Macroeconomic Effects on the Modeling of Private Capital Cash Flows

The demand of private capital investing has investors clamoring for more information about prospective cash flows. Historically, that data has been hard to estimate. Because the investments aren’t traded on a public venue, there are few figures generated beyond the data received by existing investors.

So what’s an investor to do? FRG has developed a Private Capital Model solution that provides more insight and understanding of the probable cashflows, one that includes the macroeconomic variables that have been found to influence cash flows and significantly improve the forecasting probabilities. We have found those variables create a more complete picture than the Takahashi and Alexander model, commonly used within the industry to provide guidance around cash flows.

Three of FRG’s modeling and investment experts – Dr. Jimmie Lenz, Dominic Pazzula and Jonathan Leonardelli – have written a new white paper detailing the methodology used to create the Private Capital Model, and the results the model provides. Download the paper, “Macroeconomic Effects on the Modeling of Private Capital Cash Flows” from the Resources section of the FRG website. Interested in a perspective on an investor’s need and utilization of cash flow information? Download FRG’s first Private Capital Fund Cash Flows paper.

Quantifying the Value of Electricity Storage

ABSTRACT: This research discusses the methodology developed to hedge volatility or identify opportunities resulting from what is normally a discussion constrained to the capital markets.  However, the demand (and the associated volatility) for electricity in the United States has never been more pronounced.  The upcoming paper, “Quantifying the Value of Electricity Storage,” will examine the factors that have led to the growth of volatility, both realized and potential.

There is widespread recognition of the value of energy storage, and new technologies promise to expand this capability for those who understand the opportunities being presented to firms involved in different areas of electricity generation. Objective tools to valuate these options, though, have been limited, as has the insight into when mitigation efforts make economic sense.

In order to answer these questions for electricity generators of all types we have created an economics-based model to address the initial acquisition of storage capacity, as well as the deployment optimization solutions, based on the unique attributes of the population served.

Links to the paper will be posted on FRG’s social media channels.

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 if you have an interest in this topic.

Risk Premia Portfolio Case Study

See how FRG’s VOR (Visualization of Risk) platform works for a major U.S. foundation: download a case study that explores how we customized VOR application tools to help them with their day-to-day portfolio management activities, as well as their monthly analysis and performance reporting.

The study shows how FRG was able to leverage its econometric expertise, system development capability and logistical strength to empower the foundation’s specialized investment team. Read the study, and learn more about VOR, here.

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