1

State Street Expertise

Building A Better Risk Framework For Fitting

Private Equity Into Investment Portfolios

Private equity (PE) has been one of the

fastest-growing asset classes over the

last decade. For institutional investors

with long time horizons, harvesting

the illiquidity premium is an attractive

opportunity in a world of stretched

public equity valuations and negative

interest rates. But understanding how

to size the allocation and resolve the

different valuation, volatility and liquidity

characteristics of private versus public

equity has been a challenge for strategic

asset allocation. Until now. A group of

State Street researchers recently

launched a ground-breaking framework

for estimating both the systematic and

idiosyncratic risk of private equity

programs. Using an innovative

econometric technique and applying

it to State Street’s private equity flow

data, the researchers were able to

“unsmooth” the returns of private equity

to better compare them with public equity

returns. The results of their work were

recently published in The Journal of

Portfolio Management.1 Patricia Hudson,

our global head of thought leadership,

spoke to two of the authors about how

the framework can help asset allocators

better incorporate private equity into

their risk budgets. Her conversation with

Alex Rudin, State Street Global Advisors’

head of research for the Investment

Solutions Group, and Jason Mao,

manager of the State Street Private Equity

Index, digs deeper into their research.

BUILDING A BETTER RISK FRAMEWORK FOR FITTING

PRIVATE EQUITY INTO INVESTMENT PORTFOLIOS

2

1 Alexander Rudin, Jason Mao, Nan R. Zhang and Anne-Marie Fink, “Fitting Private Equity into the Total Portfolio Framework,” The Journal of Portfolio Management, November 2019.

3

Patricia HudsonGlobal Head of

Thought Leadership

Alex Rudin Head of Research for

State Street Global Advisors’

Investment Solutions Group

Jason Mao, CFAManager of State Street’s

Private Equity Index

4

Patricia: Why did you undertake

this research?

Alex: Our total-portfolio investment

teams were working on how to

incorporate private investments into

quantitative asset allocation models.

These models generally require return,

volatility and correlation inputs. Like

many allocators, we were adjusting

volatilities from observed levels

to compensate for the mismatch

between private investments’

quarterly-with-a-lag valuations and

publicly traded assets’ more frequent

and timely values. We wanted to look

at whether we could find a more

precise way to adjust private assets

and to build on prior academics’ work

that sought to “unsmooth” private

equity returns. We saw an opportunity

to advance the field because the

State Street Private Equity Index

database provided a previously

untapped advantage in undertaking

this research.

Patricia: What is the State Street

Private Equity Index, and why was it

so important to this research?

Jason: Within State Street’s custody

business, we have access to the

returns and cash flows of more than

3,000 private equity funds over almost

40 years. To create the State Street

Private Equity Index, we aggregate

the returns across all these funds and

publish aggregate returns on a quarterly

basis. Since our data comes directly

from owners, our index reflects the

actual experience of limited partners.

Our approach eliminates the survivorship

bias or other distortions that can come

when funds self-report returns.

Having access to this level of clean data

was enormously helpful to the research.

We were able to conduct numerous

tests, developing hypotheses and then

testing them on out-of-sample data.

Patricia: How did you manage the

research process?

Jason: Preserving clients’ confidentiality

is crucial to our custody business.

To ensure the integrity of all the

information, we established

a protocol whereby Alex never

saw individual fund data. Instead,

he would formulate queries, which

my colleague Nan and I would apply

against our fund returns. We also

anonymized all the individual fund

data to preserve confidentiality.

“We wanted to look at whether we could find a more precise way to adjust private assets and to build on prior academics’ work that sought to “unsmooth” private equity returns.”

Alex Rudin, Head of Research for State Street Global Advisors’ Investment Solutions Group

5

“Using the methodology we developed, it’s possible to unsmooth the return streams of private assets, making them more comparable to the returns of publicly traded assets. We then can use the unsmoothed returns to calculate expected returns, risks and correlations.”

Alex Rudin, Head of Research for State Street Global Advisors’ Investment Solutions Group

Patricia: What were the most important

insights from the research?

Alex: Our research generated

two main advances relative to prior

efforts to “unsmooth” returns, such

as the work in 2014 by Pedersen and

co-authors. The basic premise is that

the appraisal nature of private assets’

unrealized valuations is backward-

looking, relying on historic values, and

thus unnaturally smooth. The goal is to

“correct” for these biases, and extract

the true economic returns and volatility

of private assets through regression

techniques that compare returns

with prior period returns.

One of our advances was to develop

a formula that collapsed Pedersen’s

multi-part regression process into

a single regression that can identify

two unknown variables: the degree

of return smoothness and the degree

of correlation to public equity markets.

While our algorithm is somewhat

more complex, the single calculation

reduces the potential for compounding

estimation errors that can happen in

multiple-part calculations.

Second, because of the wealth of

fund data that we have, we were able

to examine the effect of various lags

on the robustness of our calculations.

Prior investigators have tended to use

upward of four lags when unsmoothing

returns. In effect, they assume that

private equity valuations reflect values

from the prior four quarters. By conducting

rigorous in-sample and out-of-sample

analysis, we determined that a one-lag

recipe was the most robust. Using

additional lags produced an unstable,

over-fitted solution. While the predictive

power of more lags worked better in

sample, the multi-lag forecasts fell

apart in out-of-sample tests.

Patricia: From an implementation

perspective, how does the research

help when it comes to incorporating

private investments into asset

allocation frameworks?

Alex: Using the methodology we

developed, it’s possible to unsmooth the

return streams of private assets, making

them more comparable to the returns of

publicly traded assets. We then can use

the unsmoothed returns to calculate

expected returns, risks and correlations.

Asset allocators then have quantitatively

derived inputs for their preferred asset

allocation model.

When we applied our methodology to the

overall State Street Buyout Index, we

found that the index has a 0.5 beta to the

S&P 500 and alpha of 460 basis points.

The unsmoothed volatility is 13.3 percent.

6

Patricia: Why did you compare private

equity to the S&P 500? Aren’t private

equity companies generally smaller,

more in line with small- or micro-cap

indices? Also, isn’t the State Street

Buyout Index global in nature?

Jason: Yes, the State Street Buyout

Index is global. We did calculate betas

for the unsmoothed index to both the

MSCI World and the Russell 3000.

The results were similar to those of the

S&P 500. We decided to quote the S&P

500 because it’s the standard reference

that most people use.

Patricia: Your risk statistics

are surprising low. Isn’t private equity

supposed to be riskier than public

equities? I’ve always thought of PE

as having a beta of more than one.

Jason: That’s the beauty of this

methodology. We are not guessing about

the volatilities and betas. We are letting

the actual results drive where we

come out.

Alex: Yes, too often when allocators

develop inputs for private assets in their

asset allocation models, they effectively

predetermine their asset allocation

decisions through the adjustments they

make to historic numbers. If you adjust

PE volatilities too high, then the process

will not allocate to the asset class

at all. Keep the volatilities too low, and

models will allocate 100 percent to PE.

We attempted to look at the realized

private equity fund data and allowed the

data to speak for itself.

Another advantage of this methodology

is that it gives allocators the tools to

make their private asset inputs consistent

with those of public assets. Traditionally

allocators use the risk-free rate and

the equity-risk premium to estimate

public equity returns thereby creating

consistency between their fixed income

and public equity predictions. Similarly,

if a forecaster expects large-cap equities

to diverge from historic returns, say to

generate a 6 percent return since

valuations are high and the risk-free rate

is low, it’s easy to estimate a comparable

10.5 percent expected return for private

equity (0.5 beta * 6 percent return +

4.5 percent alpha). If one estimates

go-forward S&P 500 volatility to be lower

than in the past, the historic relationship

of unsmoothed private equity having

two-thirds the volatility of public equity is

a useful guide to estimating PE volatility.

Patricia: How do you address

conventional concerns that private

equity is a levered and therefore

a riskier version of equity?

“We are not guessing about the volatilities and betas. We are letting the actual results drive where we come out.”

Jason Mao, Manager of State Street’s Private Equity Index

7

Alex: While it’s only briefly mentioned

in the paper, we have given considerable

thought to the disparity in volatility

between unsmoothed private equity

and public equity returns and believe the

difference is rooted in deeply fundamental

reasons. Ever since Robert Shiller came

up with the concept of “excess volatility,”

it has been understood that public equity

gyrations are driven partly by earnings

expectations and partly by psychological

phenomena such as anxiety, flows,

momentum, etc. Shiller called these

elements “excess volatility.”

It is self-evident that while private equity

valuation processes are designed to fully

reflect the earnings expectations of

underlying companies, they are far less

exposed to “excess volatility” than their

public counterparts. This insight helps

reconcile two observations seemingly

at odds with one another: our findings

that private equity has substantially

lower risk than that of public equity over

the short term and earlier findings by

other authors who witnessed public and

private equity performing roughly in line

over the very long term (10 plus years).

In the short term, the “excess volatility”

that dominates public markets does not

enter private equity valuations in a

material way. Conversely, over the very

long term, “excess volatility” washes

away and earnings are the only thing

that truly matter – making the long-term

results of public and private equity

investing similar to each other.

Patricia: How did your research help

the common challenges around sizing

an allocation to PE?

Jason: We used our extensive database

to build a series of “mini-programs,”

portfolios of a set number of equal-

weighted funds. We constructed 500

of these randomly selected programs

over 15 years, and ran simulations.

From this work, we developed a

methodology to estimate the tracking

errors and expected returns of each

program. We also built in the cost of

adding additional funds to a program,

since due diligence is not free.

Alex: With this research, we can advise

allocators, in an informed way, on how

to size their private equity programs,

incorporating their individual situations,

including risk tolerance and the cost of

adding additional funds.

To receive a reprint of Alex and Jason’s

Journal of Portfolio Management article,

please reach out to your State Street

relationship manager.

“With this research, we can advise allocators, in an informed way, on how to size their private equity programs, incorporating their individual situations, including risk tolerance and the cost of adding additional funds.”

Alex Rudin, Head of Research for State Street Global Advisors’ Investment Solutions Group

Important InformationAll information has been obtained from sources believed to be reliable, but its accuracy is not guaranteed. There is no representation or warranty as to the current accuracy, reliability or completeness of, nor liability for, decisions based on such information and it should not be relied on as such. Views and opinions are subject to change at any time based on market and other conditions. The whole or any part of this work may not be reproduced, copied or transmitted or any of its contents disclosed to third parties without State Street’s express written consent.

This document and information provided herein is for marketing and/or informational purposes only, it does not take into account any prospects or client's particular investment or other financial objectives or strategies nor any prospect or client's legal, regulatory, tax or accounting status, nor does it purport to be comprehensive nor intended to replace the exercise of a prospect or client's own careful independent review regarding any corresponding investment or other financial decision.

This document and information provided herein does not constitute investment, legal, regulatory, tax or accounting advice and is not a solicitation to buy or sell securities nor to enter into any transaction, nor is it intended

to constitute any binding contractual arrangement or commitment by State Street to provide securities services nor any other financial services. Any information provided has been obtained from sources believed to be reliable at the time of publication, nonetheless, we cannot guarantee nor do we make any representation or warranty as to their accuracy and you should not place any reliance on such information. This document and any comments and statements made herein do not necessarily reflect those of State Street, its subsidiaries or its affiliates. State Street hereby disclaims all liability, whether arising in contract, tort or otherwise, for any losses, liabilities, damages, expenses or costs arising, either direct or consequential, from or in connection with the use of or any reliance place upon any information provided.

This document and information provided herein is not intended for retail clients, nor for distribution to, and may not be relied upon by, any person or entity in any jurisdiction or country where such distribution or use would be contrary to applicable law or regulation.

©2019 State Street Corporation

All Rights Reserved

2856139.1.1.GBL.RTL

Expiration date: 11/30/2020

State Street CorporationOne Lincoln Street, Boston, MA 02110

statestreet.com