privacy Policy. Ortec Finance can optimize my experience with the Ortec Finance brand.

We respect your privacy

Related Insights

Cookies help us improve your website experience.
By using our website, you agree to our use of cookies.