Summary
An asset management firm’s Natural Capital Portfolio Management required a tool to advise on optimal portfolio allocations for their clients. The key goal was to develop a research tool that could devise optimal allocations by implementing traditional portfolio optimization methods to nascent assets based on a hypothetical investable universe encompassing a wide array of natural resources assets divided into Timberland investments and Farmland investments.
The Challenge
The Asset Management firm designed and implemented a MATLAB script based on constructing optimal global timberland investment portfolios. However, there were significant drawbacks of the model’s development including data availability on expected returns and volatility given the nascent nature of the assets included in the investable universes.
Our Solution
Using Modern Portfolio Theory (MPT) to estimate efficient frontiers and optimal allocations for assembling portfolios based on expected returns and volatility, has been widely discussed and implemented and is considered a key industry standard. Therefore, Evalueserve focused its efforts on validating the quality of inputs used by the model and assessing the source code used in MATLAB to produce the intended outputs of the model. To do so, an independent replication of the code was created, and multiple tests were applied to ensure that the code worked as intended, that appropriate automations were in place, and that the processing components of the model would be resilient to stress scenarios and sensitivity tests.
Business Impact
Portfolio allocation is particularly complicated when ESG factors are involved. The asset management firm needed to optimize allocation based on hypotheticals and required accurate data. Evalueserve’s evaluation of the model’s inputs and code ensured that the model was performing correctly and would be able to stand up to adverse factors.
Conclusion
Evalueserve played a crucial role in addressing an asset management firm's challenge of optimizing natural capital portfolio allocations. The firm aimed to develop a research tool for optimal portfolio allocation advice, focusing on nascent natural resource assets like Timberland and Farmland investments. While the firm had constructed a MATLAB script for global timberland investment portfolios, challenges existed due to limited data availability on expected returns and volatility. Evalueserve's contribution involved validating input quality, assessing MATLAB source code, and creating an independent code replication to ensure accurate outputs, resilience to stress scenarios, and sensitivity tests. This validation reassured the asset management firm that their portfolio allocation model, critical for ESG-informed decisions, would perform effectively under adverse conditions.
