Model Updates for FRG’s VOR PCF Ensure Continuous Improvement

FRG regularly launches new models that will enhance the predictive capability of our VOR Private Capital Forecasting (PCF) solution. Together with our partner Preqin, FRG launched PCF last year to help private capital investors better forecast cash flows. Since then, behind the scenes our Business Analytics team has been hard at work fine-tuning the models used to analyze the probability distribution of cash flows generated by private capital investments.

PCF uses next-generation modeling techniques allowing us to incorporate macro-economic data into cash flow models to better forecast the timing and magnitude of Capital Calls and Capital Distributions. This gives our clients the ability to stress test their portfolios for different economic scenarios.

FRG uses four models to forecast the cash flows important for private equity funds:

  • Probability of Call
  • Probability of Distribution
  • Size of the Call
  • Size of the Distribution

The models are assessed for fit and robustness quarterly, when data updates from Preqin are incorporated. But our team of data scientists is always working to make them better and more predictive.

Throughout the past year the team has specifically refitted the models to remove LIBOR dependent variables, recognizing that LIBOR availability will not be guaranteed past 2021. We further refined the models with our goal to improve the new models’ out of sample performance relative to the current models. Our model approval committee has concluded that these current models, like their predecessors, continue to outperform the Takahashi Alexander (Yale) model consistently for all vintages dating back more than 20 years.

For more information on our PCF tool, please visit our website.