During good times, portfolio risk is often an afterthought. When asset prices are rising and market volatility is low, risk management tends to be much more of a reactive process than a proactive one. It tends to be a once- or twice-a-year process of dusting off old spreadsheets, updating them for changes, and incorporating the latest assumptions as best they can.
Building a robust, regularly updated risk process requires four critical inputs: the weights of each investment across all asset classes, a covariance matrix of all investments, returns for a representative set of risk factors, and a methodology for modeling the variances and correlations of illiquid assets. It is a lot to pull together even once. Doing so regularly requires coordination across portfolio and functional silos, risk expertise, and significant amounts of automated data.
Johnathan Crist, CFA FRM, is a Sr. Investment Analyst at the Georgia Tech Foundation, Inc., where he is part of the team managing $2.3 billion in assets. His responsibilities include managing the portfolio allocation, risk, and derivative program. Georgia Tech Foundation had integrated its live allocation in Solovis into some crude Excel models to monitor its portfolio risk and equity beta.
In 2019, Georgia Tech Foundation became Solovis’ first Risk Analytics client. At that point, Solovis Risk Analytics consisted only of prototype Python code that printed calculations into an Excel spreadsheet report. But Georgia Tech Foundation was also a Solovis Portfolio Analytics client. This meant that Solovis could see Georgia Tech Foundation’s allocation to every stock and bond in its portfolio, including full look-through into the portfolios of many of its managers, throughout time.
A key drawback of many other risk systems is that they are returns-based rather than positions-based. The consequence of calculating factor exposures and risk using returns is that the historical time series of a manager’s returns reflect shifting styles, asset allocations, and views. Risk metrics calculated using these returns capture the average positioning of the manager or portfolio over the analysis period. However, when conducting a risk analysis, the best predictor of ex-ante risk is the current positions. Solovis set out to solve this issue for Georgia Tech Foundation, and other future clients, by building an analytical platform on top of the positions-level data it already had access to via Portfolio Analytics.
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“Solovis had been our core tool used to monitor our portfolio allocation. As a group, we always challenged ourselves to look through just asset class weights to understand our true exposure and risk. We had integrated our live allocation in Solovis to some crude Excel models to monitor our portfolio risk and equity beta. The launch of Solovis Risk Analytics brought the sophistication of what we were doing to a new level, which resulted in greater trust in the data and better overall portfolio management.” Johnathan Crist, CFA FRM | Sr. Investment Analyst, Georgia Tech Foundation, Inc. |
Solovis had been prototyping risk algorithms and code in collaboration with Georgia Tech Foundation for much of 2019. An iterative approach was used where features such as scenario analysis and risk proxies for illiquid assets were developed and then beta-tested with Georgia Tech Foundation. But then as a front-end for its risk application was still under development, the COVID-19 crisis hit. Georgia Tech Foundation did not have time to wait for the final product. It needed risk answers right then.
For those stressful several weeks, Solovis delivered Georgia Tech Foundation regular risk reports using its already developed risk engine code and Excel spreadsheets. These reports included up-to-date information on its portfolio’s volatility, factor exposures, major risk contributors, and the projected impact of further economic shocks.
“No one is ever truly 100% prepared for the type of event that occurred in February and March of 2020,” Crist said. “This was especially true as we were not quite at a final stage of having the risk platform up and running. Regardless of how far along the project was, the data was vital to the circumstances. It was crucial to understand how our portfolio was positioned, both as the market sold off and in the subsequent rebound.”
“The events in February and March of 2020 ended up pushing the project along quicker,” said Crist. “It provided great fact checking for the parameters and proxies we were assigning to different parts of our portfolio. We were going through a live stress scenario that we could use to compare to what we were seeing in the hypothetical scenarios in Solovis Risk Analytics. Calibrating the model to the true output occurring in markets allowed us to ultimately gain confidence in the data going forward.”
In the fall of 2020, Solovis completed the front-end of the new Risk Analytics application. Fully integrated with Solovis Portfolio Analytics and accessible on-demand, Georgia Tech Foundation could finally move off spreadsheets for good.
Today, Georgia Tech Foundation remains a happy Solovis Risk Analytics client. Every week, Georgia Tech Foundation uses Solovis Risk Analytics to monitor its risk and portfolio exposures. Weekly conference calls with Solovis’ R&D team (the team that built the Risk Analytics application) are used to stay on top of things from both an investment risk and modeling perspective. “Like the relationship we have with Solovis on the Portfolio Analytics side, the Risk Analytics team has become an extension of our staff,” said Crist. “Our weekly calls go beyond just updates on the application, but they cover all topics around risk management from best practices, to future implementation considerations and topical current events. Very rarely do you encounter a team as open to conversation and suggestions as the Risk Analytics team at Solovis.”
One thing in particular that Georgia Tech Foundation likes about its partnership with Solovis is that it extends beyond a simple software vendor-client relationship. To Georgia Tech Foundation, Solovis is more research partner than vendor. And to Solovis, Georgia Tech Foundation is an ideation partner and sounding board. For example, during the fall of 2020, when Georgia Tech Foundation was interested in better understanding its exposure to nonlinear equity volatility, Solovis’ R&D team helped develop several new volatility-specific factors that are currently used to augment Georgia Tech Foundation’s base risk factor model.