A sustainable food and agricultural company in North America had previously engaged Sapling to develop an in-depth financial model outlining the operational and return metrics of opening a new farm. Following this, Sapling was re-engaged to build a Monte Carlo (MC) model simulating the return and probability of different strike prices for warrants that the client had purchased
Sapling researched statistical techniques to find the best probability distribution to match the MC model. Historical stock prices and volatilities of sector comparable were found as a baseline for model assumptions
Statistical certainty improves as one increases simulation sizes - Sapling was able to build a MC model in Excel and run 100,000 simulations to generate robust results
The Monte Carlo model was used to layer into an existing financial model detailing operational metrics that Sapling had built for the client
A B2B distributor selling to major retailers in the U.S. engaged Sapling to perform a sell-side Quality of Earnings review to support the planned sale of the business. The engagement focused on reconstructing and validating historical financial performance using transaction-level data, bank activity, inventory records,...
A heavy civil construction contractor running operations across several entities asked Sapling to build a management model that delivers private equity-level, best-in-class budgeting and scenario planning. The goal was a 3-statement model and dashboard that builds up from the project pipeline, so the team could...
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