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What You Need to Know: ETFs Answered Liquidity Challenges in 2020

From the Nov 2020 BlackRock Alternatives Special Report 2

1 What You Need to Know: ETFs Answered Liquidity Challenges in 2020

The COVID-19 related sell-off in corporate bonds in the first quarter 2020 caused some commentators to express concern about the liquidity and functionality of fixed income exchange traded funds (ETFs) after a financial or economic shock – in particular, corporate bond ETFs.1

Widening discounts between corporate bond ETFs and net asset value (NAV) pricing after COVID-19 was cited as further evidence of ETF illiquidity. But ETF NAVs use estimated prices for underlying cash bonds, not market trades, and may quickly become stale. In contrast, ETFs trade on exchange daily, and tend to rapidly move to new equilibrium pricing in the face of a shock such as COVID-19. This makes ETF pricing timelier than NAV calculations, as the Bank of England pointed out.2

There is scant evidence the liquidity infrastructure around ETFs, as driven by authorized participants (APs}, failed during the March/April 2020 period - and trading spreads were much narrower in some fixed income ETFs than the underlying bonds.3

Fears around bond ETFs deepened after COVID crisis.

The chart below shows the extent of significant corporate bond spread widening and market dislocation in Q1 2020, in both investment grade and high yield corporate bonds, in the U.S. and Eurozone.

Concerns about liquidity and functionality of bond ETFs are driven by the perceived decline in “market liquidity” in corporate bonds since the global financial crisis (GFC), combined with the growth in assets in fixed income ETFs. The main argument cited has been that corporate bond ETFs are built from corporate cash bonds, which trade OTC in a fragmented market with severely diminished liquidity since the GFC. Hence, it is argued, after a credit event, or market shock, ETFs will become "untradeable" with no liquidity, since if all investors seek to sell at the same time, the underlying securities that compose them will be untradeable. The widening discount between ETF pricing and NAV is also cited as a failure of the arbitrage mechanism designed to keep the ETF price in line with its NAV. 

Evidence for this claim is cited as the discount that can appear in bond ETF prices to the NAV of these funds, based on the price of the underlying cash bonds, during periods of market stress. The related assumption is that discounts to NAV on this scale question the validity of bond ETFs as investment vehicles, since ETFs in other, more liquid, asset classes (such as government bonds or equities) have tended to trade much closer to NAV. This discount reached about 5% in some corporate bond ETFs during the March COVID-19 crisis.4

Insight: ETF NAVs are not based on intra-day trading prices.

It is noteworthy that NAV pricing for bond ETFs is often based on estimated prices for underlying cash bonds, as trading data may not always be available. Underlying cash bonds may not trade at all on some days, reflecting the fragmented market and diminished market-making since the GFC (it has been estimated the inventory now held by dealer-brokers in corporate bonds is currently less than $60 billion, compared with $418 billion of the inventory held pre-GFC).Nor is there an “official” price for these corporate bonds, with no exchange trading. In the absence of trading data, NAV prices are based on estimates from pricing services. 

ETF liquidity is not determined solely by the underlying instruments.

Bond ETF “liquidity” is distinct from the “market liquidity” of underlying instruments. The supply of bond ETF shares can be varied by “authorized participants” or APs – often banks, or institutional investors – who can create or redeem ETF shares in a bond ETF in response to changes in demand for the ETF. This is known as primary liquidity in the bond ETF. Secondary, or on-screen, liquidity is the trading of ETF units that already exist, which drives pricing data, volumes, etc. Overall, liquidity in the ETF will be driven by primary and secondary market liquidity.

Some bond ETFs, such as high yield, have underlying assets with poor primary liquidity, but this does not mean the ETFs become impossibly illiquid in the secondary market after a market shock. The purpose of an AP is to act as an arbitrageur and liquidity buffer between investors and the ETF provider, creating extra ETF units when demand is strong, and redeeming units when demand is weak. In a study conducted before the COVID-19 crisis, and focused on previous periods of credit market stress, the UK’s Financial Conduct Authority found fixed income ETF liquidity in Europe to be resilient6 and that lower activity APs acted as alternative liquidity providers, when large ETF discounts appeared relative to NAV.

Authorized participants act as arbitrageurs and market-makers, but there has been no stepping away.

A related concern about bond ETFs is “step-away” risk, where all APs in an ETF step away simultaneously from their arbitrage role in a highly stressed market. The U.S. Securities and Exchange Commission found no evidence in the GFC or subsequent stressed market events of this occurring. Indeed, there is evidence in a recent BlackRock report that over 60 asset owners and managers entered the market for fixed income ETFs for the first time in the first half of 2020.7

Bond ETFs with illiquid underlying securities, such as high yield ETFs, are more likely to trade at wider discounts and premiums to NAV than ETFs that hold government bonds during severe market stress because liquidity in the underlying securities is generally more reliable. This is often described as a “liquidity mismatch” problem. It arises because it may take APs longer to buy the underlying high yield cash bonds to create new ETF units in a rising market, and to sell the underlying cash bonds to redeem the ETF units sold in a falling market, after a shock like COVID-19. There is no evidence that the arbitrage mechanism failed in March 2020. On the contrary, there is evidence of net creation of units by APs during this period, and not redemptions, in some corporate ETFs.8

ETF pricing can be a useful guide to new equilibrium pricing on underlying bonds.

Sizeable discounts and premiums in ETF pricing relative to NAV can be a useful guide to the value of the underlying bonds, as the Bank of England concluded after the Q1 2020 sell-off.Faster price discovery in the ETF should not be confused with mispricing. Instead, this may be evidence ETF pricing has moved to the new, and lower, equilibrium pricing more rapidly, increasing price efficiency.

There are two main ways volatility can lead to NAVs that are less representative of “real” prices: One, yesterday’s closing price will be farther from today’s price if vol is higher. So stale prices are more inaccurate than normal; and two, in highly volatile markets, even fewer of the underlying bonds trade on any given day, so more of the NAV price is made up of estimates vs. hard trading data.

Surge in ETF trading volumes suggests bond ETF liquidity held up well, and trading spreads in many flagship ETFs widened far less than underlying cash bonds.

Trading volumes in both investment grade and high yield bond ETFs confirm there was no suggestion of a freeze in the secondary ETF market in Q1 2020, as the chart below shows.

Some investment grade and high yield ETFs showed volumes more than doubling on a daily basis over March. Similarly, although trading spreads in ETFs widened, iShares flagship ETFs moved far less than spreads in underlying cash bonds, as seen in the chart below.

This is further evidence the liquidity infrastructure around bond ETFs held up well during the crisis, and confirms the diminished liquidity and wide trading spreads in underlying cash bonds. A useful metric for gauging liquidity costs is price liquidity ratio (PLR), which looks at market impact and measures the movement in price of a security for an executed trade of a given size. A higher PLR represents a larger movement in price for a given trade size and therefore shows lower liquidity. The FTSE Russell market price/liquidity ratio in corporate bonds10 shows a pronounced deterioration during the March/April 2020 period, both in the March sell-off, and during the rally in April/May, after the Fed announced the broadening of its QE program to include corporate bonds and high yield ETFs.

2 The Liquidity Beta Sleeve

Institutional investors have policy guardrails, so strategies that acknowledge them are always of interest. II recently sat down with Bart Sikora, Director, iShares Portfolio Consulting, and Brett Talbott, VP, iShares Institutional Team, to talk about their thoughts on how institutional asset owners might manage their liquidity needs and reduce the hassle of doing so.

We were talking a few weeks ago, Bart, and you mentioned a liquid beta sleeve, which sounds self-evident, but likely is more nuanced. Can you define it for the II audience?

Bart Sikora: Liquidity sleeve is defined as a portfolio of ETFs that attempts to match the most appropriate exposures with the benchmark indices which define a policy portfolio. Policy benchmark is defined as an established asset allocation composed of indices and their weights that is put in place at public and corporate pension plans, foundations, endowments or other entities with investment policy statements. A liquid beta sleeve is intended to deliver the convenience of a strategy that addresses policy benchmark in an investment through index ETFs which are closely aligned with components of the institutional client benchmark. Public and corporate pensions have been most frequent investors. For example, a public pension plan with 70% public market holdings can obtain a close tracking with 0.10%-.25% tracking error for about 0.08-0.15% in management fees.11 A typical LBS represents 3-5% of a plan size and generally aims to precisely match the benchmark. Of course, LBS can be customized to any needs – rather than closely aligning with the benchmark, it can also be created to become a complement (i.e. offer desired attributes that differ from the policy benchmark). 

Brett, you’ve spent a lot of time thinking about precisely paring the right ETFs with policy benchmarks. What have you discovered?

Brett Talbott: The wide variety of beta exposures available through equity and fixed income ETFs allows asset owners to seek a precise pairing of the right ETFs with various policy benchmark components. In turn, we've seen the resulting ETF based liquidity sleeve can quite closely track the policy benchmark on the public asset side, down to 0.10-0.20% tracking error in many instances.12 In the most common instance, liquid beta sleeves have been adopted by public and corporate pension plans looking to create a liquidity buffer for their plans that encounter frequent flows. A typical public pension plan allocation is nearly 80% to public assets13 allowing a very close alignment for a significant portion of a policy benchmark. Corporate pensions have an even greater public allocation. On the endowment side, alternative assets tend to be much larger portion – from 60% for larger plans down to 25% for small plans14 however, a few public-asset proxy solutions exist to help better align the economic beta exposure to the alts, especially as compared to another solution of sitting in excess cash.

Let’s take a step back – what were the options available to institutional investors prior to LBS?

Sikora: Historically, institutional asset owners took three different approaches. One approach was to keep the entire allocation invested, either internally or with third party managers. This approach led to operational headaches related to frequent benefit payments or other operational needs. A second possible approach kept a portion in cash for near term expenses, but that creates cash drag. The third approach, which is what we've been seeing lately, is ETFs replacing derivatives in strategies. The selection of ETFs now exceeds the selection of derivative instruments, and ETFs may better line up with policy benchmarks, especially in fixed income and international equities. Additionally, investing with futures requires a LIBOR-like rate of cash return for a full total return experience, which can be difficult for some institutional investors to achieve.

How does the liquidity sleeve work in the context of other strategies and managers institutional investors work with?

Talbott: Structurally, a portion of the plan is allocated to the liquidity sleeve, perhaps 3-5%. With ETFs in and out execution is generally quick (T+1 settlement with trade date notification deadline), there tends to be deep liquidity and operational hassle is low. Without the liquidity sleeve, when the plan is largely invested with external managers, there might be frequent and possibly disruptive flows going in and out, as the plan lacks the liquidity buffer.

iShares can help institutional investors determine the best course of action in creating a liquidity sleeve. We recently launched a tool on where an institution can create customized ETF-based portfolios that align with policy benchmarks to get started in building the sleeve. And of course our Portfolio Consulting team can help in this effort.

So, what’s the primary goal of the liquid beta sleeve?

Sikora: The primary objective of LBS is to minimize the tracking error to the policy benchmark (or a comparable institutional benchmark for non-pension clients). As such, an appropriate ETF should be paired with each benchmark index. Matching the right asset class and the right index significantly decreases anticipated tracking error versus cash. Often, pension funds manage their portfolios with tracking error risk budget. With a properly matched up LBS, more of the risk budget can be devoted to the pursuit of alpha and not spent on cash-related tracking error. The LBS structure is intended to manage performance shortfalls in rising markets versus cash.

How has the unending vol of 2020 affected your investment strategy?

Talbott: Uptick in market volatility inevitably leads to more frequent instances of investment policy breaches. These breaches can happen in several instances: a) asset weight limits b) historical tracking error thresholds c) active risk thresholds. As was the case with the equity sell off in Feb-March of 2020, a lot of institutional owners found themselves with significant equity underweight and fixed income overweight. Having LBS in place ahead of this significant market disruption would have allowed an immediate redemption out of fixed income and proportional increase in equity weight. The alternative would have been a slower execution of physical securities, especially in the bond market as liquidity dropped. Otherwise the redemption could have taken place among external managers and be delayed by notification deadlines and month-end notification schedules.

1See “Price Gap Triggers Fears for Bond ETFs,” Financial Times, 3/30/20; “Bond ETFs Will Never Be the Same After Coronavirus,” Bloomberg, 3/23/20; “Why Most Index Funds and ETFs are Not Good Investments,” Forbes, 4/7/19.

2 Financial Stability Report, Bank of England, May 2020.

3 BlackRock, "Turning point: How volatility and performance in 2020 accelerated institutional adoption of fixed income ETFs". July 2020

4 Financial Stability Report, Bank of England, May 2020.

5Credit trends: “How ETFs contributed to liquidity and price discovery in the recent market dislocation,” S&P Global Ratings, July 2020

6 ETF primary market participation and liquidity resilience during periods of stress, M.Aquilina, K.Croxson, G.G.Valentini, Lachlan Vass, Financial Conduct Authority, Research Note, August, 2019. 

7BlackRock, "Turning point: How volatility and performance in 2020 accelerated institutional adoption of fixed income ETFs". July 2020

8Bond ETFs and underlying price uncertainty, MSCI, April 2020, Refinitiv/Lipper data.  

9 Financial Stability Report, Bank of England, May 2020.

10“Crisis? What Crisis? U.S. dollar corporate bond liquidity since COVID,” FTSE Russell, August 2020

11Source: BlackRock based on the typical portfolio consulting analysis results of 100+ institutional portfolios, aggregated over 2017-2020 period.

12Source: BlackRock based on the typical portfolio consulting analysis results of 100+ institutional portfolios, aggregated over 2017-2020 period.

13Source: P&I, Feb 2020

14Greenwich Associates, 2019


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