During the pandemic crisis, secondaries buyers who did not account for the slowdown in post-account activity might have overpaid for some portfolios in the market. Data-driven approaches can provide additional important insights when buying, selling, or when managing the cash-flows of a private equity program.
The most traditional type of deal in the private equity secondaries market consists of situations where a limited partner (such as a pension plan, family office, or fund-of-funds) wishes to sell a portfolio of commitments in private equity funds. These portfolios can be very diversified with sometimes up to 100 different private equity funds.
The usual strategy for a seller consists of hiring an advisor to organize the sale through an auction process. This allows the seller to maximize the price and minimize the risks related to execution and compliance.
These processes tend to take a few months. The buyers are invited to submit bids based on the accounts received for a certain date (the “reference date”). Once the auction is completed, the seller will transfer the interests to the buyer at closing.
Between the reference and the closing date, the underlying funds keep on calling capital and distributing proceeds from their realized assets. These intermediary cash-flows are called post-account movements or netting. Netting has an impact on the final price paid by the buyer and therefore on the returns.
It is crucial for buyers and sellers to model these cash-flows accurately to ensure an adequate clearing price for the transaction.
The impact of netting on returns
When looking at mature portfolios of LP interests, netting impacts on the three key metrics of a deal. It inflates the money-multiple (MoM), the internal rate of return (IRR), and the roll-forward discount (the actual discount at closing).
The below table provides a numerical example of the impact of netting. The pre-netting returns refer to the returns that a buyer would earn by acquiring the portfolio at par and transferring it at reference date.
In this example, we have assumed a portfolio with an annualized distribution rate of 35% of the opening NAV in the base case. We have also assumed 3 quarters between reference and closing date (it is usually between 2 and 3).
In the base case, the post-account movements have inflated the MoM by 0.08x, the IRR by c. 5%, and has generated a roll-forward discount of almost 20% at closing.
The impact of netting is further analyzed in the sensitivity table below where the stressed parameters are the price paid in percentage of the opening NAV (columns) and the level of distribution between reference date and closing date as an annualized percentage of the opening NAV (rows).
How to account for netting during a crisis
Understanding the impact of a crisis on the post-account movements is important both for the seller and the buyer as it can drive pricing down.
At RockSling Analytics, we use advanced computational methods to forecast the future capital calls and distributions of investments in private equity funds. Our machine learning algorithms rely on historical patterns and correlations between private equity assets and other asset classes. Our models can operate at the finest level of granularity using data about the underlying assets and portfolio companies.
During the pandemic crisis, buyers who did not account for the slowdown in post-account activity might have overpaid for some portfolios in the market. Data-driven approaches can provide additional important insights when buying, selling, or when managing the cash-flows of a private equity program.
We believe at RockSling Analytics that data-driven solutions can support your team by bringing additional insights about the trends and risks in your private equity program.
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