Venn’s Scenario Analysis helps your organization understand the impact of market shocks on your investments and portfolios. After launching Scenario Analysis in the middle of 2019, the strongest feedback we received was to explore increasing the available shock size above and beyond 2 standard deviations.
We’re pleased to announce that we have released an extension of the Scenario Analysis feature that allows users to apply shocks up to 1.5x the maximum observed historical positive and negative monthly performance of market indices. When you add or modify a scenario on Venn, you can immediately see the newly available range. In some cases, this range is now almost 4x as large as what was previously available. In the case of the Bloomberg Commodity Index, the range for shocks is now -7.8 standard deviations (-31.9%) to +5 standard deviations (+20.7%), as highlighted below:
To support these more significant shocks, we needed to incorporate a model that could account for the changes in the factor correlation structure. Doris Bao, the lead quantitative researcher behind this effort, shared the following about our approach:
“Financial markets can experience regime changes. In normal times, it is reasonable to assume market returns will follow the same distribution, but when markets move dramatically, this assumption likely breaks down. As a result, we wanted to leverage a model that could capture different distributions of market returns across different regimes. And instead of asserting which regimes the market has, our preference was to let the data speak for itself.”
To accomplish this, we introduced a regime-based model that accounts for the changes in the factor correlation structure during extreme shocks. The model is called a “Gaussian Mixture Model” (or GMM), an unsupervised learning mechanism, to define four different regimes of the market, ranging from recessionary to expansionary. Depending on the specific shock assigned to a scenario index, the model produces the probabilities that represent how likely we are to be in each regime (e.g., if we shock an equity index by a large negative amount, the model will likely produce a very high probability for a crisis-related regime). Venn can then propagate the impact onto the factors and eventually onto a portfolio or investment, using its factor exposures.
Depending on the size of the scenario index shock, Venn leverages the original methodology and the new, regime-based methodology in different ways:
- For shocks less than two standard deviations, the original linear approach is used, which does not model changing market conditions.
- For shocks between two and three standard deviations, the two methodologies are blended.
- For shocks greater than three standard deviations, the regime-based methodology is used.
We’re excited this new capability is in your hands, and we look forward to continuing to learn about the ways that we can evolve and improve Venn to better meet your needs. If you have any feedback or questions, please feel free to reach out to us!
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