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State Street Associates

State Street Securities Finance

JANUARY 2013

Securities Lending: Assessing Portfolio Risk and Return

Securities Lending and the Asset-Liability Framework

The Loan Balance-at-Risk: An Empirical Look at Borrower Demand and its

Impact on the Size of the Loan Portfolio

The Cash Collateral Reinvestment Portfolio and the Importance of “Fat Tail”

Risk

Quantifying Product Risk to Aid the Institutional Investor in More Efficiently

Structuring its Securities Lending Program

State Street Associates

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State Street Associates, is creating a full

spectrum of proprietary investor behavior

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and advisory research services.

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State Street Global Markets provides

specialized research, trading, securities

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strategies to owners and managers of

institutional assets.

Authors – State Street Associates

David Chua, PhD

[email protected]

Hans-Christian Lüdemann, PhD

[email protected]

Authors – State Street Securities

Finance

Crossan Barnes

[email protected]

Leslie Levine, CFA

[email protected]

Glenn Horner, CFA, FRM

[email protected]

Jeffrey Trencher, CFA

[email protected]

Please refer to the Appendix for

important legal information.

mailto:[email protected]





2

STATE STREET ASSOCIATES

STATE STREET SECURITIES FINANCE

Contents

Executive Summary p. 3

Securities Lending: A Brief Overview p. 4

The Relationship Between the Loan and Collateral Portfolios p. 5

The Loan Portfolio: Balance-at-Risk p. 7

Collateral Reinvestment p. 9

Summary p. 13

Appendix p. 14

3



EXECUTIVE SUMMARY

The financial crisis of 2008 provided evidence of the effects of some well-known risks within securities lending programs. Most

obvious was the potential exposure that could result from a borrower default, such as Lehman Brothers. The crisis also

highlighted the potential impact of a default by an issuer of a security within a collateral reinvestment pool and the effects on

reinvestment net asset values that may result from widening credit spreads. However, one previously underestimated risk for

securities lenders that crystallized during late 2008 and early 2009 was liquidity risk.

During the financial crisis, equity markets declined by more than 40 percent,1 requiring lenders to return substantial amounts of

cash collateral to borrowers through the daily mark-to-market process. Typically, mark-to-market requirements were (and are

today) met with cash from maturing securities priced near par. As these securities became a lesser portion of the reinvestment

pools in 2008 and 2009, other securities that had declined in value had a more pronounced impact on the collateral pools’ total

net asset values. Moreover, the maturing liquidity within some lenders’ reinvestment pools was insufficient to meet required mark-

to-markets. These lenders then may have been faced with the difficult choice of either lending additional securities at unattractive

rebate rates and/or realizing losses from the sale of reinvestment assets that had declined in value due to widening credit

spreads.

Securities lending offers institutions an opportunity to generate additional income from their portfolios. That said, any discussion

regarding the desirability of participating in a securities lending program must include a thoughtful dialogue about program risks

and their role in producing income. We endeavor herein to further delineate and quantify the investment risk for lenders, focusing

on the asset-liability framework integral to any lending program for which cash collateral is accepted and reinvested.

We begin with a brief overview of the securities lending relationship from the institutional lender’s perspective. Thereafter, we

study the interaction between the components of a lender’s integrated portfolio. For the purpose of this paper, we focus on an

integrated portfolio comprised of a portfolio of loaned securities for which the lender receives cash collateral and a corresponding

collateral reinvestment portfolio.

Fluctuations in the value of the loan portfolio are driven by a multitude of factors, including the market prices for the loaned

securities, the demand to borrow these securities, underlying portfolio changes and the lender’s overarching lending program

guidelines. All of these elements determine a lender’s Loan Portfolio Balance-at-Risk.

Fluctuations in the value of the collateral reinvestment portfolio are driven by a variety of factors. In this paper we focus on the

impact of interest rate and spread changes and we highlight the need to properly consider the potential for rare but large tail

losses in the context of a cash collateral reinvestment portfolio.

Tying these two major elements together, we conclude that understanding and evaluating the characteristics of the lendable

asset base can help lenders better define the credit and maturity profile of their cash collateral portfolios.

1 The S&P 500, for example, fell from a value of 1,192.70 on September 15, 2008 to 676.53 on March 9, 2009, for a cumulative return of -43.3 percent.

4



SECURITIES LENDING: A BRIEF OVERVIEW

Securities lending offers an opportunity for institutional investors to derive incremental income from the securities in their

portfolios by making these holdings available for loan. In a securities-lending transaction, a beneficial owner of securities acts as

a lender and temporarily transfers securities to another investor acting as a borrower.

An investor may seek to borrow securities for a variety of reasons, each of which ultimately involves the need to deliver a security

the investor does not have in its possession. Reasons to borrow include the requirement to deliver a sold security it has not

received, such as from a failed purchase, to create a short position in a security or as part of a financing strategy.

In exchange for the securities loan, the borrower delivers to the lender (or its agent) collateral plus margin, generally ranging

between 102 percent and 105 percent. The dollar amount of the margin is adjusted daily in response to price movements of the

loaned securities. The lender can terminate the loan in accordance with the contract specific to the securities loan, generally a

standard settlement cycle based on contractual obligations of the borrower.

Depending on the type of collateral delivered, lenders may earn income in two ways:

When a lender accepts cash collateral, the lender reinvests the cash, typically in a short-term fixed income portfolio, and captures

the yield of this portfolio. Borrowers, in turn, demand payment of interest on the cash they post as collateral. This interest is called

a rebate and its rate is specific for each securities loan transaction. The demand for borrowing said security may be driven by a

variety of factors including settlement needs, tax considerations, merger and acquisition or capital raising activity, short interest or

other arbitrage activity, and by its lendable supply. Note that in the current near 0 percent rate environment many loans are priced

with negative rebate rates that actually represent interest received from borrowers. The lender earns income according to the

difference between the earnings from the collateral reinvestment portfolio and the rebate paid to borrowers. A sample transaction

is outlined in the Appendix in Figure A-1.

When non-cash collateral is posted, the borrower pays a fee to the lender. Similar to the rebate rate, this fee is based on the

demand for borrowing a given security and its supply.

Typically, asset holders contract with an external service provider such as a master custodian or an unaffiliated lending agent to

manage the process of lending securities and reinvesting cash collateral. The revenue generated from lending securities is split

between the lender and the lending agent at a predetermined rate.

5



THE RELATIONSHIP BETWEEN THE LOAN AND COLLATERAL PORTFOLIOS

An important part of the risk management process in securities lending is managing the relationship between the loan portfolio,

i.e., the liabilities, and the reinvestment portfolio, i.e., the assets.2 This relationship must be managed from both an interest rate

and liquidity perspective. Historically, much of the industry’s attention was directed toward managing the interest rate relationship

between the loan and reinvestment portfolios, particularly during periods of volatile and/or changing interest rate levels. Said

otherwise, participants focused on ensuring the yield of the collateral portfolio exceeded the rebate rate to be paid, while still

managing the reinvestment portfolio within guidelines. Although always important, the liquidity interrelationship of the two

portfolios did not attract substantial concern prior to the financial crisis of 2007-2008. Beginning at that time, however, declining

equity values, reduced borrowing demand, uncertain participation by asset holders and illiquidity in the short-term fixed income

market strained the liquidity of cash reinvestment pools just when the prices of the pools’ underlying assets were also under

pressure.

To frame our discussion, we introduce here a concept termed the Loan Portfolio Balance-at-Risk. At inception, the reinvestment

portfolio manager invests cash received from borrowers and the value of the collateral portfolio closely matches the value of the

loan portfolio. The collateral margin accounts for the difference. If the value of the loan portfolio rises, the reinvestment portfolio

manager can purchase more securities in the asset portfolio using the additional cash collateral received from the borrowers. If

the value of the loan portfolio falls, however, either the lending desk or the reinvestment portfolio manager must raise cash. The

lending desk may raise cash by lending additional securities. Additionally or alternatively, the reinvestment portfolio manager may

use existing overnight liquidity or sell assets from the collateral portfolio.

Generally, the reinvestment portfolio manager’s expected ability to meet liquidity requirements over a given time frame depends

on the following factors:

Loan Portfolio Balance-at-Risk: The expected change in the balance of the loan portfolio due to changes in the prices of the

underlying securities on loan and changes in the volume of securities on loan (utilization).

Both the speed and the extent of these changes are specific to the composition of the loan portfolio. All else equal, a loan

portfolio that consists of higher volatility assets or assets that exhibit larger variations in utilization will be subject to larger

fluctuations in value.

Collateral Liquidity: The fraction of the collateral that matures within a specified time frame.

If the collateral reinvestment portfolio does not contain sufficient cash (or shorter maturity assets rolling to cash) to return

requested collateral to borrowers, the reinvestment portfolio manager may be required to sell additional assets before they

mature. The portfolio manager may receive less than amortized cost upon the sale of the additional securities due to the price

impact of interest rate and credit spread volatility. Therefore, particularly in periods of market stress, required asset sales may

result in realized losses.

2 Figures A-2 and A-3 in the Appendix show the characteristics of sample collateral reinvestment portfolios.

6



Maximum Drawdown Path

We look at a potential case of an asset manager using all proceeds from maturing assets to fund the return of collateral without

having to sell anything, showing the maximum supportable drawdown path of the loan portfolio. This is the maturity profile of the

collateral portfolio, depicted in Figure 1. The question we would like to answer herein is how a lender may estimate the expected

drawdown path of the loan portfolio and lendable assets.

We arrive at an estimate of an extreme drawdown path for the loan portfolio through a simulation that considers the composition

of the loan portfolio, the characteristics of the return distributions of the securities on loan and the typical variation in demand for

borrowing these securities. We call this extreme drawdown path the 99 percent balance-at-risk and it represents the statistically

derived 99th percentile most extreme decline in the loan balance in a single month. The methodology is explained in detail in the

section “The Loan Portfolio: Balance-at-Risk.”

The difference between the maturity profile of the collateral portfolio and the balance-at-risk of the loan portfolio constitutes a

liquidity buffer. The dark blue area in Figure 1 depicts the 99 percent liquidity buffer, the difference between the 99 percent

balance-at-risk of the loan portfolio and the maturity profile of the collateral portfolio. This 99 percent liquidity buffer is a measure

of how rapidly a lender can wind down the loan portfolio, e.g., to reallocate the underlying assets, without having to sell assets in

the collateral portfolio before they mature if the value of the loan portfolio drops along its 99 percent worst drawdown path. In the

example considered here, the structure of the loan portfolio would provide for a 99 percent liquidity buffer of 40.32 percent of

portfolio value over one month.

The 99 percent liquidity buffer can be an actionable metric for lenders, as changes in the composition of the loan portfolio can

inform changes to the management of the collateral portfolio, including its liquidity profile.

Figure 1: Liquidity Risk in an Asset-Liability Framework

Source: State Street Global Markets

0%

20%

40%

60%

80%

100%

0 21 42 63Time (Business Days)

Liquidity Buffer

Fra

cti

on

of

Init

ial P

ort

foli

o V

alu

e

Value of Unmatured Collateral (Assuming No Reinvestment)

Level of Collateral Supportedby 99% Drawdown Path of

Loan Portfolio

Maximum Drawdownof Loan PortfolioSupported by Maturing Collateral

1 Day 1 Month

Cumulative Maturing Collateral 17.25% 50.40%

99% Loan Portfolio Balance-at-Risk 2.20% 10.08%

99% Liquidity Buffer 15.05% 40.32%

7



THE LOAN PORTFOLIO: BALANCE-AT-RISK

The value of the loan portfolio is influenced by the following key drivers:

Market movement: Changes in market prices of the securities on loan.

Demand for securities to borrow: Changes in demand influence asset utilization (i.e., the fraction of the lendable portfolio

that is on loan to borrowers).

Asset allocation and portfolio management: A lender, or asset manager acting on behalf of a lender, may wish to sell

assets that are currently on loan and purchase other assets. These new assets may not be lendable or may have different

utilization characteristics.

Operating cash flows: A lender may need to draw on the lendable portfolio, e.g., to make benefit payments, reducing

lendable assets.

Lender’s securities lending program guidelines, including:

Cash collateral portfolio yield: Generally, for loans versus cash (and excluding a scenario where the sale of

collateral assets may generate a realized loss), a lender seeks to maintain only those loans for which there is a

positive net spread between the cash collateral portfolio’s yield and the rebate rate due to the borrower.

Minimum spread requirements: A lender may wish to transact only loans with a minimum demand spread.

Approved counterparties

The first two drivers outlined above — changes in the market prices for the securities in the portfolio and changes in the demand

to borrow these securities (“utilization”) — are out of the lender’s control. The other factors are important, but we focus here on

measuring the potential risk in the factors that are independent of lender-directed actions, with the goal of helping lenders to

better inform their decision-making when establishing program parameters meant to suit their risk profile. To illustrate, we present

a typical client loan portfolio in Figure 2.

Figure 2: Composition of a Typical Loan Portfolio


Equities Fixed Income

US S&P 500 32.1% US Gov't. Treasury Bonds 10.7%

Russell 2000 10.7% Treasury Notes 10.7%

Japan Nikkei 225 8.7% USD Corp. Inv't. Grade 14.3%

France CAC 40 3.5%

Australia ASX 50 3.4%

Germany DAX 3.1%

Spain IBEX 1.3%

Hong Kong Hang Seng 1.1%

Norway OBX 0.4%

64.3% 35.7%

8



We sought to estimate the distribution of changes in the balance of the loan

portfolio caused by changes in market prices and changes in demand to

borrow. First, we aggregated the underlying asset classes in a sample loan

portfolio and used benchmark indices to estimate the asset classes’ changes

in market value. Next, we combined this data with daily utilization information

gathered from State Street’s securities lending program3 to estimate how the

balance of each asset class position in the loan portfolio would have

changed through time. We considered the potential for a lending agent to

increase its liquidity buffer by transacting additional loans and, by extension,

raising additional cash collateral. While this may be readily achievable under

normal market circumstances, raising cash in a stress scenario may be

expected to be more difficult. For the purpose of our analysis herein, we

have assumed market utilization rates rather than utilizations driven by

liquidity needs.

Based upon our empirical analysis, shown in Figure 3, the three-month 95

percent balance-at-risk tells us that in 95 percent of cases we can expect the

value of the loan portfolio to either rise or fall by no more than 10.91 percent

over the course of three months. In other words, we would expect with 95

percent confidence that the value of the loan portfolio would remain at or

above 89.09 percent of its original value.

Figure 3: Loan Portfolio Balance-at-Risk


3 We use State Street program-level utilization data to smooth the potential effects of client-specific activity related to portfolio trading, transitions and/or lending parameter changes

that may otherwise tend to skew observed changes in utilization.

Block Bootstrap

Bootstrap methods calculate estimates

based on an empirical distribution

and are generally used when the

underlying time series are thought to

exhibit serial dependence, such as

trending or mean reversion.

In such cases, building paths out of blocks

of consecutive observations from the

historical time series helps to account for

the impact of any serial dependence in the

original historical distribution on the

resulting risk estimates.

As referenced herein, we performed a

block bootstrap simulation with overlapping

paths, constructing the maximum possible

sample of overlapping three-month paths,

and ranked the cumulative change in loan

balances from the beginning of the path to

the 1st and 21st business day of the path

and report the 1st and 5th percentile of all

paths on that day as a measure of the loan

portfolio balance-at-risk. These measures

help us assess the risk of large decreases

in the value of the loan portfolio.

0 10 20 30 40 50 60

-25%

0%

25%

50%

Time/Business Days

Change in

Loan P

ort

folio

Valu

e

1 Day 1 Month 3 Months

99% BaR -2.20% -10.08% -14.52%

95% BaR -1.42% -7.62% -10.91%

9



COLLATERAL REINVESTMENT

Having explored the potential for loan balance declines and their potential impact on collateral portfolio liquidity, we next focus on

the market factors that may negatively impact the amortized cost of the collateral investments. Specifically, we focus on the

market risk in the collateral reinvestment portfolio and analyze the effects of changes in benchmark interest rates and credit

spreads on a number of typical reinvestment portfolios.

Portfolio Choices and Market Risk

In seeking to generate high risk-adjusted returns from reinvesting collateral, an agent lender has the option to adjust the

composition of the reinvestment portfolio to optimally capture various incremental premiums. For a cash collateral reinvestment

portfolio, investment managers typically focus on the following:

• Term premium: By adjusting the duration of the reinvestment portfolio

• Credit premium: By investing in assets of different credit quality

Capturing either of these premiums exposes the reinvestment portfolio and the returns associated with the securities lending

program to market and liquidity risks: changes in interest rates and/or credit spreads may change the market value of the

securities in the reinvestment portfolio at the same time as a decrease in market prices or the demand for borrowing securities

reduces the value of the loan portfolio.

To illustrate the magnitude and distribution of interest rates and credit spreads and their potential impacts on security values, we

consider 30-day LIBOR as a benchmark interest rate and the two-year AAA Asset Backed Securities spread as a benchmark

credit spread.

In Figure 4 we show histograms of the overlapping one-month changes in rates and spreads as dark blue bars.4 The

superimposed black lines represent a normal distribution with the same mean and standard deviation as the empirical changes in

interest rates and credit spreads.

To illustrate that large changes in rates and spreads occur significantly more often than a normal probability distribution would

suggest (i.e., that the empirical distributions have significantly more pronounced “fat tails” — the tails of the distribution being the

far left and right sides that converge on the horizontal axis), we have magnified the section of the histogram depicting large

increases in rates and spreads. These increases correspond to losses in a collateral reinvestment portfolio. To properly account

for this deviation from normality, we use analytical methods that rely on historical data rather than a more traditional mean-

variance (normal distribution based) risk model. We consider tail-risk metrics such as the conditional Value-at-Risk (cVaR),

defined here as the mean of the worst 5 percent of one-month returns.

4 This is based on daily data from January 4, 1999 through May 31, 2012. In Figure A-4 in the Appendix, we show historical values for LIBOR and ABS spread for this time period.

10



Figure 4: Interest Rates and Credit Spreads


Market Risk of the Collateral Reinvestment Portfolio

In Figure 5, we present a number of risk metrics for the sample reinvestment portfolios, including the asset-weighted interest rate

and spread durations as well as the average time to maturity and the allocation to floating rate securities.

We use asset-specific proxies for interest rates and spreads and a linear approximation5 (described in Figures A-5 and A-6,

respectively, in the Appendix) to calculate price changes for each of the assets in the portfolio and we use overlapping daily

historical one-month changes in the yields of these proxy rates and spreads from January 4, 1999 through May 31, 2012.

Figure 5: Risk Metrics and Yields


5 For each asset, we compute the change in interest rate specific to the asset’s maturity by interpolating between the interest rate changes for the closest available maturities of the

asset-specific proxy.

0%

20%

40%

-600 -400 -200 0 200 400 600

Fre

qu

en

cy

1-Month Change (Basis Points)

ABS Spread

0%

1%

0 200 400 600

0%

20%

40%

Fre

qu

en

cy

LIBOR

0%

1%

0 200 400 600

Treasury Repo Money Market Fund Enhanced Cash Separate Account

Interest Rate Duration (Days) 1 23 26 34

Spread Duration (Days) 0 16 39 161

Average Time to Maturity (Days) 1 36 57 180

Allocation to Floating Rate Securities 0.0% 19.7% 31.2% 62.1%

Historical Standard Deviation of 1-Month Returns* 0.1 2.2 4.1 11.9

Historical 5% 1-Month Excess cVaR* 0.2 3.9 8.9 28.4

Current Yield (Basis Points, Annualized) 18.6 32.0 41.3 65.6

Excess Yield over Eff. Fed Funds Rate (Basis Points) 2.6 16.0 25.3 49.6

* In basis points, historical period from January 4, 1999 - May 31, 2012

11



With the information gleaned thus far, we consider in more detail the market

risk of the collateral reinvestment portfolio, alongside an assumed large

decrease in the dollar value of the securities on loan.

As we know, drawdowns in the loan portfolio may be caused by a drop in

market value of the securities on loan, by a drop in the demand for

borrowing these securities, by lender restrictions or by other portfolio

management related decisions.

Such a reduction in the value of the loan portfolio requires that the value of

the collateral reinvestment portfolio be reduced accordingly. In the event that

cash returned to borrowers is comprised of cash from maturing (i.e., short-

duration) assets, a reduction in the value of the loan portfolio will indirectly

increase the duration of the remaining collateral portfolio and may

exacerbate the effect of interest rate and spread changes on the unit price of

the remaining portfolio.

In Figures 6, 7 and 8, we present three scenario analyses of the effect of

different combinations of interest rate and spread changes on the value of

the lender’s reinvestment portfolio. In Figure 6, we assume the reinvestment

portfolio is a money market fund. In Figure 7, we assume the lender

reinvests cash collateral in an enhanced cash portfolio. In Figure 8, we

assume the lender reinvests cash collateral in a separate account portfolio

with relatively broader investment guidelines. The top left number in each

cell corresponds to the simulated change in the NAV of the reinvestment

portfolio (as of May 31, 2012) if interest rates changed by the amount in the

top row and spreads changed by the amount in the leftmost column. The

bottom right number in each cell corresponds to the simulated change in

NAV if the collateral portfolio simultaneously experiences a redemption

equal to 99 percent of the Loan Portfolio Balance-at-Risk.

The shading of the cell denotes the frequency with which this combination of asset-weighted yield and spread change over one

month was observed in the historical sample period. For the historical period we examined, simultaneous detrimental moves in

both interest rates and credit spreads occurred very infrequently. This methodology gives us another means of viewing the

potential for extreme events.

Note that for other portfolios, similar joint rate and spread changes may lead to larger or smaller changes in portfolio value,

depending on the characteristics of the portfolio.

Price Returns of the Collateral

Reinvestment Portfolio

The price of assets in the collateral portfolio

responds to changes in both interest rates

and credit spreads.

Throughout, we approximate the

interest rate duration or the change in

the price of an asset in response to a

change in interest rates for fixed rate

assets with the asset’s time to maturity.

The interest rate duration for floating rate

securities is assumed to be relatively small,

even for assets with a long time to maturity,

as their yield is quoted as a spread over a

specified benchmark interest rate, typically

LIBOR, and the benchmark rate resets at

pre-specified intervals of typically one or

three months.

Floating rate securities are, however,

subject to spread rate risk. When

credit spreads rise, the price of a floating

rate asset may fall substantially, as the

spread duration is approximately equal to

the time to expected maturity of the floating

rate asset.

12



Figure 6: Scenario Analysis for Money Market Fund Portfolio – Rate and Spread Changes and Portfolio NAV


Figure 7: Scenario Analysis for Enhanced Cash Portfolio – Rate and Spread Changes and Portfolio NAV


66 57 47 38 29 19 10 1 -9 -18

73 63 53 42 32 21 11 1 -10 -20

60 50 41 32 22 13 4 -6 -15 -25

66 56 45 35 25 14 4 -6 -17 -27

53 44 35 25 16 6 -3 -12 -22 -31

59 49 38 28 18 7 -3 -14 -24 -34

47 37 28 19 9 0 -9 -19 -28 -37

52 41 31 21 10 0 -10 -21 -31 -41

40 31 22 12 3 -6 -16 -25 -35 -44

45 34 24 14 3 -7 -18 -28 -38 -49

34 25 15 6 -4 -13 -22 -32 -41 -50

37 27 17 6 -4 -14 -25 -35 -45 -56

27 18 9 -1 -10 -19 -29 -38 -47 -57

30 20 10 -1 -11 -21 -32 -42 -53 -63

21 12 2 -7 -16 -26 -35 -45 -54 -63

23 13 2 -8 -18 -29 -39 -49 -60 -70

Historical Sample: 1-Month Yield and Spread Changes, Overlapping, January 4, 1999 - May 31, 2012

Historical Frequency Legend:

< 5% of historical sample > 5% of historical sample

Δ S

pre

ad

in

BP

s

NAV

Change

did not occur in historical sample < 0.1% of historical sample < 1% of historical sample

0

100

200

300

400

Δ Interest Rate in BPs

-300-400-500

-300

-200

-100

4003002001000-100-200

99 89 78 68 57 47 36 26 15 5

110 98 87 75 64 52 40 29 17 6

84 73 63 52 42 31 21 10 0 -11

93 81 69 58 46 35 23 11 0 -12

68 58 47 37 26 16 5 -5 -16 -26

75 64 52 40 29 17 6 -6 -17 -29

52 42 31 21 10 0 -10 -21 -31 -42

58 46 35 23 12 0 -12 -23 -35 -46

37 26 16 5 -5 -16 -26 -37 -47 -58

41 29 17 6 -6 -17 -29 -40 -52 -64

21 11 0 -10 -21 -31 -42 -52 -63 -73

23 12 0 -11 -23 -35 -46 -58 -69 -81

6 -5 -15 -26 -36 -47 -57 -68 -78 -89

6 -6 -17 -29 -40 -52 -64 -75 -87 -98

-10 -20 -31 -41 -52 -62 -73 -83 -94 -104

-11 -23 -34 -46 -58 -69 -81 -92 -104 -116



400



300 400

Δ S

pre

ad

in

BP

s

-300

-200

-100

0

100

200

300

NAV

Change


-500 -400 -300 -200 -100 0 100 200

13



Figure 8: Scenario Analysis for Separate Account Portfolio – Rate and Spread Changes and Portfolio NAV


SUMMARY

Recognizing the value of defining metrics for loan balance volatility, we have established a simple framework to measure two

market risk factors of a client’s lendable asset pool and loan portfolio: changes in the market value of securities on loan and

changes in the demand for borrowing. Integrating this analysis with the collateral reinvestment portfolio’s scheduled maturity

profile, we can identify the potential likelihood of a lender needing to liquidate collateral assets. A lender can also quantify the risk

of loss in the unlikely event that portfolio securities must be sold. In summary, we present our analysis as a quantitative basis for

institutional investors to assess and guide decision-making for managing liquidity risk in a securities lending program.

261 248 234 221 207 194 180 167 153 140

289 274 259 245 230 215 200 185 171 156

196 183 170 156 143 129 116 102 89 75

217 202 188 173 158 143 129 114 99 84

132 118 105 92 78 65 51 38 24 11

146 131 116 101 86 72 57 42 27 12

67 54 40 27 13 0 -13 -27 -40 -54

74 59 44 30 15 0 -15 -30 -44 -59

3 -11 -24 -38 -51 -65 -78 -92 -105 -118

2 -12 -27 -42 -57 -72 -86 -101 -116 -131

-62 -75 -89 -102 -116 -129 -143 -156 -170 -183

-69 -84 -99 -114 -129 -143 -158 -173 -188 -202

-126 -140 -153 -167 -180 -194 -207 -221 -234 -248

-141 -156 -171 -185 -200 -215 -230 -245 -259 -274

-191 -204 -218 -231 -245 -258 -272 -285 -299 -312

-213 -227 -242 -257 -272 -287 -301 -316 -331 -346



-100 0 100 200 300 400

Δ S

pre

ad

in

BP

s

-300

-200

-100

0

100

200

300

NAV

Change


-500 -400 -300 -200

400



14



APPENDIX

A Sample Securities Lending Transaction

Figure A-1 shows a sample one-day transaction. In this example, a borrower seeks 50,000 shares of XYZ Corporation with a

market value of $10 million. The borrower contacts an agent lender that has XYZ in inventory. The two parties agree that the loan

will be made versus cash collateral on an open basis (i.e., no fixed loan period) at a rebate rate of 0.05 percent. The agent lender

executes the trade on its internal systems, the borrower delivers cash collateral valued at 102 percent of the market value (in this

case $10,200,000) and shares are delivered by the agent lender to the borrower. The cash collateral is invested in a reinvestment

portfolio earning a 0.30 percent annualized return, or $85 for one day’s investment. (In the case of non-cash collateral, there is no

reinvestment yield. Instead, the borrower pays a fee based on the market demand to borrow and the size of the loan.) From the

$85 reinvestment revenue, $14 is paid to the borrower in the form of the rebate and the remaining $71 is split between the lender

and the agent lender as contractually agreed.

Figure A-1: Sample Securities Lending Transaction


Borrower Client

Agent Lender

Collateral Reinvestment

Account

Yield: 0.30% Earnings: $85

Collateral at 102%

$10,200,000

Loaned Securities

(XYZ Corp.)

Rebate: 0.05%

0.05%/360*$10,200,000

Interest Due: $14

75% of total spread:

$71 * 75% = $53.25

:

25% of total spread:

$71 * 25% = $17.75

Collateral

$10,200,000

15



Sample Reinvestment Portfolios: Asset Allocation and Maturity Distribution

Figure A-2: Asset Allocation


Figure A-3: Maturity Distribution


Figure A-4: Historical LIBOR and ABS Rates

Source: State Street Global Markets; Bloomberg


Asset-Backed Structures

Corporate Obligations

Bank Obligations

Repo


> 252 Days

≤ 252 Days

≤ 90 Days

≤ 30 Days

1 Day

-250

0

250

500

750

Jan-99 Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12

Inte

res

t R

ate

(B

Ps

) LIBOR ABS Spread

16



Figure A-5: Yield Curve Mapping

We assign a benchmark interest rate to each security in the collateral portfolio. For each security, we select the yield curve based

on Figure A-5 below and then interpolate between the changes in yield for the two nearest maturities, used here as a proxy for

duration.

Figure A-6: Linear Approximation of Price Changes

The change in the price of an asset in response to an interest rate shock (ΔIR) is approximated by

ΔNAVasset =-(Interest Rate Duration)*ΔIR

The change in price of an asset in response to a credit spread shock (ΔSpread) is approximated by

ΔNAVasset =-(Spread Duration)*ΔSpread

ΔNAVasset =-(Interest Rate Duration)asset *ΔIRasset -(Spread Duration)asset*ΔSpreadasset

Fixed Rate Securities Floating Rate Securities

Repo Overnight: Fed Funds, else LIBOR Floating Rate Swap Spread

Gov't Obligations

US Agency US Agency Curve Floating Rate Swap Spread

Bank Obligations

Bank Note

Time Deposit

Euro CD

Yankee CD

Corporate Obligations

Corporate

Commercial Paper, Interest Bearing

Asset-Backed Structures

Asset-Backed Securities LIBOR + ABS Spread

Asset-Backed Commercial Paper ACPA, ACPB Commercial Paper CurvesAAA ABS Floating Rate Swap Spread

LIBOR

DCDA, DCDB Curves

DCPA, DCPB Commercial Paper Curves Floating Rate Swap Spread

Index Interest Rate: LIBOR or

FEDSOPEN

Floating Rate Swap Spread

17



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arm of State Street Corporation (NYSE: STT), one of the world’s

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