Putting the recent volatility in fixed income into historical perspective.
The first two months of 2020 saw outsized moves in both US Treasury (UST) yields and US credit spreads, driven by the coronavirus/COVID-19 outbreak and its significant impact on the global economic growth outlook. By the end of February, the 10-year UST yield rallied 77 bps to 1.15% whereas the US IG corporate spread widened 29 bps to 122 bps. How extreme was this market move in a historical context?
At the beginning of 2020, our proprietary risk system, WISER, estimated volatility on the 10-year UST yield at 70 bps (annualised) and IG corporate spread at 28 bps (annualised). The magnitude of the Jan-Feb move was equivalent to a 2.6-2.7 sigma (standard deviation) event. Under normal distribution assumptions, the chance of market moves larger than this in magnitude is roughly only 0.5% or less (1 in 200), so it was a really big market move — a tail event, from a risk model perspective.
However, it can be argued that using normal distribution assumptions is likely to underestimate the probability of tail events. We know that tail events in financial markets tend to occur more often than implied by normal distribution (fatter tails). Thus it may be helpful to examine the magnitudes in an empirical manner. Exhibit 1 shows frequency distribution of both series using the past 30 years of bi-monthly data (1990-2019; a total of 180 data points). The bin that the Jan-Feb 2020 move falls into is highlighted in red.
Exhibit 1: Frequency Distribution of Financial Market Shocks
Source: Bloomberg. Generic U.S. Treasury 10-year yields and Bloomberg Barclays US Corporate Bond OAS) January 1990- December 2019, as of 31 Dec 2019. Past performance is no guarantee of future results. Indexes are unmanaged, and not available for direct investment. Index returns do not include fees or sales charges. This information is provided for illustrative purposes only and does not reflect the performance of an actual investment.
In the past 30 years, there were five instances when the 10-year UST yield rallied by more than 70 bps in two months — a historical frequency of about 2.8% (1 in 36). This is almost six times more likely to happen than implied by normal assumptions but still quite an extreme tail event. It happened two times in the 1990s when yields were much higher, in the 6%-8% range. More recently, we saw a 174 bps rally in Nov-Dec 2008 at the height of the financial crisis, and two more instances in May-Jun 2010 (-72 bps) and Jul-Aug 2011 (-94 bps) in the days of quantitative easing (QE1 and QE2).
The move in IG corporate spread was relatively less extreme than it was for the 10-year UST yield. In the past 30 years there were 15 instances, or 8.3% (1 in 12) in historical frequency, when the IG spread widened by more than 29 bps in two months. This is about 16 times more likely to happen than implied by normal assumption. It happened five times before 2007 with an average widening of 41 bps, five times during the 2007-2008 financial crisis, including the 271 bps blowout in Sep-Oct 2008, and five more times after the crisis with an average widening of 41 bps. The most recent occurrence was a 32 bps widening in Jan-Feb 2016, driven by the concerns of a China-led global growth slowdown.
What does this mean for market volatility going forward? The market is likely to remain volatile in the short term, given significant uncertainty about the spread of COVID-19 and its economic impact. Indeed, the 10-year UST yield dipped further below 1.0% on March 3 after the Fed’s 50 bps emergency rate cut. Over the longer term, it depends on whether the COVID-19 impacts will be deeper or more prolonged than currently anticipated, or if the impacts will turn out to be more moderate, leading to a quick recovery to investor confidence and global growth.
The next relevant question is how long this short-term rate volatility is likely to last, assuming that Jan-Feb 2020 was already a peak in volatility this time. To answer that, we look at historical data again. Exhibit 2 shows the historical path of absolute changes (another simple measure of volatility) for each of the last five extreme moves in the 10-year UST yield. By definition, volatility will only go down from the peak. From historical experience, it usually takes two to four months for volatility to return to its long-term average (38 bps bi-monthly volatility in the case of the 10-year UST yield).
While examining past market behavior won’t necessarily help us foresee the future, it can be very valuable to frame current events into a historical context from which we can more confidently face the current shock and address its impact.
Exhibit 2: Absolute 10-Year UST Yield Changes After Big Shocks
Source: Bloomberg. Generic U.S. Treasury 10-year yields, January 1990- December 2019. Past performance is no guarantee of future results. This information is provided for illustrative purposes only and does not reflect the performance of an actual investment.
U.S. Treasuries are direct debt obligations issued and backed by the "full faith and credit" of the U.S. government. The U.S. government guarantees the principal and interest payments on U.S. Treasuries when the securities are held to maturity. Unlike U.S. Treasury securities, debt securities issued by the federal agencies and instrumentalities and related investments may or may not be backed by the full faith and credit of the U.S. government. Even when the U.S. government guarantees principal and interest payments on securities, this guarantee does not apply to losses resulting from declines in the market value of these securities.
Investment-grade (IG) bonds are those rated Aaa, Aa, A and Baa by Moody’s Investors Service and AAA, AA, A and BBB by Standard & Poor’s Ratings Service, or that have an equivalent rating by a nationally recognized statistical rating organization or are determined by the manager to be of equivalent quality.
COVID-19 is the World Health Organization's official designation of the current coronavirus.
An investment-grade (IG) rating (AAA, AA, A, BBB for example) is one that indicates that a municipal or corporate bond has a relatively low risk of default. Bonds with below investment-grade ratings (BB, B, CCC for example) are considered low credit quality and have a higher risk of default.
The Bloomberg Barclays US Corporate Bond Index measures the investment grade, fixed-rate, taxable corporate bond market.
An Option-Adjusted Spread (OAS) is a measure of risk that shows credit spreads with adjustments made to neutralize the impact of embedded options. A credit spread is the difference in yield between two different types of fixed income securities with similar maturities.
A spread is the difference in value or yield between two different types of securities (often fixed-income) with similar but not identical attributes.
One basis point is one one-hundredth (1/100, or 0.01) of one percentage point.
WISER, Western Information System for Estimating Risk, is a single risk system for all Western Asset portfolio and benchmark securities/constituents.
Standard deviation, also referred to as Sigma, is a statistic used as a measure of the dispersion or variation in a distribution, or dataset, from its mean, or average; it measures the volatility of an investment’s return over a particular time period; the greater the number, the greater the volatility.
Tail risk is a form of portfolio risk that arises when the possibility that an investment will move more than three standard deviations from the mean is greater than what is shown by a normal distribution.
A tail event is an event which has the potential to cause an investment to move by an amount more than three standard deviations from the mean value of a normal distribution.
In investing, a fat tail is a probability distribution which predicts movements of three or more standard deviations more frequently than a normal distribution. This is important because normal distributions understate asset prices, stock returns and subsequent risk management strategies
A normal distribution, in investing, is a probability distribution of returns or prices that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean. In graph form, normal distribution will appear as a bell curve.
QE1 refers to the Fed’s initial round of quantitative easing begun in late November 2008 when it started buying $600 billion in mortgage-backed securities.
QE2 refers to the Fed’s second round of quantitative easing, announced in November 2010, whereby the Fed would buy $600 billion of Treasury securities by the end of the second quarter of 2011.
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