[This article appears in September/October 2010 issue of
the Journal of Indexes.]
Over the past decade, the ETF market has expanded both in terms
of assets and market coverage. Investors can now choose from a wide
variety of equity, fixed income and alternatives markets through
The first fixed-income ETF was established in 2002. More than $160
billion is now invested in hundreds of funds listed on exchanges
around the globe.
As fixed-income ETFs have grown in popularity, a robust discussion
has evolved with respect to how the funds trade on an exchange. In
particular, recent dialogue has focused on the funds' premiums and
discounts, where an ETF's trading price diverges from its
calculated net asset value (
Some of this divergence can be traced to the mechanics that govern
ETFs across all asset classes. The rest lies in how
over-the-counter fixed-income securities behave when held in an
exchange-traded instrument. In this paper, we develop a framework
for understanding the drivers of fixed-income ETF premiums and
discounts to help investors better evaluate these funds and achieve
more efficient execution.
Premiums And Discounts
We begin by introducing the following factors that relate to
premiums/discounts and liquidity:
- Value of the underlying bond portfolio
- Level of ETF supply and demand in the secondary market
- Cost of share creation through the underlying fixed- income
- Level of fixed-income market volatility and liquidity
Investors purchase and sell shares of ETFs on an exchange,
trading them in exactly the same way as a listed stock. A share of
an ETF represents partial ownership of the portfolio of securities
in the ETF itself, much like shares in a traditional open-end
mutual fund represent partial interest in the underlying fund
holdings. What differs is the ETF's creation/redemption mechanism.
During periods of strong demand for an ETF, the price of the shares
is bid up in the market. If the ETF price is higher than the value
of the underlying securities held within the ETF, an arbitrage
opportunity may exist. Authorized participants (e.g.,
broker/dealers) could purchase the underlying fixed-income
securities, create new ETF shares and then sell the newly created
ETF shares in the market for a profit.
Conversely, this same set of mechanics operates in markets of
strong selling pressure, to help keep the ETF from trading at a
persistent discount. Authorized participants could purchase the ETF
shares (at a discount), redeem them and then sell the fixed-income
securities received from the redemption at a net profit. Arbitrage
helps keep the ETF price in line with the value of the underlying
securities. The premium or discount is calculated as follows:
Premium/discount = ETF market price - value of underlying
A premium or discount can exist and even persist for an ETF as
long as it is not large enough to trigger an arbitrage opportunity.
This means that the size of the premium/discount will be bounded by
the transaction costs participants would incur in executing the
underlying arbitrage transaction. As long as the premium or
discount is less than these transaction costs, there is no economic
incentive to execute the arbitrage opportunity.
The largest cost component is the expense to trade the underlying
securities held by the ETF, as represented by their bid/offer
spreads. This implies that an ETF can trade anywhere within the
bid/offer spread of the underlying securities market. How much of
this underlying market transaction cost is reflected in the ETF
price is a function of trading flows. In balanced markets (i.e.,
symmetrical buy vs. sell orders), there is no need for authorized
participants to access the underlying securities markets;
therefore, only a fraction of the underlying market bid/offer
spread is reflected in the price of the ETF. In unbalanced markets
(e.g., excessive buy orders), the entire underlying bid/offer
spread may be priced in.
This concept can be explained by defining the underlying bid/offer
spread as the creation cost, and the balance of trading activity in
the ETF as the flow factor.
Creation cost = bid/offer spread of underlying market
In fixed-income markets, the fund NAV is determined using the
bid side of the underlying market, while individual bonds purchased
to facilitate creation of new ETF shares are acquired on the offer
side of the market.
As a result, this creation cost is meaningful when there is
sufficient buying pressure to result in the creation of new shares.
Strong selling pressure, on the other hand, results in security
redemptions. The underlying securities received from a redemption
are sold at the bid side of the market, which is in line with where
the fund NAV is valued.
In markets where the fund NAV is determined using mid or offered
prices, the creation cost term must be adjusted accordingly.
Premium/discount = (creation cost x flow factor)
This framework may now be expanded to include other factors that
impact the arbitrage opportunity. The most significant factor is
the level of execution risk present in a market. During periods of
high volatility and low liquidity, it can be difficult for
authorized participants to execute what appears to be an arbitrage
opportunity-the magnitude of an ETF's premium or discount can move
to levels that would not be sustainable in normal markets but are
appropriate given volatile market conditions. This risk level is
called the execution risk adjustment. We add this term to determine
the premium/discount level that can exist without the presence of
an arbitrage opportunity:
Premium/discount = (creation cost x flow factor) + execution
Further adjustments are made for factors that are market
specific. In the case of fixed-income ETFs, an adjustment must be
made when evaluating end-of-day premiums and discounts. The market
standard is to value individual fixed-income securities that
comprise the ETF at the close of the U.S. bond market, 3 p.m. ET.
The fixed-income ETF itself, which trades on the stock exchange,
continues to trade until 4 p.m. ET. As a result, market movements
that occur between 3 p.m. and 4 p.m. ET may create the appearance
of premiums or discounts to NAV. The timing adjustment is generally
a fairly small portion of the total premium or discount, with the
potential exception of more volatile funds such as those that
invest in long-duration U.S. Treasurys.
Combining these factors, we see that the level of premium or
discount for any fixed-income ETF is a function of the creation
cost of the ETF, the fund flows in the ETF secondary market, the
level of execution risk for creating or redeeming shares in the
underlying bond market, and differences in the timing of bond
market and ETF valuations. A complete conceptual relationship may
now be defined:
Premium/discount = (creation cost x flow factor) execution risk
adjustment + timing adjustment
- Creation cost is defined by the bid/offer spread in the
- Flow factor is a scalar between 0 and 1, representing the
balance of ETF flows in the market (0 = all sell orders; 1 = all
- Execution risk adjustment encompasses the cost of basket
execution and intraday hedging to facilitate creation/redemption
(it is generally positive for creation activity, negative for
- Timing adjustment represents market movements between the
valuation of the underlying bond portfolio at market close and
trading price of the ETF at market close (e.g., 3 p.m. to 4 p.m.
ET in the U.S.); this may be positive or negative
As an example, consider an ETF trading at a 150 bp premium to
NAV, while the underlying securities trade at a 200 bp bid/offer
spread. The creation cost-defined by the 200 bp underlying
bid/offer spread-generally represents the largest component of the
premium. Assuming a flow factor of 0.6 and a timing adjustment of
0, the 150 bp premium would comprise 200 bps of total creation cost
weighted by the flow factor (200 bps x 0.6 = 120 bps) plus 30 bps
of execution risk adjustment.
Creation Cost:In-Kind Or Cash-Create
Creation cost is the cost of originating new fixed-income ETF
shares, and is generally the largest driver of fixed-income ETF
premiums. Given that the bonds underlying the ETF are always marked
on the bid side of the market for NAV calculations, and that the
ETF generally trades within the underlying market bid/offer spread,
creation costs are visible through the ETF premium to the NAV. This
is the reason that fixed-income ETFs trade at a premium to NAV
under most market conditions. The size of the creation cost for a
given ETF, and resultant impact on the fund premium, is dependent
upon the creation methodology used by the ETF. The two most common
creation/redemption methodologies are in-kind and cash-create
• In-Kind Methodology: With an in-kind methodology, broker/dealers
deliver bonds to the ETF provider in exchange for ETF shares. The
creation cost reflects the cost of acquiring bonds in the
underlying market; the magnitude of the creation cost varies
according to liquidity and the level of transaction costs in the
underlying bond market. Because the creation cost impact on the ETF
premium is incurred only by new investors, existing investors in
the fund are not affected.
As liquidity changes through time, so does the level of transaction
costs. This leads to changes in the creation cost and, as a result,
the level of the ETF premium. As an example, Figure 2 depicts the
premium on a Treasury inflation protected securities ETF (the
iShares Barclays TIPS Bond Fund) through time versus the bid/offer
spread in the underlying TIPS market. The chart illustrates that as
TIPS market liquidity improved through 2009, and the bid/offer
spread on TIPS securities declined, the creation cost of the ETF
(as reflected in the premium) also declined. The correlation
between the level of the premium and the level of the bid/offer
spread was approximately 0.70 over this time frame, with a
t-statistic of 15.3, indicating a high degree of statistical
• Cash-Creation Methodology: Broker/dealers deliver cash to the ETF
provider in return for new shares. All creations occur at NAV, so
this mechanism is very similar to that of traditional open-end
mutual funds. Because the broker/dealer is delivering cash to the
ETF provider and does not need to access the underlying bond
market, the premium for cash-create funds may be lower than that of
in-kind creation funds. A premium to NAV will likely still be
present (and discounts may still be possible) as the broker/dealer
still incurs intraday risk that must be hedged.
When the broker/dealer sells shares into the market, they become
short the economic exposure of the ETF. Because the broker/dealer
will purchase new ETF shares from the ETF provider at the closing
NAV, they must hedge any potential price movement between the time
at which shares are sold and the end of the day when the cash
creation occurs (i.e., the closing NAV may be above or below where
shares were priced intraday, resulting in a possible loss for the
broker/dealer). Some level of creation cost may be built into the
ETF price to account for the hedge risk and intraday market
volatility, as available hedging instruments are likely to offer an
Cash-creation funds initially take in cash and subsequently
purchase securities, so transaction costs are ultimately reflected
in the performance of the fund. While open-end mutual funds and
ETFs employing a cash-creation methodology appear to initially
shield investors from transaction costs-since they may be purchased
and sold at or near NAV (as opposed to market price)-the
transaction costs are still incurred. Instead of being borne by the
purchasing investor, however, the transaction costs are effectively
distributed among all investors in the fund.
This is a key point. Transaction costs must be borne by
investors in either the cash-create or in-kind structures. For
investors, the difference between the two is in the transparency of
the costs. With an in-kind methodology, transaction costs are
transparent in that they are reflected in the price at which the
ETF is traded. With a cash-create methodology, transaction costs
are less visible; they are embedded in the fund's performance.
This difference in transparency affects how investors perceive and
react to transaction costs. With the in-kind methodology, investors
can evaluate the impact of transaction costs they bear through the
level of premium to NAV, and adjust their trades accordingly. They
do not bear the cost of additional transactions generated by the
activity of other fund investors.
With a cash-creation methodology, investors are able to transact at
or near NAV, which initially results in lower transaction costs
(distributed among all fund investors). However, these investors
will bear the cost of subsequent transactions generated from the
activity of all fund investors.
Generally speaking, the cash-creation methodology results in lower
initial transaction costs, in return for bearing the impact of
future transaction costs created by other fund participants. The
in-kind structure, on the other hand, results in higher initial
costs, in return for protection from future transaction costs
generated by other fund participants.
The in-kind methodology is most common in more liquid markets, such
as U.S. Treasurys, where the underlying portfolio securities are
readily available. In less liquid segments of the market, such as
municipal bonds and high-yield corporate debt, some funds employ a
Hypothetical Example:In-Kind Vs. Cash-Creation
To understand the difference between the methodologies and the
impact on new and existing investors, consider the following
simplified example. For illustrative purposes, we focus only on the
impact of creation/redemption methodology, and not on the other
factors that may contribute to premiums and discounts.
Assume a hypothetical fund with one share outstanding, a market
price of $100, and an NAV of $100. The underlying market is
illiquid and has a bid/offer spread of 200 bps. Assume that a new
investor wishes to purchase one share of the fund, in effect
doubling its NAV to $200. Further assume that the new share must be
created. (In reality, some portion of an order would be absorbed by
the existing exchange liquidity of the ETF.)
For an in-kind transaction, the broker/dealer would purchase the
underlying bonds and deliver them to the ETF provider in exchange
for the share created at the NAV. The broker/dealer would pay the
offer-side price for the underlying bonds, so the price of the ETF
would likely increase from $100 to $102, offsetting the cost of the
underlying bond execution. Purchasing a new share at $102, the new
investor bears the cost of transacting in the underlying market
through the premium, while the existing investor is unaffected.
If this were a cash-creation transaction, the fund would receive
cash and immediately purchase new securities or elect to hold cash
and purchase securities over time. Either way, the fund and its
investors (both new and existing) would absorb the 200 bps in
transaction costs. The fund may also experience a return drag while
the cash is invested. Both effects impact fund performance and
contribute to tracking error.
In the case of a cash creation, the fund would invest $100 in a
market with a 200 bp bid/offer spread ($2 in transaction costs).
This would drag the overall fund's performance by 100 bps (i.e., $2
transaction costs/$200 total NAV). The original investor in the
fund would see the value of his holdings drop by 1 percent, as a
result of the new share creation. This is a subsidy to the new
investor who ended up incurring only 100 bps of transaction costs
for investing into a market with a 200 bp bid/offer spread.
Comparing the benefits and drawbacks of the two methodologies,
investors should be aware that the impact of client activity in a
cash-creation ETF is exactly the same as that of a traditional
open-end mutual fund. These funds also operate in an environment in
which all subscriptions and redemptions occur in cash.
ETF Liquidity Layer
One of the central benefits of ETFs is that they develop their own
independent exchange liquidity "layer" (through the secondary
market) as trading volume and shares outstanding grow. This
liquidity layer allows investors to trade in the ETF without having
to create or redeem shares, and can lead to the ETF's trading at a
much tighter bid/offer spread than the underlying market. To
illustrate, Figure 3 presents observed bid/offer spreads for trades
on some of the largest fixed-income ETFs relative to spreads in the
respective underlying market.
Secondary market activity accounts for the majority of trading
volume, as most ETF transactions occur without the need to trade
the underlying bond market. This secondary market liquidity is a
key benefit of ETFs generally and fixed-income ETFs in particular.
Bid/offer spreads in underlying fixed-income markets can be wide;
the secondary market helps keep transaction costs low. Figure 4
compares primary market volume (i.e., gross creation/redemption
activity) and secondary (exchange) market volume. Volume in the
secondary market dwarfs the primary market for these fixed-income
The Flow Factor
The balance of ETF flows in the market, known as the flow factor,
drives how much of the creation cost is priced into the ETF and
where the ETF bid/offer spread resides within the underlying
portfolio bid/offer spread. The flow factor is a scalar between 0
and 1 that represents the percentage of purchases vs. sales of the
fund relative to the available exchange liquidity. A flow factor
near a value of 1 indicates a high level of net purchases relative
to the available exchange liquidity, and may result in share
creations. Conversely, a flow factor near a value of 0 indicates a
high level of net sales relative to the available exchange
liquidity, and may result in share redemptions.
Figure 5 represents the dynamics of the ETF liquidity layer in a
balanced market and the impact of the flow factor on creation cost.
The gray area represents the underlying bond portfolio bid/offer,
or the full creation cost for an in-kind creation fund. The blue
area represents the ETF bid/offer. In markets where secondary
trading flows are balanced, the flow factor will be roughly at the
midpoint (approximately 0.5), and the ETF bid/offer will rest near
the midpoint of the portfolio bid/offer, all else being equal.
If the flows are predominantly buy orders, the flow factor shifts
toward a value of 1, and the bid/offer of the ETF shifts to the
right. Note that the distance between the ETF bid and offer may
remain unchanged. If buy orders are large enough to exceed the
ETF's available exchange liquidity layer, and therefore result in
the creation of new shares, the flow factor will converge to a
value of 1, and the ETF offer will converge to the underlying
portfolio offer (Figure 6). This is due to the fact that
broker/dealers must access the underlying bond market to acquire
the requisite securities in order to create new shares to satisfy
demand. In doing so, they will likely purchase bonds on the offer
side of that market. The same dynamic occurs with sales and
redemptions. Sales cause the flow factor to shift toward a value of
0. Under strong selling pressure, the flow factor converges to 0,
and the ETF bid converges to the bid side of the underlying bond
portfolio (as bond holdings will be liquidated at the bid side of
The result of this dynamic is that, once the ETF is fully priced to
the bid or offer of the underlying market, additional market impact
from large orders may be limited-the ETF is already fully
reflecting the cost of the underlying portfolio bond execution.
Figure 7 shows the average premiums for a cross section of
fixed-income ETFs during 2009 versus the estimated range of
bid/offer spreads for the underlying bond markets over the same
time period. The liquidity and bid/offer spreads of fixed-income
markets varied substantially, and the average size of fund premiums
moved accordingly. ETFs that saw strong buying interest (e.g., high
yield) tended to have premiums that averaged closer to the full
underlying market bid/offer spread. ETFs that had more balanced
flows (e.g., U.S. Treasurys) tended to have premiums that were less
than the full underlying market bid/offer spread.
The relationship between creation cost and the balance of flow
factors is summarized as follows:
- Symmetrical flows :If an ETF is experiencing relatively
symmetrical flows, the flow factor lies near the midpoint between
0 and 1, and the price of the ETF is centered within the
bid/offer spread of the underlying bond portfolio (assuming a
relatively small execution risk adjustment). Only a portion of
the actual creation cost is reflected in the fund premium,
because the broker/dealers who trade the ETF will not need to
access the underlying bond market to support ETF trading
- Strong net inflows :An ETF with demand that exceeds the
available liquidity in the market will likely have a flow factor
that approaches a value of 1. This results in the majority of the
creation cost being reflected in the ETF premium. The ETF share
price shifts toward the offer side of the underlying market, as
the broker/dealer's cost reflects the underlying bond market
execution costs of ETF share creation.
- Strong net outflows :An ETF that faces strong selling
pressure will likely have a flow factor that approaches a value
of 0. The ETF price shifts toward the bid side of the underlying
bond market in anticipation of, or in response to, ETF share
redemptions and the liquidation of bonds at the bid side of the
Figure 8 represents the behavior of the premium observed on the
iShares iBoxx $ High Yield Corporate Bond Fund (NYSE Arca:HYG)
versus its flow factor (defined as the number of shares purchased
divided by the sum of shares purchased and sold on a daily basis)
over the 12-month period ending 12/31/09.
The premium has a directional relationship with the flow factor.
The correlation between the level of the premium and level of the
flow factor was approximately 0.38 over this time frame, with a
t-statistic of approximately 6.5, indicating a high degree of
Execution Risk Adjustment
An ETF's execution risk adjustment represents the execution and
liquidity risk that broker/dealers bear when executing trades and
aggregating bond portfolios to facilitate share creation and
redemption. Because the execution risk adjustment is a measure of
execution risk, its magnitude is driven by the level of volatility
and overall liquidity conditions in the market, while its direction
is driven by whether the broker/dealer is creating or redeeming ETF
shares (generally positive for creation, generally negative for
Recall that NAV represents a weighted average of the underlying
bond bid-side prices and does not contemplate a simultaneous basket
execution. In less liquid or less transparent markets, the
theoretical bid/offer for a given bond can be highly tenuous, and
may only apply to a very narrow size of execution. Accordingly,
broker/dealers may encounter difficulty in sourcing or selling
bonds to satisfy a specified creation or redemption basket for a
certain size of transaction. The level of the execution risk
adjustment reflects the uncertainty around price discovery and
liquidity. In highly stressed markets, the execution risk
adjustment may be significant, allowing for larger-than-normal
premiums or discounts.
Figure 9 shows a situation in which market pressures have pushed
the price of the ETF to a discount. Note that the ETF bid/offer is
less than the theoretical bid side of the portfolio, indicating
that the broker/dealer has determined that the true liquidation
value received when redeeming shares lies below the theoretical bid
side of the portfolio. The distance between them (the white area)
is the execution risk adjustment.
A Case Study In Risk:September 2008
An example of a pronounced execution risk adjustment occurred at
the peak of the credit crisis. Credit markets essentially froze,
while fixed-income credit ETFs continued to trade on the exchange.
Exchange-traded funds offered a great benefit for fixed-income
market participants. In some instances, they were the only source
of market exposure and price discovery.
Nonetheless, because the underlying market was impaired, ETFs were
trading at a discount, as dealers struggled to mark positions, and
fund NAVs lagged the real-time, intraday price discovery reflected
in the ETFs. This situation reversed itself going into year end, as
many investors attempted to reallocate exposure back into credit.
Due to persistent and significant illiquidity, credit-based ETFs
shifted to large premiums, as dealers continued to wrestle with
price discovery and valuation of bonds that, in some instances,
were not trading.
Because they are exchange-traded instruments, ETFs continued to
trade throughout the crisis, providing price discovery in an
underlying market that had become highly illiquid. As liquidity was
gradually restored to the credit markets, the execution risk
adjustment declined, and premiums reverted to more historic levels.
Stressed and illiquid markets may lead to an increase in the
execution risk adjustment, which can cause larger pricing
deviations from bid-side NAVs, as ETF prices tend to more fully
reflect market risk premia and true execution costs.
During this volatile month, the iShares iBoxx $ Investment Grade
Corporate Bond Fund (NYSE Arca:LQD) functioned as a price discovery
mechanism for the illiquid corporate credit markets (Figure 10).
The blue line in the chart represents the sum of the last traded
prices for the 100 individual corporate bonds in LQD at that time.
Note that this does not indicate where the 100 bonds would have
traded in a single basket transaction.
In normal markets, there is little difference between where bonds
trade individually and where they trade as a basket. In markets of
extreme volatility, however, significant differences can arise.
What drives these price differences is that the underlying
portfolio value is not an actionable value, while the price of the
ETF is actionable. Consider the week of September 15. Due to the
decline in market liquidity, many bonds did not trade on certain
days. In some cases, only 70 percent of the underlying portfolio
traded on a given day. Market participants who were transacting in
LQD had to value the underlying bonds as well as the risk and
transaction costs associated with trading bonds that had not
The light blue band in Figure 10 represents the risk premium of the
underlying assets due to market volatility. Prices of bonds in the
underlying portfolio moved significantly and displayed wide trading
spreads across short time periods. Market participants in LQD
widened their spreads and changed prices in line with where they
could effectively make a market, considering their need to
simultaneously hedge risk (i.e., the execution risk adjustment).
Using the fundamental underlying portfolio value as a starting
point for fair value, and incorporating the additional risk premium
due to volatility and market uncertainty (as shown by the light
blue band), we see that LQD traded appropriately in the context of
the market (as shown by the green line). The fund provided price
discovery that reflected the level of market risk as well as
investor sentiment at the time. Similar market dislocation and
price discovery were observed in a number of other fixed-income
markets during this time, including high-yield corporates and
The Arbitrage Mechanism: A Check On Premiums/Discounts
As discussed above, the ETF bid/offer should be anchored inside the
underlying portfolio bid/offer (Figure 5); otherwise, arbitrage
opportunities may exist. It is important to note that the level of
liquidity and pricing transparency in the fixed-income markets is
generally lower than that of the equity markets. As a result,
premiums and discounts on fixed-income ETFs can persist for longer
time periods than those on equity ETFs. For equity ETFs, a premium
or discount can be identified relatively easily by anyone with
access to exchange tick data. Executing the arbitrage requires only
the ability to electronically trade a list of equities, which is
available to a large number of market participants. Because of
these equity market efficiencies, true premiums and discounts are
generally quickly taken advantage of and corrected.
In the fixed-income markets, pricing information is fragmented, and
views of valuation often differ widely among market participants.
There is no live tape of fixed-income executed prices. Few sectors
have reliable execution data available, and often at a delay; a
limited portion of the fixed-income market trades on any given day.
As a result, many fixed-income securities are valued daily, using
some form of algorithmic or matrix pricing scheme that creates an
estimate of value based on the pricing behavior of those securities
that have actually traded.
Fixed-income ETFs trade on an exchange, but the underlying
securities trade over-the-counter. Only the most liquid sectors
offer electronic trading platforms. For many sectors, especially
corporate and municipal bonds, trading a specific list of
securities to execute a creation or redemption may take hours or
even days. All of these factors make it difficult to identify
whether an arbitrage opportunity exists. When an investor does
identify an apparent opportunity, they may have further challenges
in acting on it.
Timing Adjustments:NAV Vs. ETF Valuation
The last factor that drives fixed-income premiums and discounts is
the timing difference between when a fund NAV is calculated and
when the ETF trading day ends. For NAV calculations, the bond
portfolio underlying a U.S. fixed-income ETF is valued at 3 p.m.
ET, whereas the ETF continues to trade until the 4 p.m. equity
market close. Significant market movements can occur between 3 p.m.
and 4 p.m. Depending on the direction of these movements, large
discrepancies can arise, resulting in the appearance of premiums or
discounts to NAV. Although the impact of this factor is small under
most market conditions, it does create pricing noise, which can
obscure the dynamics discussed above.
As an example, consider the iShares Barclays 20+ Year Treasury Bond
Fund (NYSE Arca:TLT). A rally in U.S. Treasurys after 3 p.m. can
result in the ETF closing at a premium to NAV, as the ETF continues
to trade until 4 p.m., while the NAV was set at 3 p.m.
Figure 11 shows a strong directional relationship between changes
in 30-year U.S. Treasury yields (between the 3 p.m. and 4 p.m.
market closes) and the premium/discount observed in TLT, from
12/31/09 to 2/26/10. The levels-based correlation over this time
series was -0.91 with a t-statistic of -13.5, indicating a high
degree of statistical significance.
This phenomenon does not exist in U.S. domestic equity markets,
because market trading hours for the underlying securities and the
ETF are in sync. It does, however, occur with non-U.S. equity
market ETFs, in which the underlying market closes while the ETF
continues to trade in U.S. market hours.
Understanding The Factors
As with other types of exchange-traded funds, fixed-income ETFs
have an arbitrage mechanism that helps ensure they trade at a price
consistent with their underlying portfolios, level of liquidity and
market risk. By understanding the factors that drive fixed-income
ETF pricing, investors can better evaluate and utilize these funds.
As a result both of structural and technical factors, fixed-income
ETFs generally trade at a premium to NAV. Premiums or discounts to
NAV may appear to deviate more significantly than investors are
accustomed to observing in equity ETFs. When evaluating
fixed-income ETFs, it is important to keep two key points in
mind:First, fixed-income transaction costs are incurred
irrespective of the investment vehicle utilized; second,
fixed-income markets exhibit illiquidity and volatility that become
more visible through the lens of an exchange.
On the first point, investors must realize that regardless of
whether they purchase bonds individually, through an ETF or through
a mutual fund, the cost to trade fixed-income securities will be
incurred eventually. What differentiates over-the-counter markets
like fixed income from exchange-traded equity markets is that both
sides of the market are generally not visible. As a result,
investors may be unable to fully ascertain the true cost of their
When accessing fixed-income markets through a mutual fund or an ETF
that employs a cash creation/redemption methodology, investors are
theoretically able to purchase the portfolio at or near the NAV,
but transaction costs are still incurred. Furthermore, these costs
are distributed among all investors in the fund, and are ultimately
reflected in the fund's performance.
Fixed-income ETFs utilizing an in-kind methodology generally trade
at larger premiums or discounts than comparable cash
creation/redemption ETFs (or mutual funds, which trade at NAV, by
definition). However, the presence of these premiums/discounts
provides investors with transparency into the true costs they incur
to access fixed-income markets through the in-kind ETF structure.
Investors in an in-kind structure are also shielded from subsequent
transaction costs arising from the activity of other fund
investors. This transaction cost transparency is a key benefit to
Second, liquidity in fixed-income markets can be intermittent, and
market prices often lack transparency. These are simply attributes
of fixed-income markets themselves. Bringing over-the-counter bond
markets to an exchange through the ETF structure makes market
anomalies more visible to investors. These are not "problems" with
fixed-income ETFs; they are simply the normal dynamics inherent to
fixed-income markets which, heretofore, many investors have been
unable to observe.
A Closer Look At Two Drivers Of Premiums And
How do the individual drivers of premiums and discounts combine to
influence premium behavior? Taking a high-yield bond ETF (NYSE
Arca:HYG) as an example, we can gauge the impact of certain
For practical purposes, we isolate the two largest drivers of
premium behavior:creation cost and flow factor. We exclude the
execution risk adjustment from this analysis, because it is
difficult to quantify and can vary across dealers (it is a function
both of market risk premia and dealer positioning). Likewise, we
exclude the timing adjustment, as intraday data in the
over-the-counter high-yield market is not broadly available.
Our analysis is based upon a monthly time series (from the launch
of HYG on 4/11/07 to 12/31/09) and two independent variables:
- Average monthly flow factor:Average percentage of purchases
relative to total purchases and sales each month.
- Average creation cost:Average bid/offer spread observed in
the underlying securities each month.
These independent variables are regressed against a dependent
variable-the fund's average monthly premium-to better understand
their impact. Given limitations in the underlying data set, it was
necessary to use a monthly time series instead of a daily series.
And because our base conceptual model is multiplicative (i.e.,
average monthly premium = average monthly flow factor x average
creation cost), it was necessary to use a log-based regression,
which prohibits negative numbers. As a result, the one negative
premium observation in the series was removed. This is consistent
with a framework that employs only the average flow factor and
average creation cost, assuming the flow factor is between 0 and 1,
and bid/offer spreads are always positive. Under such a framework,
discounts to NAV (i.e., negative premiums) are not possible, as
they could only exist as a function of the execution risk
adjustment or timing adjustment. Figure 12 summarizes our results.
Results indicate statistical significance, as evidenced by the
R-squared, correlation coefficient and the significance of
The individual t-statistics also indicate a high level of
significance for each independent variable. From this analysis, we
may conclude that both the flow factor and the creation cost
strongly influence the ETF's premium.
This analysis was designed to ascertain the significance of the
flow factor and creation cost in driving premium behavior in HYG,
rather than to form the basis for a predictive model of this
behavior. If and when data becomes available to expand the model
and include other variables-such as the execution risk adjustment
and timing adjustment-we may gain even greater insight into
observed ETF premiums and discounts, and possibly formulate a more
Source:BlackRock, as of 12/31/09.
The t-statistic is a measure of an independent variable's ability
to explain the behavior of a dependent variable. A value of
approximately +/- 2.0 is generally considered to be significant
under a normal distribution. T-statistics on levels-based data may
be influenced by the presence of autocorrelation. Results, however,
were similar after adjusting for such effects, where present, using
Even in funds that primarily utilize the in-kind methodology, it
may be advantageous in certain instances (such as fund rebalancing)
to accept a cash creation/redemption in order to manage fund cash
flow and minimize trading activity and transaction costs.
Additionally, in-kind transactions may not be possible in all
markets, due to limitations in security delivery and settlement.
This hypothetical example does not represent any specific
Raw data was sourced from the New York Stock Exchange (NYSE Arca
TAQ) and subjected to an algorithm to determine purchases vs.
Because bid/offer spreads in high-yield securities are difficult to
observe and quantify, the Barclays Capital Liquidity Cost Score for
the Barclays Capital U.S. Corporate High Yield Bond Index was used
to proxy bid/offer spreads in the underlying high-yield market.
R-squared measures "goodness of fit" and represents the percentage
of total variation in the data explained by the statistical model.
The correlation coefficient signifies the correlation of the
behavior between the statistical model and the dependent variable.
The F-statistic is the ratio of the variance in the data explained
by the statistical model relative to the variance not explained by
the model. The significance of F-statistic indicates the
probability that the statistical model is irrelevant in explaining
the behavior of the dependent variable.
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