Bond ETF Pricing: Efficient or Erratic?

Note: This article was originally featured in January 2011, but in case you missed it, we are re-featuring it today as part of ETF Investing Week.

Everyone who follows and invests in the stock market, by and large, understands and is comfortable with how an exchange market works. For any security on the exchange, there is an order book with a list of buy and sell orders. Trades happen when the exchange matches a buy and a sell at the same price. This is simple and intuitive and creates an environment where everybody can know, at the same time, the fair price of any security.

The fixed-income market operates in an entirely different manner and is misunderstood by the general investing public. Fixed-income ETFs make the situation even more complex because now you have a security that trades on an exchange rapidly throughout the day tracking fixed-income securities that may trade only a few times a week. There seems to be a general view that bond ETFs are inefficient because they sometimes trade with sizeable premiums and discounts. This article will look at the factors that affect how bond ETFs are priced and will detail the reasons why, in some respects, they are more efficient than individual bonds themselves.

The easiest way to measure price efficiency is to calculate the average distance from net asset value a fund trades over time. U.S. equity ETFs with more than $100 million in assets and average trading volumes greater than 100,000 shares per day had an average deviation from NAV of 0.08% in 2010. In contrast, the average bond ETF in 2010 traded with an average deviation of 0.26%. This higher deviation from net asset value is due to a host of factors.

Fund Size and Trading Volume
Because ETFs are derivative products, there are two ways to create liquidity. An authorized participant can create or redeem shares of the ETF in the primary market, or investors can trade shares in the secondary market. As fund size grows and trading volumes increase, the trading of shares in the secondary market increases. This exchange liquidity layer allows investors to trade without affecting the underlying holdings. This is especially important in fixed-income ETFs because the underlying holdings are often not very liquid, which can make creations or redemptions of shares expensive. In general, more than 70% of bond ETF trading is part of secondary-market trading volume. A key benchmark for new ETFs is to reach $100 million in assets and regularly trade more than 100,000 shares daily. At this level of activity, there is a sufficient secondary-market liquidity layer to permit orderly trading in most market environments. Increases above these levels will continue to improve pricing efficiency, but to a smaller degree.

ETFs have allowed fixed-income investments to trade on an exchange, giving investors liquidity that was unavailable before, in the over-the-counter bond market. For example,  iShares iBoxx $ Investment Grade Corporate Bond (LQD) trades about 2 million shares per day for a dollar-weighted volume of close to $218 million. If 70% of the trading is secondary-market liquidity, the ETF has created about $152 million of additional liquidity on a daily basis. This extra liquidity helps keep bid-ask spreads tighter and deviations from net asset value smaller.

Risk
The risk of the asset class is an important measure that factors into the pricing of fixed-income ETFs, but not in the way most people would suspect. Many investors assume that the more volatile an asset class, the harder it will be to price. If you use standard deviation as a measure of risk, the riskiest fixed-income asset classes in 2010 were long-term U.S. Treasuries, international government bonds, and U.S. TIPS bonds. These asset classes have some of the most liquid fixed-income trading markets, and the ETFs that tracked these sectors traded with very small deviations from net asset value. The more important factor affecting trading costs is the relative change in risk.

An increase in standard deviation for an ETF is highly correlated with an increase in deviation from net asset value. For example, in 2007 LQD had a standard deviation of 3.72 and an average deviation from NAV of 0.48%. In 2008, in the wake of the financial crisis, the standard deviation of LQD skyrocketed to 9.35. This was an increase in risk of 2.5 times, and because of this, the average deviation from NAV increased 2.7 times to 1.33%. As the credit markets stabilized in 2010, the standard deviation went down to 5.52 and the average deviation from NAV came back down to a more normal 0.39%.

Liquidity of Asset Class
The biggest factor by far in the pricing of fixed-income ETFs is the underlying liquidity of the bonds in the portfolio. The chart below shows the average deviation from net asset value for the major fixed-income categories. You can see that U.S. government bonds have the smallest average deviation because they are the most liquid fixed-income instruments, and high-yield bonds have the highest spreads because they are the most illiquid. The numbers in the chart are only averages and the deviations fluctuate on a daily basis.

Average Deviation from NAV

Fixed-Income Sector   2010 Government   0.07% Aggregate   0.22% Municipal   0.31% International Treasury   0.37% Corporate   0.44% High Yield   0.61%

The main determinant of fixed-income liquidity is the size of the bid-ask spread. This is simply the difference between the price at which you can buy a security (the ask) and the price at which you can sell a security (the bid) at any given time. In the equity markets, the size of the spread is often as small as one penny, but in fixed income this spread can be as high as 3% of net asset value. As an investor you will never see the ETF's bid-ask spread as high as 3%, but you will see this effect in premiums or discounts to net asset value. This is because an ETF's net asset value is the average "bid" price of the portfolio of bonds. If there are inflows into the fund, new shares need to be created by an authorized participant who will need to buy the underlying bonds on the open market. To buy the individual bonds, they will pay the "ask" price of the market. When the authorized participant sells the newly created shares, they will charge a slightly higher price than they paid. If the bid-ask spread of the OTC market was 0.50%, you should expect the ETF to trade with a premium of at least 0.50% or more. Because fixed-income ETFs are a growing investment type, new shares are always being created, so you should expect, during normal market environments, bond ETFs to trade with premiums.

Recently, the municipal-bond market has been one of the most volatile sectors, as investors have become more concerned about the growing credit quality issues with state and local governments and the expiration the Build America Bond program. During the recent sell-off the largest municipal-bond ETF,  iShares S&P National AMT-Free Municipal Bond (MUB), traded at a discount to net asset value as high as 3%. Because an ETF's NAV is the current bid price of the market, an ETF should theoretically not trade very much below the NAV because the authorized participant will have strong economic incentive to arbitrage any discount away.

In reality, the discount was not eliminated because it was not a true discount. The calculation of net asset value is an attempt by a computer algorithm to price a portfolio's bonds. This calculation works well during normal markets, but during volatile, fast-trading markets, it does not adjust as quickly as the traders on the exchange. In a volatile market, fixed-income ETFs become one of the best price-discovery mechanisms to learn a portfolio's true value.

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