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.

 

 

 

 

 

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?
    1. The timing of capital calls and distributions is probabilistic (from #1). 
    2. 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).
    3. 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.

The Case for Outsourced Hosting

Middle office jobs are fascinating. In performance analysis, spotting dubious returns and tracing them back to questionable inputs requires insight that seems intuitive or innate but results in fact from a keen understanding of markets, asset classes, investment strategies, security characteristics, and portfolio dynamics. Risk management additionally calls for imagination in scenario forecasting, math and programming skills in model development, judgment in prioritizing and mitigating identified risks, and managerial ability in monitoring exposures that continually shift with market movements and the firm’s portfolio decisions. Few careers so completely engage such a wide range of talents.

Less rewarding is handling the voluminous information that feeds the performance measurement system and risk management models. Financial data management is challenging for small banks and investment managers, and it becomes more and more difficult as the business grows organically, adding new accounts, entering new markets, and implementing new strategies that often use derivatives. Not to mention the extreme data integration issues that stem from business combinations!

And data management hasn’t any upside: nobody in your chain of command notices when it’s going well, and everyone reacts when it fails.

Nonetheless, reliable data is vital for informative performance evaluation and effective risk management, especially at the enterprise level. It doesn’t matter how hard it is to collect, format, sort, and reconcile the data from custodians and market data services as well as your firm’s own systems (all too often including spreadsheets) in multiple departments. Without timely, accurate, properly classified information on all the firm’s long and short positions across asset classes, markets, portfolios, issuers, and counterparties, you can’t know where you stand. You can’t answer questions. You can’t do your job.

Adding up the direct, explicit costs of managing data internally is a straightforward exercise; the general ledger keeps track of license fees. The indirect, implicit costs are less transparent. For example, they include the portion of IT, accounting, and administrative salaries and benefits attributable to mapping data to the performance measurement system and the risk models, coding multiple interfaces, maintaining the stress testing environment, correcting security identifiers and input errors—all the time-consuming details that go into supporting the middle office. The indirect costs also include ongoing managerial attention and the potential economic impact of mistakes that are inevitable if your company does not have adequate staffing and well-documented, repeatable, auditable processes in place to support smooth performance measurement and risk management operations.

You can’t delegate responsibility for the integrity of the raw input data provided by your firm’s front office, portfolio assistants, traders, and security accountants. But you can outsource the processing of that data to a proven provider of hosting services. And then your analysts can focus on the things they do best—not managing data but evaluating investment results and enterprise risk.

Learn more about FRG’s Hosting Services here.

Spreadsheet Risk Is Career Risk

Stop and think: how much does your firm — and your work group — depend upon electronic spreadsheets to get mission-critical assignments done? How badly could a spreadsheet error damage your company’s reputation? Its financial results? Your own career?

Here’s an example. Advising Tibco Software on its sale to Vista Equity Partners, Goldman Sachs used a spreadsheet that overstated its client’s shares outstanding and, as a result, overvalued the company by $100 million. The Wall Street Journal reported, “It’s not clear who created the spreadsheet. Representatives for Tibco and Goldman declined to comment. Vista couldn’t be reached for comment.” (October 16, 2014.) Nonetheless, it’s safe to assume that the analyst who prepared the spreadsheet was identified, along with his or her manager, and that they both were penalized for the mistake.

Spreadsheets proliferate in financial organizations for good reasons. They offer convenient, flexible, and surprisingly powerful ad hoc solutions to all sorts of analytical problems. But as risk managers we are an impatient lot, and all too often results-oriented people like us turn to spreadsheets even for production applications because we cannot wait for IT resources to become available. We know that the IT department has a hard-and-fast policy of disavowing the business lines’ spreadsheets, but that’s all right, we tell ourselves, because “it’s only temporary.” Then we turn our attention to another problem….

Let’s take it as axiomatic that the firm’s risk management operations should not exacerbate the firm’s exposure to operational risk.

You may already have established some controls to mitigate spreadsheet risk in production applications. For example, key spreadsheets may be encrypted, stored on dedicated, non-networked PCs with password protection, and backed up every night. And it might be said that spreadsheets are self-documenting because the macros and formulas are visible and the functions are vendor-defined. As a practical matter, however, only the analyst who originally developed a spreadsheet fully understands it. When she leaves, and other analysts add enhancements — possibly with new names for existing variables — the spreadsheet becomes much more difficult to troubleshoot.

We recommend taking these steps now:

  • Starting in the risk management area, inventory all the spreadsheets in use across the firm’s operations.
  • Confirm that every time a spreadsheet enters a workflow it is identified as such. Cross-check the workflow documentation and swim lane diagrams against the spreadsheet inventory and update them where necessary.
  • Document every non-trivial spreadsheet, minimally including its purpose, the data sources, and any procedural tips.
  • Select the operationally embedded spreadsheets whose failure would be most injurious to departmental objectives and downstream processes, and look for permanent solutions with proper controls.

Whether or not it’s explicitly listed in your performance objectives, you owe it to your firm and yourself to migrate mission-critical spreadsheet applications to a reliable platform with codified controls. Systems development life cycle (SDLC) methodologies impose the discipline that’s needed in all phases of the project, from requirements analysis through deployment and maintenance, to minimize operational risk. This is not a trivial task; transferring the ad hoc functionality you currently have embedded in spreadsheets to a system that is well designed and amply supported takes heart. But the potential consequences of inaction are unacceptable. We strongly encourage you to take the necessary steps before a problem comes to light because a key person leaves the organization, a client spots a costly mistake, or — in the worst case — an operational crisis prevents the firm from meeting its contractual or regulatory obligations. And you lose your job.

 

Click here for information about FRG’s state-of-the-art risk modeling services and here for information about our hosting services.      

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