Optimal Pacing for Private Assets: An Example

The FRG Private Capital Forecasting (PCF) solution recently released a module for optimal pacing.  Pacing refers to the planning of future commitments. Future commitments encompass a decision on commitment size as well as a decision on commitment timing. This is done to help balance a portfolio’s needs to achieve or maintain allocations to private capital vehicles.

Creation of pacing plans is not straightforward. The plan should consider not just the allocations to private asset classes, but to other asset classes as well. It also needs to balance these commitments with liquidity constraints and the need to keep all asset classes from breaching risk limits.

The Pacing Module combines the class-leading PCF forecasting simulation with stated portfolio goals for allocation and limits with a non-linear optimizer to create optimal pacing plans.

This blog posts walks through an example pension fund that is in a net distribution scenario.  They are actively selling down the portfolio to fund retirements. Further, they have only recently begun to invest in private capital. Their allocations are low and need to be brought up to target.

PCF has been configured with this information. The fund manager has specified semi-annual rebalancing for the public side of the portfolio.

The simulation will run through 2027 and the plan will be created for vintage years 2020 – 2024.  Investments will be planned in the sub-asset classes of Private Equity (Buyout and Fund of Funds), Real Estate, and Venture.

The fund is experiencing outflows.  Overall NAV of the portfolio is declining.

Charts showing allocation and NAV

 

The first graph shows the expected cash needs per quarter to fund employee retirements.  This represents cash leaving the portfolio and leading to a decline in total NAV.

The second chart shows the NAV growing out of the pandemic recession and then beginning to decline as cash requirements outstrip fund growth.  The mean and inner quartile range from the simulation are plotted.

Because NAV of the portfolio is declining pacing is extremely challenging. Investing too much risks an illiquid portfolio, unable to be sold to meet retiree needs.  Investing too little might mean that the portfolio does not reach its allocation target and undershoots the expected return.  The portfolio manager is in a bind.

Graphs shows portfolio allocation total before PCF optimization

The fund is underweight to private assets.  The manager needs to build the portfolio allocation to meet the expected return target, but as stated above, investing too much could cause liquidity problems down the road.

The Pacing module takes the simulation of the portfolio and optimally chooses which and how much vintages to invest in.  Once the optimization has been run, we can see the allocations through time are better in line with the targets:

Chart showing improved allocations after optimization has been run.

 

If you would like more information about VOR Private Capital Forecasting or the VOR Pacing Optimization Module, please download our white papers here or reach out to Dominic Pazzula.

Dominic Pazzula is FRG’s Director of Risk and Asset Allocation. He is a specialist in investment management, asset allocation, portfolio construction, and risk management. 

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.

How COVID-19 Could Affect Private Capital Investors

A new blog by Preqin explores what COVID-19 could mean for private capital investors.

FRG and Preqin, an industry-leading provider of data, analytics and insights for the alternative assets community, partnered to develop a novel cash flow prediction model. The model is guided by FRG’s innovative methodology and powered by Preqin’s fund-level cash flow data.

Analysts used this tool in conjunction with the release of FRG’s Pandemic Economic Scenario to assess the impact of a recession triggered by the novel coronavirus on capital calls, distributions and net cash flows.

In the blog, Preqin’s Jonathon Furer examines an analysis created by FRG.  Jonathon explores the pandemic’s effect focused on 2017-2019 vintage funds, which represent 72% of the $2.63tn in callable dry powder that the private capital industry has raised since 2000. “Assuming the global economy undergoes a significant but brief recession, and then recovers, our model suggests GPs will respond in two stages,” Furer writes.

Read about the projected stages in the full analysis, Why COVID-19 Means Investors Should Expect Lower Capital Calls and Distributions in 2020.

FRG has 20+ years of experience applying stress testing to portfolios for banks and asset allocators. We developed this unique model enabling investors to stress test private capital portfolios for a wide range of macroeconomic shocks. We are ready to help investors looking to better understand portfolio dynamics for capital planning and pacing, or risk control for a black swan event.

Download the Pandemic Economic Scenario or get in contact with Preqin at info@preqin.com for the most accurate private capital cash flow forecasting model.

If FRG can help you better understand the effects of macroeconomic shocks on your private capital portfolios, contact us at info@frgrisk.com.

 

 

 

 

 

Stress Testing Private Equity


FRG, partnered with Preqin, has developed a system for simulating cash flows for private capital investments (PCF).  PCF allows the analyst to change assumptions about future economic scenarios and investigate the changes in the output cash flows.  This post will pick a Venture fund, shock the economy for a mild recession in the following quarters, and view the change in cash flow projections.

FRG develops scenarios for our clients.  Our most often used scenarios are the “Growth” or “Base” scenario, and the “Recession” scenario.  Both scenarios are based on the Federal Reserve’s CCAR scenarios “Base” and “Adverse”, published yearly and used for banking stress tests.

The “Growth” scenario (using the FED “Base” scenario) assumes economic growth more or less in line with recent experience.

The “Recession” scenario (FED “Adverse”) contains a mild recession starting late 2019, bottoming in Q2 2020.  GDP recovers back to its starting value in Q2 2021.  The recovery back to trend line (potential) GDP goes through Q2 2023.

Real GPD Growth chart

 

The economic drawdown is mild, the economy only loses 1.4% from the high.

Start DateTrough DateRecovery DateFull PotentialDepth
Q4 2019Q2 2020Q2 2021Q2 2023-1.4%

Equity market returns are a strong driver of performance in private capital.  The total equity market returns in the scenarios include a 34% drawdown in the index.  The market fully bottoms in Q1 2022, and has recovered to new highs by Q1 2023.

This draw down is shallow compared to previous history and the recovery period shorter:

Begin DateTrough DateRecovery DateDepthTotal LengthTrough Recovery
06/30/200009/30/200212/31/2006-47%271017
12/31/200703/31/200903/31/2013-49%22616
12/31/201903/31/202203/31/2024-34%18108

The .COM and Global Financial Crisis (GFC) recessions took off nearly 50% of the market value.  This recession only draws down 34%.  The time from the peak to the trough is 10 and 6 quarters for the .COM and GCF respectively.  Here we are inline with the .COM crash with a 10-quarter peak to trough period.  This recovery is faster by nearly double than either of the recent large drawdowns at 8 quarters versus 17 and 16.

We start by picking a 2016 vintage venture capital fund.  This fund has called around 89% of its committed capital, has an RVPI of 0.85 and currently sports about an 18% IRR.  For this exercise, we assume a $10,000,000 commitment.

Feeding the two scenarios, this fund, and a few other estimates into the PCF engine, we can see a dramatic shift in expected J-curve.

Under the “Growth” scenario, the fund’s payback date (date where total cash flow is positive) is Q1 2023.  The recession prolongs the payback period, with the expected payback date being Q3 2025, an additional 2.5 years.  Further, the total cash returned to investors is much lower.

This lower cash returned as well as the lengthening of the payback period have a dramatic effect on the fund IRR.

That small recession drops the expected IRR of the fund a full 7% annualized.  The distribution shown in the box and whisker plot above illustrates the dramatic shift in possible outcomes.  Whereas before, there were only a few scenarios where the fund returned a negative IRR, in the recession nearly a quarter of all scenarios produced a negative return.  There are more than a few cases where the fund’s IRR is well below -10% annually!

This type of analysis should provide investors in private capital food for thought.  How well do your return expectations hold up during an economic slowdown?  What does the distribution of expected cash flows and returns tell you about the risk in your portfolio?

At FRG, we specialize in helping people answer these questions.  If you would like to learn more, please visit www.frgrisk.com/vor-pcf  or contact us.

Dominic Pazzula is a Director with FRG, specializing in asset allocation and risk management. He has more than 15 years of experience evaluating risk at a portfolio level and managing asset allocation funds. He is responsible for product design of FRG’s asset allocation software offerings and consults with clients helping to apply the latest technologies to solve their risk, reporting, and allocation challenges.

 

 

Does the Liquidity Risk Premium Still Exist in Private Equity?

FRG has recently been investigating the dynamics of the private capital markets.  Our work has led us to a ground-breaking product designed to help allocators evaluate potential cash flows, risks, and plan future commitments to private capital.  You can learn more here and read about our modeling efforts in our white paper, “Macroeconomic Effects On The Modeling of Private Capital Cash Flows.”

As mentioned in a previous post, we are investigating the effects of available liquidity in the private capital market.  This leads to an obvious question: Does the Liquidity Risk Premium Still Exist in Private Equity?

It is assumed by most in the space that the answer is “Yes.”  Excess returns provided by private funds are attributable to reduced liquidity.  Lock up periods of 10+ years allow managers to find investments that would not be possible otherwise.  This premium is HIGHLY attractive in a world of low rates and cyclically high public equity valuations.  Where else can a pension or endowment find the rates of return required?

If the answer is, “No,” then Houston, we have a problem.  Money continues to flow into PE at a high rate.  A recent article in the FT (quoting data from FRG partner Preqin) show there is nearly $1.5 trillion in dry powder.  Factoring in leverage, there could be, in excess of, $5 trillion in capital waiting to be deployed.  In the case of a “No” answer, return chasing could have gone too far, too fast.

As mentioned, leverage in private capital funds is large and maybe growing larger.  If the liquidity risk premium has been bid away, what investors are left with may very well be just leveraged market risk.  What is assumed to be high alpha/low beta, might, in fact, be low alpha/high beta.  This has massive implications for asset allocation.

We are attempting to get our heads around this problem in order to help our clients understand the risk associated with their portfolios.

 

Dominic Pazzula is a Director with the Financial Risk Group specializing in asset allocation and risk management.  He has more than 15 years of experience evaluating risk at a portfolio level and managing asset allocation funds.  He is responsible for product design of FRG’s asset allocation software offerings and consults with clients helping to apply the latest technologies to solve their risk, reporting, and allocation challenges.

 

 

 

 

 

Private Equity and Debt Liquidity, the “Secondary” Market

A significant consideration in several aspects of Private Equity and Private Debt has been attributed to the liquidity (or lack thereof) of these investments.  The liquidity factor has been cited as a basic investment decision, influencing complex pricing, return of investment and financial risk management.  But as the environment has changed and matured, is liquidity being considered as it should be?

FRG’s ongoing research suggests that some of the changes this asset class are experiencing may be attributable to changes in the liquidity profile of these investments, which in turn may affect asset management decisions.  As modeling techniques continue to evolve in the asset management space, illustrated in our recent paper Macroeconomic Effects On The Modeling of Private Capital Cash Flows, their use as both an asset management tool and a risk management tool become more valuable.

The extreme importance placed on liquidity risk for all types of financial investments, and the financial community in general, to this point in time have been primarily associated with public investments.  However, a burgeoning “secondary” market in Private Equity and Private Debt will change the liquidity consideration of this asset class, a better understanding of which is necessary for investment managers active in this space.  Achieving this understanding will in turn provide private equity and private debt investment managers with another perspective with which to assess management decision aligning a bit more with that traditionally available for public investments. FRG is refining research into the liquidity of Private Capital investments through an appreciation of the dynamics of the environment to provide a better understanding of the behavior of these investments. Watch for more from us on this intriguing subject.

Read more about FRG’s work in Private Capital Forecasting via the VOR platform.

Dr. Jimmie Lenz is a Principal with the Financial Risk Group and teaches Finance at the University of South Carolina.  He has 30 years of experience in financial services, including roles as Chief Risk Officer, Chief Credit Officer, and Head of Predictive Analytics at one of the largest brokerage firms and Wealth Management groups in the U.S.

Forecasting Capital Calls and Distributions

Early in his career, one of us was responsible for cash flow forecasting and liquidity management at a large multiline insurance company. We gathered extensive historical data on daily concentration bank deposits, withdrawals, and balances and developed an elementary but fairly effective model. Because insurance companies receive premium payments from and pay claims to many thousands of individuals and small companies, we found we could base reasonably accurate forecasts on the quarter of the year, month of the quarter, week of the month, and day of the week, taking holidays into account. This rough-and-ready approach enabled the money market traders to minimize overnight balances, make investment decisions early in the morning, and substantially extend the average maturity of their portfolios. It was an object lesson in the value of proactive cash management.

It is not such a trivial matter for investors in private capital funds to forecast the timing and amount of capital calls and distributions. Yet maintaining adequate liquidity to meet obligations as they arise means accepting either a market risk or an opportunity cost that might be avoided. The market risk comes from holding domestic large-cap stocks that will have to be sold quickly, whatever the prevailing price, when a capital commitment is unexpectedly drawn down; the opportunity cost comes from adopting a defensive posture and holding cash or cash equivalents in excess of the amount needed for ongoing operations, especially when short-term interest rates are very low.

FRG is undertaking a financial modeling project aimed at forecasting capital calls and distributions. Our overall objective is to help investors with outstanding commitments escape the unattractive alternatives of holding excess cash or scrambling to liquidate assets to meet contractual obligations whose timing and amount are uncertain. To that end, we seek to assist in quantifying the risks associated with allocation weights and to understand the probability of future commitments so as to keep the total portfolio invested in line with those weights.

In other words, we want to make proactive cash management possible for private fund investors.

As a first step, we have formulated some questions.

  1. How do we model the timing and amount of capital calls and disbursements? Are there exogenous variables with predictive power?
  2. How do the timing of capital calls and disbursements correlate between funds of different vintages and underlying types (e.g., private equity from venture capital to leveraged buyouts, private credit, and real estate, among others)?
  3. Do private funds’ capital calls and distributions correlate with public companies’ capital issuance and dividend payout decisions?
  4. How do we model the growth of invested capital? What best explains the returns achieved before money is returned to LPs?
  5. What triggers distributions? 
  6. How do we allocate money to private funds keeping an eye on total invested capital vs. asset allocation weights?
    • The timing of capital calls and distributions is probabilistic (from #1). 
    • Diversification among funds can produce a smooth invested capital profile.  But we need to know how these funds co-move to create distributions around that profile (from #2).
    • Confounding problem is the growth of invested capital (from #3).  This growth affects total portfolio value and the asset allocation weights.  If total exposure is constrained, what is the probability of breaching those constraints?

We invite front-line investors in limited partnerships and similar vehicles to join the discussion. We would welcome and appreciate your input on the conceptual questions. Please contact Dominic Pazzula at info@frgrisk.com if you have an interest in this topic.

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