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Description of Neuberger Berman’s Proprietary Stochastic Model
Neuberger Berman Private Equity uses stochastic modeling capabilities to forecast capital call / distribution activity and Net Asset Value (“NAV”) development of private market investments. NB’s stochastic model uses a Monte Carlo Simulation, projecting, with varying levels of confidence, how a private markets portfolio of funds, co-investments and secondaries will develop over time. The model projects capital calls, distributions and NAV development based on asset class, current NAV, vintage year and drawn amount of each investment in the portfolio, as well as additional (potential) future investments and commitments.
The input and assumptions used in the model are based on information from Thomson Reuters’s Thomson ONE database covering 25 years of private equity industry data (cash flow, NAV development, etc.). Cash flows represent the pooled cash flows of all private equity funds that report performance data to Thomson Reuters and are net of all underlying fund fees and expenses. The industry performance assumptions used in the analysis are based on long-term averages from the Thomson ONE database, not on NB’s historical or projected returns. The inputs used within the model include the median historical net IRR, median historical yield, average holding period, mean and standard deviation of contributions for various private market asset classes (i.e., large-cap, small & mid-cap buyout, venture & growth capital, special situations, private credit, real estate and infrastructure debt) and strategies (i.e., primary fund investments, secondary fund investments, direct co-investments and direct credit investments). Yield is calculated as actual annualized cash coupon of current unrealized investments divided by current unrealized invested capital.
The assumptions are for illustrative purposes only and are not intended as a promise or prediction of performance. There can be no assurance that the fund will achieve comparable results, that targeted diversification or asset allocations will be met, that the fund will be able to or will ultimately elect to implement the assumptive investment strategy and approach described in the model. Alternative assumptions may result in significant differences or complete loss of capital in such projections.
Note, all targets and underlying assumptions can be adjusted if desired as requested by the client. There is no guarantee that returns targeted in any underwriting process will be realized or achieved or that an investment strategy will be successful, and actual returns may be significantly lower than the targeted returns referenced herein. Investors should keep in mind that the securities markets are volatile and unpredictable. There are no guarantees that the historical performance of an investment, portfolio, or asset class will have a direct correlation with its future performance.
Asset Class Assumptions & Estimates
Capital market assumptions used herein reflect Neuberger Berman’s forward-looking estimates of the benchmark return or volatility associated with an asset class. Estimated returns and volatilities are hypothetical return and risk estimates generated by Neuberger Berman’s Institutional Solutions Group. Estimated returns and volatilities do not reflect the alpha of any investment manager or investment strategy/vehicle within an asset class. Information is not intended to be representative of any investment product or strategy and does not reflect the fees and expenses associated with managing a portfolio or any other related charges, such as commissions and surrender charges. Estimated returns and volatilities are hypothetical and generated by Neuberger Berman based on various assumptions and inputs, including current market conditions, historical market conditions and subjective views and estimates. Capital market assumptions shown reflect Neuberger Berman’s long-term (20+ years into the future) estimates or intermediate-term (5-7 years into the future) estimates which are reviewed at least annually. Results will differ depending on whether they are based on Neuberger Berman’s long-term (20+ years into the future) or intermediate-term (5-7 years into the future) capital market assumptions. Neuberger Berman’s capital market assumptions are derived using a building block approach that reflects historical, current, and projected market environments, forward-looking trends of return drivers, and the historical relationships asset classes have to one another. These hypothetical returns are used for discussion purposes only and are not intended to represent, and should not be construed to represent, predictions of future rates of return. Actual returns may vary significantly. Neuberger Berman makes no representations regarding the reasonableness or completeness of any such assumptions and inputs. Assumptions, inputs, and estimates are periodically revised and subject to change without notice. Estimated returns and volatilities should not be used, or relied upon, to make investment decisions.
Rate of Return Estimate: Rate of return or geometric return is a measure of average returns of an investment over a period of time. Geometric rate of returns are typically referred to as annualized compound rate of returns and are always less than or equal to the arithmetic mean return of the same time series. Geometric rate of returns are used for straight-line calculations within the analysis, for example, the cash flow calculations. In straight-line calculations, each year is represented as a gain, so the compound (geometric mean) rate of return is used to adjust for the amount needed to make up for a loss in a given year. For example, if you lose 5% in one year, and gain 5% the year after, you still have less than you started with at the beginning of year one.
Arithmetic Mean Estimate: Arithmetic mean or average return is calculated by dividing the sum of a series of numbers by the number of overall items. This is more typically thought of as an “average” of the data set. Arithmetic mean or average return ignores the impact of compounding in the context of analyzing investment returns and is the simple average of returns observed over a period of time. Arithmetic mean returns are used in this material and, if applicable, the Efficient Frontier, because, through randomization, losses and gains are being accounted for each year.
Standard Deviation: A statistical measure of the volatility based on the distribution of a set of data from its mean (average value). For example, a portfolio with an average return of 10% and a standard deviation of 15% would return a result between -5% and +25% the majority of the time (68% probability or 1 standard deviation), almost all of the time the return would be between -20% and +40% (95% probability or 2 standard deviations). If there were 0 standard deviation then the result would always be 10%. Generally, more aggressive portfolios have a higher standard deviation and more conservative portfolios have a lower standard deviation.
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