Derivatives and collateral at U.S. life insurers.
Berends, Kyal ; King, Thomas B.
Introduction and summary
Insurance companies serve the important economic role of helping
businesses and households to insulate themselves against risks. But
these risks do not disappear from the economy--they remain on
insurers' books, necessitating careful risk management among
insurers themselves. Over the past two decades, one way that insurers
have managed risk is through the use of derivative contracts, (1) which
derive their value from the performance of an underlying entity. This
underlying entity can be an asset, index, or interest rate. Some of the
more common derivatives include forwards, futures, options, and swaps.
Most derivatives, including interest rate swaps (IRS), have historically
been traded over the counter (OTC) rather than on centralized exchanges.
The use of derivatives comes with its own set of costs related to
the transaction, management, and collateralization of positions. With
the implementation of the Dodd-Frank Act of 2010, those costs seem
certain to rise. Among other provisions, the law requires the central
clearing of certain types of OTC derivatives and mandates that those
transactions must satisfy margin requirements that will in most cases
require counterparties to post more collateral than was previously the
case. (2) Forthcoming rules will impose additional collateral
requirements on derivatives positions for which the central clearing
mandate does not apply. Thus, the new rules for both cleared and
noncleared derivatives could generate new costs for insurers or require
changes in their business practices.
In this article, we review life insurers' use of OTC
derivatives and discuss the possible implications of these new rules for
their financial condition. (3) Although insurers represent a relatively
small part of the derivatives markets, they are an interesting case
study, in part because they report very detailed information about their
derivatives positions and associated collateral in quarterly regulatory
filings. We exploit these data to study how derivatives are used by
insurers and to get a quantitative sense of what the new regulations are
likely to imply for their business models.
The new regime poses several potential costs for insurers. For
example, like many market participants, insurers will face a short-term
fixed cost of adjusting operations and corporate structure to meet the
new clearing and collateralization requirements, as well as ongoing
expenses associated with trading, collateral optimization, and
back-office functions; and insurers may also face some regulatory
capital consequences.
In this article, however, we focus on one particular set of costs
that has received attention, namely, costs related to reallocating
insurers' portfolios to highquality--and therefore
low-yielding--assets in order to meet margin requirements. (4) We find
that, overall, the requirements are unlikely to generate large costs for
the industry as a whole through this channel-although there are some
low-probability tail scenarios in which they could result in substantial
forgone investment income for a few larger insurers. This finding is
largely due to the fact that insurance companies already hold large
amounts of high-quality unencumbered securities that could be pledged
for this purpose, and indeed they may be natural collateral providers to
other market participants. (5)
After reviewing insurers' use of derivatives and collateral in
the following section, we develop a Monte Carlo exercise to attempt to
quantify the amount of margin posted and revenue lost due to required
margin under different scenarios for interest rates and insurer
portfolio evolution. Then, we consider some ways that insurers may
adjust their business practices in light of the new regulations. Two
likely responses are to reduce the need for hedging by shifting more
interest rate risk onto consumers or markets and to build up new sources
of liquidity to cover cash needs. Depending on how these adjustments
play out, they could expose insurers and their counterparties to new
risks, especially in a crisis environment in which liquidity is
constrained.
Life insurers' use of OTC derivatives
Insurers use a variety of types of derivatives for hedging
different types of risks. Some of these derivatives, such as equity
options and currency swaps, are typically exchange traded and are not
affected by the Dodd-Frank rules. In this article, we focus on the
interest rate and credit derivatives that are traded OTC, because those
are the contracts to which the central clearing and collateralization
requirements apply. Table 1 lists the 20 life insurance companies that
participate most in the OTC derivatives market, as measured by the gross
notional value of their positions in these instruments. (6) These
companies include the largest insurers by assets, but derivatives usage
is not perfectly correlated with firm size--it depends on a variety of
factors, including lines of business and corporate structure. For
example, some very large insurers, including TIAA-CREF and Northwestern
Mutual, have OTC derivatives positions that are too small to be included
in the table.
As a whole, the life insurance industry held $1.1 trillion of
notional value in OTC derivatives as of September 2014. For a sense of
scale, we note the statutory assets of these companies totaled $6.1
trillion. Relative to other market participants, such as commercial
banks, the OTC derivatives portfolios of life insurers are relatively
modest. The gross market value of their swaps positions was only about
$13.2 billion, and the net positions are likely smaller still. (7)
However, derivatives portfolios are highly concentrated--over 50 percent
of notional value of OTC derivatives in the industry is held by the four
insurers with the largest swaps portfolios (MetLife, Manulife, Mass
Mutual, and New York Life). The companies in the table collectively hold
97 percent of the industry's OTC derivatives.
Large insurance operating companies often reside within even
larger, complex corporate structures. Thus, derivatives positions at the
operating company may not give a complete picture of the derivatives
activity at the whole firm. For companies that are publicly traded in
the United States, it is possible to obtain some information on
consolidated derivatives positions from SEC filings, although this
information is not as detailed as what is available from regulatory
reports. Table 2 shows the sum of interest rate and credit derivative
positions for the largest companies for which such information is
available. For these eight firms (which together hold about half of the
positions listed in table 1), derivative exposures that are in
subsidiaries other than life insurance operating companies constitute 55
percent of the holding companies' notional positions.
As shown in table 3, insurers' interest rate swaps positions
at the industry level are roughly equally balanced between paying and
receiving fixed rates. (8) This pattern also holds at the individual
insurer level: A typical firm both receives and pays fixed rates.
However, as we discuss later, the simultaneous positions in opposite
directions reflect the hedging of different types of risk and,
consequently, typically differ by maturity. Insurers also hold fairly
large positions-about $327 billion in notional value--in other types of
interest rate derivatives, especially caps and call swaptions, which
hedge against rising rates. They also hold small amounts of total return
and credit default swaps, which are used for asset replication purposes
as well as hedging, and a smattering of miscellaneous products.
To understand the potential impact of the new collateral rules on
the insurance industry, it is useful to review how these derivative
positions function within insurers' business models. Insurers take
very few directional positions using derivatives, relying on them almost
entirely for hedging purposes. In particular, they hedge four broad
types of risk. (9) First, they hedge the interest rate risk of their
fixed-income portfolios. As of September 2014, the insurers in table 1
collectively held nearly $1 trillion in various types of bonds, exposing
them to rising interest rates. (10) They use pay-fixed interest rate
swaps and other interest rate derivatives to hedge against this risk.
Statutory data on hedging purpose (not shown) indicate that about half
of OTC derivatives positions serve this function.
Second, insurers hedge the risks of deposit-like liabilities,
including funding agreements and guaranteed interest contracts (GICs).
These may pay fixed or floating rates and span a spectrum of maturities,
although they are typically much shorter than insurers' other
liabilities. These contracts may also have option-like features that
require more complex hedging strategies. Some of these strategies may
involve relatively exotic derivatives for which central clearing is not
available.
Third, insurers attempt to match the duration of their long-term
insurance and annuity liabilities. For the simplest contracts, hedging
these exposures involves receiving interest payments to match the
payments that the firm is required to make. But, for most insurance and
annuity products, cash flows are uncertain. Thus, unlike the
security-specific hedging on the asset side, liability hedging can only
be done imperfectly in an economic sense, since there is significant
uncertainty about the timing and duration of future insurance claims. As
shown in table 3, insurers are, on net, receivers of fixed payments in
swaps, implying that on balance they are using swaps to add duration to
their portfolios. This makes sense as many life insurance liabilities
are very long duration--indeed, in some cases longer than can be
achieved by buying fixed-income products in the cash market.
Finally, insurers hedge the optionality of their liabilities. This
optionality can take a variety of implicit and explicit forms. For
example, it is common for insurance companies to offer minimum-return
guarantees on variable annuities, which they in turn hedge with a
combination of OTC and exchange-traded derivatives. Furthermore, most
annuities may be surrendered at the option of the beneficiary.
Fixed-rate annuities are more likely to be surrendered when interest
rates rise, precisely when they are most attractive from the
issuer's point of view. Most of the caps, floors, and swaptions
reported in the table are also used to hedge these types of risk, and
interest rate swaps may be used as part of the strategy. Many of the
nonoperating-company positions shown in table 2 are likely held by
captive reinsurers, which also principally use them for this type of
hedging.
It is important to recognize that derivatives portfolios reflect a
mix of risk mitigation, accounting, and regulatory considerations. In
particular, under FAS 133, insurers can receive hedge accounting
treatment for derivatives positions that are deemed "effective
hedges," and a similar treatment applies in statutory accounting.
For example, insurers discount the value of future claims on insurance
policies using an assumed maturity structure and discount rate, and they
can receive hedge accounting treatment by entering into (usually
long-dated) swaps that match these terms. Although long-term bonds might
be able to match the duration of those same positions reasonably well
and thus hedge them in an economic sense, such a strategy would not
qualify for hedge accounting treatment. Insurers may have incentives to
engage in offsetting swaps contracts to hedge both sides of the balance
sheet to recognize accounting benefits.
One should also bear in mind that insurers' derivatives use
takes place against a backdrop of regulatory controls. Some states
require insurers to maintain a strict "derivatives use plan"
that must meet with the approval of supervisors, and they also set
limits on the quantity of derivatives activity. For example, New York
prohibits swaps holdings with potential exposure in excess of 3 percent
of admitted assets. ("Potential exposure" is a regulatory
measure of the total amount of risk posed by an insurer's
derivatives book.) Insurers must therefore choose carefully which risks
to hedge and how best to use their limited derivatives capacity.
Margin requirements and Dodd-Frank
Because participants in derivatives contracts have risk exposures
to their counterparties, they are typically required to post some form
of collateral to each other. The Dodd-Frank Act standardizes these
requirements for OTC derivatives transactions. Collateral requirements
associated with derivatives trades are of two types. Variation margin
captures the marked-to-market change in the value of positions on a
daily or, in exceptionally volatile periods, intraday basis. This is
meant to ensure that in the event of a default by one counterparty, the
other counterparty can recover the fair value of the position. Initial
margin is intended to cover possible losses incurred by the remaining
counterparty after default, as it goes about liquidating or replacing
the defaulted position. Thus, initial margin is typically calculated by
assuming a certain amount of time for liquidation and using the data to
estimate a worst-case scenario for the price moves of the position.
Even prior to the Dodd-Frank rules, it was standard for OTC
derivatives counterparties to post some form of variation margin, and
the exchange of initial margin was also common. (11) However,
derivatives counterparties typically had a fair amount of leeway in how
these requirements were satisfied. For example, they may have been able
to post a variety of collateral types as margin or, depending on their
bilateral agreements, post margin only when the change in the fair value
of the position exceeded some threshold. Figure 1, panel A, shows margin
posted by insurance companies in support of derivatives since 2013:Q1,
when these data were first collected. (12) Figure 1, panel B, shows the
collateral breakdown as of 2014:Q3. Note that, although variation margin
constitutes the bulk of insurers' collateral positions, very little
of this collateral consists of cash. This reflects the fact that most
derivatives on insurers' books, if they require collateral at all,
allow variation margin to be posted in the form of a range of
securities.
Since June 10, 2013, new plain vanilla IRS and CDS index positions
covered under Dodd-Frank have had to be cleared by a central
counterparty (CCP) and collateralized accordingly. In particular, CCPs
must require counterparties to post initial margin sufficient to cover a
hypothetical five-day liquidation period with at least a 99 percent
level of confidence and variation margin to cover daily fluctuations in
the market value of positions. Forthcoming rules on uncleared trades are
likely to impose a similar requirement for variation margin and a more
stringent ten-day liquidation period for initial margin.
As shown in figure 1, margin posted by insurance companies to cover
derivatives positions has indeed risen notably since the first quarter
of 2013. In the 18 months surrounding the implementation date, insurers
increased the collateral posted with derivatives counterparties by 45
percent, from $7.2 billion to $10.4 billion. Although both initial
margin and variation margin have increased significantly, variation
margin has fluctuated more. This is because variation margin is heavily
influenced by external factors, such as interest rates. This volatility
is suggestive of one type of risk that insurers now face--large
movements in interest rates can require the transfer of large quantities
of securities and, especially, cash into margin accounts. The following
section discusses the scope of this risk in greater detail.
The types of collateral that can be posted to cover margin for
cleared contracts, and the haircuts that apply, vary across CCPs.
Initial margin is most often satisfied by high-quality securities, such
as U.S. Treasury securities, although at least one major CCP has begun
accepting investment-grade corporate bonds (within certain limits and
subject to steep haircuts). In contrast, variation margin must be
covered by cash. Moreover, the time frame within which clearing members
must post variation margin after receiving a margin call is typically
very short, often a matter of hours. (For uncleared trades, proposed
rules would require most insurance companies--as "low-risk
end-users"--only to update variation margin once per week and when
the values involved rise above some de minimus amount.)
The burden of initial margin requirements is reduced to a degree by
the possibility of netting potential moves in negatively correlated
positions against each other. For example, if an insurer engages in a
receive-fixed swap and a pay-fixed swap on similar terms with the same
counterparty, that counterparty should expect price movements in the two
contracts to offset exactly. Consequently, the margin needed to cover
the position as a whole should be minimal, even though the margin needed
to cover each swap individually might not be. For cleared trades, the
extent to which such gains are available depends on the CCP's rules
and models. For uncleared trades, the potential for margin offsets
depends on the extent and terms of master netting agreements. In both
cases, it also depends on the degree to which positions are concentrated
at particular counterparties, since it is generally not possible to
recognize portfolio-margining benefits from offsetting positions at
different counterparties. (13)
The potential costs of the new collateral and clearing requirements
span a variety of operational and economic considerations and are
discussed more fully in a later section. It is clear, however, that the
incidence of these costs--and, therefore, the nature of the
industry's response--will depend greatly on the quantity of
collateral that insurers end up having to post. We turn to this question
next.
Collateral needs under alternative scenarios
In this section, we attempt to quantify the amount of collateral
that may be necessary for life insurers to provide in support of cleared
swaps positions in coming years. The results are essentially the product
of three inputs: 1) a distribution for the possible path of interest
rates; 2) calculations of how the value of each derivative contract type
responds to the various interest rate configurations; and 3) an
assumption regarding how insurers' derivative positions will evolve
over time. Given institutional shifts in the industry and limited
historical data, the last item is the most difficult of the three to
ascertain. Therefore, we consider two different scenarios for the
changes in the industry's derivatives mix that likely bracket the
possibilities.
We summarize the methodology briefly here and describe it in detail
in the appendix.
Model setup
For each of the 20 firms with the largest OTC derivatives holdings,
as measured by notional value, we break down the interest rate swaps
portfolio based on derivative type (pay-versus receive-fixed), maturity,
and time since the contract was originated. We take the granularity of
maturity buckets and contract ages to be annual, and we assume that the
maximum maturity is 30 years. (14) For each type, we approximate each
firm's notional holdings using a beta distribution over maturities,
based on the 2014:Q3 data that were summarized at an aggregate level in
table 1 (p. 22). Our assumptions about how this distribution evolves
generate flows of derivatives originations and terminations in each year
in our simulations for each firm in each type/maturity bin. Knowing the
flows allows us to back out the distribution of contract ages for each
swap bin. Since swaps valuation depends on the contract's remaining
maturity and the fixed rate that applies to it, we can track the
distribution of swap rates within each bin, given a path of historical
interest rates.
We assume that all swaps held by insurers are "plain
vanilla" interest rate swaps (meaning standard contracts that
exchange fixed and floating payments based on commonly used benchmarks
and schedules). This assumption allows us to calculate the net present
values of these contracts analytically, given an interest rate path.
Furthermore, this assumption implies that the collateral requirements
associated with central clearing apply to all of those contracts that
are originated going forward. (15) We do not consider contracts
originated prior to 2013:Q2 because, although many such contracts do
involve margin agreements between the counterparties, the Dodd-Frank
rules only require insurance companies to clear and post margin on plain
vanilla swaps originated after June 2013.
Dodd-Frank mandates initial margin sufficient to cover a five-day
liquidation period on cleared trades. To give a sense of the magnitudes
involved, we calculate the range of initial margin values that could
apply to swaps of various maturities and rates. Specifically, we
calculate the distribution of five-day changes in value by drawing
random five-day yield curve changes from the last ten years of data, and
we apply these changes to rates that start at their 2014:Q1 level. Table
4 shows the resulting 99.7 percent quantiles, corresponding roughly to
the levels of confidence used by CCPs. (16) In the absence of netting,
the total initial margin required on a particular portfolio in the
current interest rate environment would simply be given by the margin
rates listed in the table, weighted by the amount of the portfolio in
each corresponding bin. However, when calculating initial margin, CCPs
and other counterparties generally allow for possible negative
correlations between value changes for different derivatives positions
in the same portfolio. This implies that one needs to evaluate the
distribution of outcomes at the portfolio level. Our simulations of
initial margin do this for each firm, at each date, for each simulated
path of interest rates, based on our projections for how the
distribution of swaps to which Dodd-Frank applies evolves over time.
Calculating variation margin, given a path of interest rates, is
somewhat easier, since variation margin is simply equal to the net fair
value of the swaps positions. Thus, for each firm, at each date, for
each simulated path of rates, we calculate the net present value of
swaps of each age in each type/maturity bin. Total variation margin is
the sum of these values across swaps originated after 2013:Q2, weighted
by the respective portfolio shares.
Interest rate simulations
We begin our computations in 2013:Q2. For the calculations through
2014:Q3, we use actual data on the yield curve to price the swaps
portfolios. For projections beyond that date, we estimate a vector
autoregression on Treasury forward rates, the Moody's Baa corporate
bond yield, gross domestic product (GDP), and PCE inflation (based on
the Personal Consumption Expenditures Price Index). We then take 10,000
draws from the estimated residual distribution and simulate forward ten
years beginning with 2014 data. Any time a simulation results in a
nonpositive rate in any quarter, we discard it and draw again. Figure 2
shows the distribution of simulated rate paths.
Portfolio scenarios
The amount of margin that will need to be posted against
derivatives positions will depend crucially on how insurers adjust their
derivatives portfolios going forward. The most natural assumption about
this behavior may be simply that they keep the distribution across
contract types and maturities unchanged at its current level, and this
is indeed the first scenario that we consider. However, market
participants generally anticipate that the net duration of the portfolio
will lengthen going forward. This is also the situation in which margin
is potentially greatest in the rising-interest-rate environment that we
consider, and so it is worth modeling from a stress-testing point of
view. Our second scenario is a variant of this outcome, in which
insurers take new long positions by passively rolling over their
maturing derivatives.
Specifically, in our "constant maturity distribution"
scenario, we assume that the distribution of the stock of derivatives
(that is, the percentage of the total in each type/maturity bin) is
static. This means that the flows--that is, the amount of contracts
originated or extinguished in each quarter--must generally be nonzero.
We assume that the gross flows (the amount of notional value originated
and canceled) are the minimum possible to achieve the net flow that
keeps the stock distribution unchanged. In our "duration
extension" scenario, we assume that insurers do not terminate any
swaps going forward, but all contracts (either long or short) that
mature are rolled into new 30-year receive-fixed swaps. Given the
initial maturity distribution of swaps, this implies that by the end of
the projection period, about 40 percent of the pay-fixed and 60 percent
of the receive-fixed portfolio have rolled into new long swaps positions
that are subject to Dodd-Frank.
[FIGURE 2 OMITTED]
Importantly, both scenarios assume that the overall size of
insurers' derivatives portfolios stays constant. This assumption is
simply for ease of comparison to current balance-sheet values. If, as
seems nearly certain, the notional value of swaps positions continues to
increase over time, the dollar values of posted margin--and the
corresponding costs--will be proportionally higher.
Estimated margin
For each firm, we calculate the margin that would be required in
each year under each scenario, given the distribution of interest rate
paths shown in figure 2. As shown in figure 3, initial margin is
forecast to rise steadily over the projection period in both scenarios.
The smoothness and relative precision of the projected paths of initial
margin reflect the fact that initial margin is largely driven by
portfolio turnover, which is (by assumption) independent of the interest
rate environment. However, the size of the increase depends crucially on
the extent of the portfolio lengthening. In the constant-maturity case,
it climbs about $2 billion between 2013:Q2 and 2014:Q3, reflecting
portfolio changes that we have already observed, but then stays
approximately constant for the remainder of the projection period. This
outcome reflects the strong negative correlation between changes in
receive-and pay-fixed values, which insulates the value of the overall
portfolio from interest rate shocks. In the duration-extension case, in
which this offset gradually disappears, the required amount of initial
margin climbs to about $8 billion by 2024. (17)
[FIGURE 3 OMITTED]
Under the constant-maturity scenario, the mean level of variation
margin peaks at a level of about $4 billion after eight years, as shown
in figure 4. Under the duration-extension scenario, this amount is
considerably larger, at about $18 billion. Furthermore, the amount is
very sensitive to the path of interest rates, with the 90 percent
confidence interval in the duration-extension scenarios spanning a range
of nearly $100 billion. Thus, the amount of variation margin that will
be required from the industry in coming years is quite uncertain.
Potential costs of margin requirements
Initial margin
Table 5 reports sample firms' securities holdings that could,
in principle, be used to meet initial margin requirements. In practice,
two reasons that these total amounts of securities may not be able to be
used for margin are that they are already pledged for some other purpose
or that the CCP imposes a limit on how much may be used. As shown in
column 2, encumbered assets generally represent a small portion of
insurers' overall securities portfolios. To address the question of
collateral limits imposed by CCPs, we apply the margining rules for
cleared swaps adopted by the CME (Chicago Mercantile Exchange). (18) In
particular, we assume that for margining purposes, each type of security
is discounted by the amount shown in column 3, reflecting a typical
haircut applied to that asset class by the CME. Furthermore, we apply
the CME's rule that the sum of agency debt and agency
mortgage-backed securities (MBS) used as collateral cannot exceed 40
percent of total collateral for any given customer and that corporate
and foreign sovereign bonds cannot exceed the lesser of 40 percent of
total collateral or $5 billion. The portfolio limits at the CME apply at
the level of the futures commissions merchant (FCM), not the client, so
an insurer effectively competes with the other clients of an FCM when
trying to post corporate bonds. However, large insurers also have
accounts at multiple FCMs; thus, it is not clear whether the effective
limits on insurers should be considered to be greater or less than the
limits imposed by the CCP. The table therefore considers both a case in
which the CME rules are passed through one-for-one to insurers and a
more conservative calculation in which insurers are not able to post any
securities at all other than cash and Treasury securities. The results
of these calculations, reflecting the approximate amount available for
initial margin, are shown in columns 5 and 6, with the actual amount of
margin (both initial and variation) currently posted shown for
comparison in the final column. As the available securities exceed those
being used by a factor of 6, even under the conservative assumptions,
there is clearly a significant amount of spare capacity at present.
[FIGURE 4 OMITTED]
Furthermore, the amount of securities available to pledge is large
compared with the amount of collateral that was projected to be needed
for initial margin in the previous section. Thus, it appears unlikely
that collateral availability for initial margin will be a binding
constraint for most insurers in the foreseeable future. (19) This is in
contrast to the situation for many other types of derivatives market
participants, which may have large OTC derivatives positions but do not
necessarily hold large volumes of high-quality securities, giving rise
to increased demand for collateral-transformation services. (20)
Although insurers have little incentive to engage in collateral
transformation (apart, perhaps, from increased repo activity, as
discussed later), the requirement to post initial margin will still
involve some ongoing costs. CCPs typically charge fees of 10 to 25 basis
points to service collateral (in addition to the other fees associated
with central clearing). This is on top of any collateral administration
fees charged by the insurer's clearing member.
Variation margin
The potentially costly scenario for insurers with respect to
variation margin is one in which long-term interest rates rise
significantly and spreads between the yields on their assets and
overnight rates widen, even if these moves were to occur over a
relatively long period. This is because such a scenario could involve
having to sell bonds to meet variation margin on long-dated
receive-fixed swaps; and the return on that margin would be low relative
to that on bonds, representing an opportunity cost for the firm.
Accordingly, we assume that variation margin on cleared swaps is posted
in cash that is raised by selling corporate bonds and that it pays the
effective federal funds rate. (21) Thus, the cost of variation margin is
driven by the spread between the corporate bond rate and the fed funds
rate in each of our Monte Carlo scenarios. (22) Figure 5 shows the
corresponding distribution of losses (more precisely, forgone revenue),
relative to what would obtain if there were no margin requirements.
For the constant-maturity scenario, the amount of projected
variation margin was relatively small, and consequently the forgone
revenue associated with variation margin is also small--$180 million per
year by the end of the projection period in the mean case. While this
amount is not trivial, it would not represent insurmountable costs for
the industry. For example, profits at the firms in our sample were $24
billion in 2013, (23) so that even for extreme interest rate paths,
margin-related costs would amount to less than 1 percent of earnings. In
large part, this modest outcome has to do with the factors noted in the
previous section that keep margin small when the distribution of swaps
stays fixed.
Again, the scenario in which insurers extend the duration of their
portfolios results in much larger median outcomes and a much wider range
of possibilities. The mean cost of posting variation margin rises to
about $760 million per year; and, for adverse interest rate outcomes (a
steeply rising yield curve and a widening of the spread between
corporate yields and the PAI), the cost could be over $2.5 billion per
year.
Other costs
In addition to the opportunity cost of variation margin, there are
other costs for insurers to consider. In particular, organizational and
operational details may introduce complications, especially in the short
run. For example, it may be that the subsidiaries of an insurance
company that currently hold its swaps positions are not the same
subsidiaries that hold its high-quality collateral. Insurers could
respond by consolidating or rearranging the corporate structure or by
transferring exposures and assets across entities.
[FIGURE 5 OMITTED]
Though relatively minor, there are also capital issues involved
with collateral management. For example, collateral pledged for
derivatives positions continues to be counted as an asset of the
pledging insurance company, but it receives an additional risk-based
capital charge, reflecting the risk that it may not be available to pay
policyholder claims in the event of default.
The cost of derivatives trading may also increase. CCPs charge
maintenance and transaction fees for swap clearing, although these are
on the order of fractions of basis points. Perhaps more significantly,
clearing members face significant new costs associated with account
administration, default fund contributions to CCPs, and clearing. It is
likely that they will pass on most of these costs to clients in the form
of increased fees. The costs of trading uncleared derivatives are likely
to increase by even more as liquidity deteriorates for such products.
Furthermore, in order to ensure that they can meet variation margin
on an ongoing basis, insurers will have to maintain buffers of cash,
highly liquid securities, or access to liquidity from other providers
beyond the amount of margin that is required of them at each point in
time. Using a similar calculation as we did earlier, we note that
insurers would require an increment of about $2 billion in our
constant-maturity scenario and $8 billion in our duration-extension
scenario to keep cash on hand to satisfy, say, 99 percent of five-day
movements in swaps positions--assuming that margin could be
frictionlessly netted across all contracts and accounts. This compares
with their current cash balances of about $16 billion.
Implications for the industry
Although we find it unlikely that the direct costs of posting
margin will be unbearable for the life insurance industry, these costs
could nonetheless amount to billions of dollars per year, and the bulk
of this amount would fall disproportionately on a handful of larger
firms. These firms thus have incentives to try to minimize their margin
burden.
One obvious way to reduce collateral needs is simply to reduce
derivatives positions. Since most insurer derivative use reflects
hedging, rather than speculative activity, this could result in greater
exposure to risk. However, much of insurers' derivatives-based
hedging activity reflects accounting and regulatory considerations, not
necessarily economic ones. For example, some of insurers'
receive-fixed swaps are matched to specific bonds held on their balance
sheets or otherwise qualify as highly effective hedges under GAAP. (This
explains why they maintain large portfolios of both pay-and
receive-fixed swaps.) Reducing hedging of this purely accounting sort
would not necessarily increase overall risk. Indeed, the extent to which
insurers are able to leave economic risks un-hedged will be mitigated by
regulatory pressure. It could mean an increase in GAAP earnings
volatility or in regulatory capital requirements, but insurers would
have to weigh those costs against the costs of holding margin.
On balance, however, insurers may move toward hedging strategies
that require less collateral--particularly those that involve only
cleared derivatives. As shown in table 3 (p. 24), insurers maintain
sizable portfolios of caps, floors, and other derivatives that are not,
for the moment, subject to central clearing. As noted earlier, many of
these positions are intended to hedge the optionality embedded in
various annuity and insurance products. If the cost of trading in these
products rises significantly--or if liquidity deteriorates-insurers may
find it advantageous to try to hedge some of these risks using swaps or
exchange-traded products, which could introduce basis risk.
Another way for insurers to reduce the need for derivatives
activity--or to cover the potentially higher costs of that
activity--would be to shift some risk that is currently hedged using
derivatives to other parties. For example, some companies may find it
attractive to offer insurance or annuity products that offload some
interest rate risk onto consumers. Indeed, insurance companies report
that, as a result of the new rules, they are beginning to shift their
mix of products by offering relatively less attractive pricing on
products that provide long-term guaranteed payments and more
aggressively marketing products with customer participation features,
such as certain whole life policies. If insurers find it too expensive
to hedge certain types of insurance products and pull back from offering
them, significantly raise their prices, or modify them to pass through
risks to customers, this could reduce the economic function they serve
in providing risk-sharing services to the economy. The rules could also
hasten the exit of insurance companies from variable annuities-which
have proven expensive in the low-rate environment--as the costs of
hedging guarantees on these products will increase. Many companies have
already attempted to reduce their exposures to these products either by
ceding them to captive reinsurers or by selling them outright.
Insurers will also increasingly need to maintain access to ready
sources of liquidity to cover variation margin. Without such a liquidity
buffer, insurers might have to make relatively large and rapid
adjustments to variation margin during episodes of market volatility,
perhaps contributing to fire-sale dynamics. One likely source of this
liquidity is advances from Federal Home Loan Banks (FHLBs). Insurers
maintain sizable portfolios of mortgage-related assets that qualify them
for FHLB membership (Paulson et al., 2014). And, indeed, many insurers
have begun to tap FHLBs for funds in recent years. Insurers may also
turn to the broker-dealer sector to offer term repos against their
securities portfolios or other collateral-transformation services.
However, since term repos are not available to match the duration of
long-dated swaps contracts, this strategy would be subject to rollover
risk. Particularly for riskier collateral, insurers could find their
liquidity sources evaporating during a crisis, perhaps at the same time
that variation margin is rising due to volatile market conditions.
Insurers could also look to sources of cash from elsewhere in their own
corporate structures. Securities lending operations, for example, could
potentially be scaled up to provide a source of cash for variation
margin. Alternatively, firms may look for new ways to hold liquid assets
without occupying balance-sheet space. (24)
With respect to the impact on capital, insurers may have an
incentive to move derivatives activity outside of the insurance
operating company, where they will not be subject to regulatory capital
requirements. One way this could be done is through captive reinsurance.
However, as noted earlier, captive reinsurers themselves may not
maintain reserves of cash or high-quality securities adequate to meet
margin requirements. Thus, insurers face conflicting incentives for
corporate structure when it comes to swaps margin. On the one hand, they
may wish to move derivatives transactions to nonoperating subsidiaries
that face less-binding capital constraints. On the other hand, these
subsidiaries themselves will be forced to hold high-quality collateral,
reducing their profitability.
To the extent that insurers need to shift their assets into cash or
liquid securities, they may look to offset the effect on returns by
taking additional risks elsewhere. This activity could be similar to
behavior that has been observed as insurers have faced weak investment
returns in the persistently low-interest rate environment (Becker and
Ivashina, 2013). While, in principle, larger cash positions and larger
risky-asset positions may leave the aggregate risk of their assets
unchanged, such a shift may well result in reduced liquidity for the
industry, since the higher-quality assets would now be tied up as
collateral.
Conclusion
Like other market participants, insurers that rely on OTC
derivatives face challenges from the new Dodd-Frank regulations
requiring the central clearing and collateralization of most of those
positions. We have used Monte Carlo simulations to study the amount and
type of collateral that insurers may have to hold against their interest
rate swaps portfolios over the next decade. While we find that the
industry-wide costs of collateralizing positions are likely to be
modest, there are some low-probability tail scenarios in which they
could be substantial for some large insurers, primarily because
collateral must be posted in the form of low-yielding cash assets. We
have discussed a variety of ways in which the industry might respond to
these and the other costs associated with clearing and collateralizing
derivatives positions.
Kyal Berends is a former senior associate economist and Thomas King
is a senior financial economist in the Economic Research Department at
the Federal Reserve Bank of Chicago. The authors thank Anna Paulson,
Rich Rosen, and other members of the Chicago Insurance Initiative for
helpful feedback.
[c] 2015 Federal Reserve Bank of Chicago
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ISSN 0164-0682
(1) Other risk-management techniques employed by insurance
companies include insuring a large and diversified portfolio of risks
(which reduces uncertainty), writing insurance on lines of business that
act as natural hedges (for example, the mortality risk insurers face
from life insurance contracts can partially offset the longevity risk
associated with annuities), and sharing risk with other companies
through reinsurance.
(2) The portion of the Dodd-Frank Act applying to most large life
insurance companies took effect in June 2013. Title VII of Dodd-Frank
mandates central clearing of certain types of swaps contracts, and in
May 2013 the Commodity Futures Trading Commission (CFTC) finalized its
rule indicating the specific classes of swaps for which central clearing
will be required. These include all "plain vanilla" interest
rate swaps, basis swaps, forward-rate agreements, and overnight index
swaps (OIS) written in major currencies against the standard short-term
interest rate benchmarks (the London interbank offered rate or LIBOR,
the Euro interbank offered rate or EURIBOR, and, in the case of OIS, the
fed funds rate). Credit default swaps are also covered under title VII,
and the CFTC rule applies to CDS indexes on corporate debt. The
Securities and Exchange Commission (SEC), which has yet to publish final
rules, is responsible for single-name CDS contracts. The U.S. Department
of the Treasury has determined that physically settled foreign exchange
(FX) swaps are not subject to the Dodd-Frank central clearing
requirements.
(3) Among insurance companies, the impact of the rules is only
likely to be material for life insurers, not for property and casualty
insurers, as the latter maintain substantially smaller OTC derivatives
positions, both relative to their assets and in absolute terms. Unless
otherwise stated, the terms "insurers" and "insurance
companies" refer to life insurance companies in this article.
(4) See, for example, Festa (2013). Others have analyzed similar
questions for other types of market participants. For example, Heller
and Vause (2012) examine the collateral that swaps clearing requires
from broker-dealers.
(5) While market commentary suggests that forgone revenue from
investments likely represents one of the largest potential costs to the
industry associated with Dodd-Frank OTC derivatives rules, our
calculations do not include other possible costs associated with
uncleared derivatives or operational and organizational costs that may
result from the new clearing regime.
(6) These data come from quarterly statutory filings and cover only
insurance-operating subsidiaries.
(7) We also note that although notional value is a convenient way
of summarizing the size of a derivatives position, it is not a good
measure of the potential loss or gain associated with that position,
which is typically an order of magnitude smaller. For this reason, the
importance of derivatives may be better captured by their "fair
value," which reflects their economic worth based on current market
conditions--see table 3 (p. 24).
(8) Interest rate swaps are an agreement between two parties in
which one stream of future interest payments is exchanged for another,
based on specific notional principal amounts. In a pay-fixed (or
"receive-float") interest rate swap, a company makes fixed
payments and in return receives a floating payment linked to an interest
rate. In a pay-float (or "receive-fixed") interest rate swap,
a company makes a floating payment linked to an interest rate and in
return receives a fixed payment. In both cases, the fixed payment is
agreed upon by both parties at the inception of the contract.
(9) Cummins, Phillips, and Smith (2001), Shiu (2007), and Gonzalez,
Lopez, and Cunill (2011) investigate the factors that determine
insurance companies' use of derivatives.
(10) See Berends et al. (2013) for a broader discussion of
insurers' sensitivity to interest rates.
(11) For example, in the Bank of New York Mellon Corporation and
Insurance Risk's Collateral Management Survey 2013, 7 percent of
respondents (including a global sample of large insurers) indicated that
they did not typically post variation margin, while 32 percent indicated
that they did not post initial margin (available at https://
www.bnymellon.com/_global-assets/pdf/solutions-index/collateralmanagement-survey-2013.pdf).
(12) Note that these data include collateral for both OTC and
listed derivatives, but the amount associated with the latter is very
small as insurers generally do not engage in much futures activity or
write options.
(13) The move to central clearing could actually reduce netting
opportunities in some situations by forcing insurers to clear some
trades that could previously have been netted against other trades that
will remain uncleared (and thus with non-CCP counterparties).
(14) Experiments using quarterly data did not yield substantially
different results.
(15) Most fixed-to-floating swap contracts on insurers' books
already satisfy the conditions for central clearing. Those that do not
likely differ from clearing-eligible contracts in only relatively minor
ways, such as the timing of interest payments or the day-count
convention. As noted, we essentially assume away the other types of
interest rate derivatives. Evaluating collateral that would have to be
held against nonswap contracts would be a more challenging problem
because of the diversity of such contracts and the complexity involved
in computing their fair values. Most of these positions will not, at
least initially, be centrally cleared. Margin requirements for uncleared
derivatives have yet to be finalized but are certain to be more punitive
than those for cleared positions. Given the harsher rules that will
apply to these trades, insurers have an incentive to move away from such
nonstandard contracts going forward, so that our assumption may not be
much of an exaggeration. Furthermore, the framework developed by the
Committee on Payment and Settlement Systems and the Technical Committee
of the International Organization of Securities Commissions (CPSS-IOSCO,
2013) proposes exempting uncleared derivatives from initial margin
requirements until 2019 for end-users with less than 3 trillion [euro]
in notional value. Thus, initial margin on uncleared OTC contracts will
likely not be collected from insurance companies until at least the
middle of the projection period considered here. While most CDS
contracts will be centrally cleared sooner and could in principle be
incorporated into this analysis, those positions are a fairly small
fraction of insurers' overall portfolios and do not seem likely to
significantly affect the results.
(16) Dodd-Frank mandates a 99 percent level of confidence, but the
CME (Chicago Mercantile Exchange), for example, uses 99.7 percent. As we
do here, CCPs typically assess the distributions of derivative gains and
losses for the purposes of calculating initial margin using a five-or
ten-year look-back period. Indeed, the results are roughly in line with
industry estimates, which have suggested that the initial margin
requirements will amount to anywhere from 1 percent to 10 percent of the
notional value of a single (one-way) swap contract. See, for example,
Heller and Vause (2012).
(17) The calculations here assume that potential efficiencies from
netting are completely exhausted--that is, that 100 percent of the
fairvalue gains in contracts is netted against the fair-value losses of
contracts when determining potential portfolio losses for the purposes
of calculating initial margin. In reality, these efficiencies may be
smaller, either because contracts are cleared through multiple, separate
accounts or because CCPs do not fully incorporate all netting
possibilities into their initial margin calculations. The CME has
recently begun offering cross-margining between futures and swaps
positions, possibly allowing initial margin requirements to be reduced
further for insurers with futures exposure.
(18) See http://www.cmegroup.com/clearing/financial-and-collateralmanagement/collateral-types-accepted-irs.html.
(19) This conclusion applies only to insurance operating companies.
As noted earlier, several large insurance organizations have significant
derivatives portfolios elsewhere in their corporate structure, and the
legal entities that hold them do not necessarily maintain securities
portfolios that would be adequate to cover initial margin under these
assumptions.
(20) Indeed, the demand for high-quality collateral due to OTC
derivatives requirements, bank regulatory requirements, and other
sources could create potential opportunities for insurance companies
themselves to expand their collateral-transformation services.
(21) Cash collateral for OTC variation margin receives price
alignment interest (PAI) at a short-term interest rate in the
corresponding currency. For dollar-denominated contracts, CME and LCH.
Clearnet pay PAI at the federal funds rate.
(22) The federal funds rate is not a variable in our VAR, but it is
nearly perfectly correlated with the instantaneous Treasury rate. In our
simulations, we derive the fed funds rate path from the projections for
this rate, as explained in the appendix.
(23) This amount reflects net income for domestic life insurance
operating companies only. Earnings at the consolidated parent level are
higher. For the ten firms in our sample that are publicly traded in the
United States (and thus have easily available consolidated financial
statements computed under generally accepted accounting principles
[GAAP]), net income was $19.7 billion (relative to $16.46 billion in net
income at the operating company level for these same firms).
(24) For example, although not explicitly tied to the Dodd-Frank
rules, Prudential created an off-balance-sheet entity (a special-purpose
vehicle or SPV) in November 2013 to hold Treasury securities. This
structure enables the firm to source Treasury securities as
"contingent liquidity" in exchange for notes issued to the
SPV. The Treasury securities could be sold quickly to meet variation
margin. See Prudential Financial Inc. Annual Report, 2013 (p. 91).
APPENDIX: TECHNICAL DETAIL ON THE MONTE CARLO EXERCISE
We assume that all fixed-for-floating swaps are plain vanilla and
that they are therefore subject to central clearing and initial margins
reflecting a 99.7 percent confidence threshold for five-day losses. To
calculate the change in the value of insurers' swaps positions
under the simulated rate paths, slot each firm's portfolio into 60
buckets, reflecting receive-fixed versus pay-fixed positions and
maturities of one through 30 years. We approximate the proportion of
swaps in each of these buckets for each insurer by a beta distribution
over the range 0-30 years with the parameters chosen to match the mean
and standard deviation of each insurer's actual swaps portfolio,
based on Schedule DB of their regulatory filings, as of September 2014.
For the "constant maturity distribution" scenario, we
assume that the distribution of the stock of swaps held by each firm is
fixed over time. This implies that the net flow in each maturity bucket
must be nonzero in each quarter in order to keep the portfolio stable as
contracts mature. In particular, the net amount of receive-fixed swaps
originated by firm i at maturity m in each period must be
[DELTA][x.sub.i] ( m, fixed) = B[m, [[alpha].sup.fixed.sub.i],
[[beta].sup.fixed.sub.i]] - B[m + 1, [[alpha].sup.fixed.sub.i],
[[beta].sup.fixed.sub.i]],
where B[...] is the probability density function of the beta
distribution, and [[alpha].sup.fixed.sub.i] and [[beta].sup.fixed.sub.i]
are the shape parameters for the receive-fixed swap distribution at firm
i. (1) An analogous equation holds for the pay-fixed portfolio. In
principle, this net amount could be obtained in a variety of ways. In
particular, if the amount is positive, one could terminate y notional
value each quarter and originate [DELTA]x+y in new contracts, for any
arbitrary number y. We assume that, within any type/ maturity bin, a
firm never terminates and originates contracts at the same time. Thus,
if [x.sub.i](m) is the desired notional value for the stock of swaps in
bucket m and [x.sub.i](m+1) swaps are rolling down into that bucket from
maturity m+1, the firm will either (if [x.sub.i](m+1) < [x.sub.i](m))
originate swaps with [x.sub.i](m) - [x.sub.i](m+1) notional value
without terminating any of the existing ones or (if [x.sub.i](m+1) >
[x.sub.i](m)) terminate swaps with [x.sub.i](m+1) - [x.sub.i](m)
notional value without originating any new ones. In the cases in which
firms terminate swaps, we assume that they do so without regard to the
contract's age or original maturity. New swaps are assumed to be
originated at zero fair value.
For the "duration extension" scenario, we assume that the
legacy swaps portfolio gradually matures over time. The amounts that
mature are rolled into new 30-year receive-fixed swaps.
For pricing purposes, we assume that all swaps have quarterly
payments, are indexed to the instantaneous risk-free rate, and are
priced off of the same discount curve as Treasury bonds. The m-maturity
swap rate at time t is given approximately by
[R.sub.t](m) [approximately equal to]
[[[delta].sub.t](0)-[delta](m)/[m.summation over
(n=.0)][[delta].sub.t](n)],
where [[delta].sub.t](n) is the time-t n-period discount rate. This
formula is an approximation because the numerator is only strictly
correct in continuous time and the denominator ignores intraquarter
discounting. (If swap payments were made continuously, rather than
quarterly, the formula would be exact.) The fair value (as a fraction of
notional value) of a receive-fixed swap contract with remaining maturity
m that was originated 5 periods ago, is given by the formula
F[V.sub.t], (m, s) [approximately equal to] [[delta].sub.t] (m) -
[[delta].sub.t] (0) + [R.sub.t-s](m + s)[m.summation over (n=.0)]
[[delta].sub.t] (n).
Consequently, to value the swaps portfolio, one must know both the
distribution of remaining maturities and the distribution of origination
dates conditional on the current remaining maturity.
To measure [[delta].sub.t](n), we use zero-coupon Treasury rates
through 2014:Q3 and projections for those rates from a vector
autoregression (VAR) for subsequent dates. For the m-maturity yield
[y.sub.t](m), by definition,
[[delta].sub.t] (m) = exp [-m[y.sub.t] (m)].
The data are the zero-(instantaneous), one-, three-, seven-, 15-,
and 30-year yields computed by Gurkaynak, Sack, and Wright (2007) over
the period 1986:Q1-2014:Q3. The Moody's Baa corporate yield, real
gross domestic product growth, and Personal Consumption Expenditures
Price Index inflation are also included in the VAR. We begin the sample
in 1986 because that is the first date at which 30-year yields become
available.
Data are simulated from the VAR by drawing both from the
distribution of parameter estimates and the distribution of error terms,
assuming normality for both, and simulating forward 20 quarters from
2014:Q3. The zero lower bound is imposed by rejecting any draw for which
any interest rate would be below zero at any time; in this case, the
whole vector of shocks for that period is resampled. In addition, to
reflect current forward guidance about the level of short-term rates (as
well as current market expectations), we impose through rejection
sampling that the fed funds rate cannot rise above 25 basis points until
at least 2015:Q2. (2)
For each simulated value of the six Treasury yields that are
included in the VAR, the entire yield curve is interpolated using a
quadratic spline. This allows for the calculation of the swap rate
associated with each of the 30 possible maturities at each point in
time.
To calculate the opportunity cost of holding variation margin, we
assume that variation margin must be posted in cash and is remunerated
at the fed funds rate, consistent with current practice at the major
clearinghouses. We approximate the federal funds rate in each simulation
by the equation
[ffr.sub.t] [approximately equal to] 1.072[y.sub.t] (0),
where the coefficient was estimated from an ordinary least squares
regression, with an [R.sup.2] of 0.998. We assume that, under normal
circumstances, the opportunity cost of holding cash is the Baa corporate
bond yield. Since a significant portion of insurers' securities
portfolios consist of bonds that are generally safer and thus typically
pay lower yields than Baa corporates, this is a conservative assumption.
However, occasionally in our simulations some Treasury rates (or the fed
funds rate itself) may rise above the corporate bond rate, and in that
case we use the higher rate. Specifically, the quarterly opportunity
cost is then calculated as
[VM.sub.t] x (max[[r.sub.t]] - [ffr.sub.t])/4,
where [r.sub.t] is the time-t vector of yields simulated from the
VAR.
To calculate initial margin, we first estimate the covariance
matrix of five-day changes in swap fair values between 2004:Q1 and
2014:Q3, across a 10 x 10 grid of maturities spanning zero to 30 years
and swap rates spanning 0 percent to 10 percent. In each of the same
10,000 simulations used to calculate variation margin, we calculate the
amount of each firm's receive-and pay-fixed portfolio that falls
within each of the 100 bins in the grid. Multiplying these weights by
the covariance matrix of swap value changes allows us to approximate the
five-day variance of each portfolio. (3) The initial margin is assumed
to be the 0.3 percent quantile of a normal distribution with this
variance and a mean of zero.
NOTES
(1) The amount of 30-year swaps originated each period is simply
equal to the stock of swaps maintained in the 30-year bin (that is, the
normal PDF evaluated at that point).
(2) Since some parameter draws can imply nonstationary dynamics
that lead to explosive behavior, we also impose restrictions to ensure
that no projected rate exceeds its historical maximum. In addition, we
impose that the spread of the corporate bond to the seven-year Treasury
yield cannot be negative.
(3) This calculation assumes that the initial margin that applies
to a given portfolio remains constant over time. In practice, central
counterparty clearinghouses are likely to adjust margin requirements
with the level of rates, as the conditional covariance matrix of swap
values changes is not constant. Our calculation likely errs on the
conservative side--estimating too much initial margin--because we
forecast interest rates to rise, and the volatility of a given
swap's value is generally decreasing in the level of rates.
REFERENCES
Bank for International Settlements, Basel Committee on Banking
Supervision, and Board of the International Organization of Securities
Commissions,
2013, "Margin requirements for non-centrally cleared
derivatives," Basel, Switzerland, September, available at
http://www.bis.org/publ/bcbs261.pdf.
Becker, B., and V. Ivashina, 2013, "Reaching for yield in the
bond market," working paper, October.
Berends, K., R. McMenamin, T. Plestis, and R. J. Rosen, 2013,
"The sensitivity of life insurance firms to interest rate
changes," Economic Perspectives, Federal Reserve Bank of Chicago,
Vol. 37, Second Quarter, pp. 47-78, available at
https://www.chicagofed.org/publications/
economic-perspectives/2013/2q-berendsmcmenamin-plestis-rosen.
Cummins, J. D., R. D. Phillips, and S. D. Smith, 2001,
"Derivatives and corporate risk management: Participation and
volume decisions in the insurance industry," Journal of Risk and
Insurance, Vol. 68, No. 1, March, pp. 51-91.
Festa, Elizabeth D., 2013, "New derivatives rules raise life
insurers' collateral needs," LifeHealthPro.com, June 27,
available at http://www.lifehealthpro.com/2013/06/27/
new-derivatives-rules-raise-life-insurerscollater?page_all=1.
Gonzalez, L. O., S. F. Lopez, and O. M. Cunill, 2011, "Hedging
with derivatives and value creation: An empirical examination in the
insurance industry," Frontiers in Economics and Finance, Vol. 8,
No. 1, pp. 17-42.
Gurkaynak, R. S., B. Sack, and J. H. Wright, 2007, "The U.S.
Treasury yield curve: 1961 to the present," Journal of Monetary
Economics, Vol. 54, No. 8, November, pp. 2291-2304.
Heller, D., and N. Vause, 2012, "Collateral requirements for
mandatory central clearing of over-thecounter derivatives," Bank
for International Settlements, working paper, No. 373, March.
Paulson, A., R. J. Rosen, K. Berends, and R. McMenamin, 2014,
"Understanding the relationship between life insurers and the
Federal Home Loan Banks," Chicago Fed Letter, Federal Reserve Bank
of Chicago, No. 318, January, available at
https://www.chicagofed.org/publications/chicagofed-letter/2014/january-318.
Prudential Financial Inc., 2014, Prudential Financial, Inc. Annual
Report 2013, Newark, NJ, available at http://www.prudential.com/media/
managed/Prudential-AR2013.pdf.
Shiu, Y-M., 2007, "An empirical investigation on derivatives
usage: Evidence from the United Kingdom general insurance
industry," Applied Economics Letters, Vol. 14, No. 5, pp. 353-360.
TABLE 1
Life insurers with the largest OTC derivatives portfolios
Notional OTC Statutory
derivatives assets
(--dollars in billions--)
MetLife Inc. 188 603
Manulife Financial Corp. 151 267
Massachusetts Mutual 137 202
Life Insurance Co.
New York Life Insurance Group 104 261
Nationwide Mutual Group 72 132
Voya Financial Inc. 71 193
Ameriprise Financial Inc. 65 110
AEGON 57 202
Lincoln National Corp. 52 222
Prudential Financial Inc. 44 545
Jackson National Life Group 29 186
Principal Financial Group Inc. 24 149
Allianz Group 21 116
Genworth Financial Inc. 19 70
AXA 16 166
Hartford Financial Services 12 179
American International Group 11 269
Aflac Inc. 7 111
Delaware Life Partners LLC 6 42
Sun Life Financial Inc. 5 19
Notes: OTC indicates over the counter. Includes interest rate
swaps, caps, floors, collars, and swaptions; credit default
swaps; total return swaps; and inflation-linked products. Data as
of 2014:Q3.
Source: Statutory filings via SNL Financial.
TABLE 2
Selected operating company versus consolidated derivatives
positions
Operating company Consolidated
(--dollars in millions--)
Prudential 50,179 316,283
MetLife 189,881 267,155
Manulife 169,550 209,486
AIG 17,685 90,446
Voya 69,773 73,614
Lincoln 60,009 56,864
Hartford 11,645 30,715
Principal 24,063 25,426
Notes: Data as of 2014:Q3. Includes all interest rate and credit
derivatives. Operating company amounts may not match those
in table 1 due to imperfect overlap between these categories and
OTC derivatives.
Sources: Statutory filings and 10K reports via SNL Financial.
TABLE 3
Characteristics of insurer OTC derivatives portfolios
Notional amount Fair
(millions value
of dollars)
Interest rate swaps 705,229 11,121
Receive-fixed 346,373 19,411
Pay-fixed 296,358 -9,570
Type not reported 62,498 1,279
Other rate products 326,961 1,696
Floors and puts 87,675 796
Caps and calls 184,603 716
Other 54,683 184
Credit default swaps 25,896 209
Bought protection 3,638 -33
Sold protection 16,871 183
Type not reported 5,386 59
Miscellaneous 32,957 -28
Maturity (% of notional)
< 1 1-3 3-7 7-15 > 15
year years years years years
Interest rate swaps 6 15 19 27 33
Receive-fixed 3 12 17 29 39
Pay-fixed 9 20 22 23 25
Type not reported 7 10 16 35 32
Other rate products 27 30 27 12 3
Floors and puts 53 30 3 13 1
Caps and calls 16 33 39 11 1
Other 26 20 26 12 15
Credit default swaps 17 21 56 3 3
Bought protection 33 27 31 2 7
Sold protection 19 19 55 4 2
Type not reported 0 24 73 2 0
Miscellaneous 73 4 3 7 13
Notes: Includes data as of 2014:Q3 from the 20 life insurance
operating companies with the largest OTC derivatives portfolios,
as measured by notional value. Other rate products include
interest rate collars and swaptions classified as "other."
Miscellaneous includes total return swaps and inflation swaps.
Source: Statutory filings via SNL Financial.
TABLE 4
Five-day, 1 percentile fair-value changes for interest rate swaps
of various terms
Remaining maturity (years)
Fixed 1 3 7 15 30
rate (%)
2 -0.2 -0.9 -2.0 -3.2 -3.9
4 -0.2 -0.9 -2.2 -3.6 -5.1
6 -0.2 -0.9 -2.2 -4.1 -5.9
8 -0.2 -0.9 -2.5 -4.8 -7.6
10 -0.2 -0.9 -2.5 -4.9 -8.7
Notes: Considers rate changes from the average 2014:Q4 level of
interest rates. Distribution of rate changes is based on daily data,
April 1,2004-September 30, 2014.
Source: Authors' calculations based on interest rate data provided
by the Board of Governors of the Federal Reserve System.
TABLE 5
Estimated collateral available for initial margin at top 20 swaps
users
Fair Less:
value of encumbered
securities
Cash and equivalents 16 0
Treasury securities 84 33
Agencies 25 4
Agency MBS 85 22
Foreign government 63 28
Public corporates 700 117
Total 972 204
= Available Assumed
collateral haircuts
(%)
Cash and equivalents 16 2.5
Treasury securities 50 4.5
Agencies 22 6.0
Agency MBS 63 11.0
Foreign government 35 8.5
Public corporates 583 20.0
Total 768
Potential collateralized
positions
CME-like Cash and Margin
limits (a) Treasury currently
securities pledged
Cash and equivalents 15 15 1
Treasury securities 48 48 5
Agencies 20 (b) -- 0
Agency MBS 56 (b) -- 2
Foreign government 32 (c) -- 0
Public corporates 61 (c) -- 2
Total 232 63 10
(a) Uses portfolio limits for each insurer on each asset class
based on those currently imposed on clearing members by the CME.
(b) Sum of agency debt and agency mortgage-backed securities
(MBS) must be less than 40 percent of total portfolio.
(c) Sum of foreign government and corporate bonds must be less
than 40 percent of total portfolio and $5 billion per insurer
under CME-like limits.
Notes: Amounts in billions of dollars. Data as of 2014:Q3.
Sources: Statutory filings via SNL Financial and authors'
calculations.
FIGURE 1
Fair value of collateral pledged by life insurance companies
B. Securities posted as margin
Treasury 43%
Cash 13%
Agency and agency MBS 22%
Corporate 16%
Other 6%
Notes: Data for 20 largest OTC derivatives users. Panel B as of
September 2013. MBS indicates mortgage-backed securities. Source:
Statutory filings via SNL Financial.
Note: Table made from pie chart.
