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Sunday, June 7, 2015

Bond Market Volatility - Yawn

Recent bond market moves have triggered some rather excited commentary. Central banks allegedly have pumped up a bubble that will cause the financial markets to explode in some amazing fashion. The reality is a lot more sedate – the bond market is bracing for a Fed rate hike sequence that may hit this autumn (assuming that it is not delayed – again). Given that governmental interest rates are at levels that are completely unattractive for liability matching (outside of Greece!), no sensible asset allocator should care about a marginal repricing in bonds. The only reason you want to own bonds is an insurance against a selloff in equities (and other risk assets)  and a few rate hikes by the Fed is not enough to trigger an equity correction by itself.



Chart: U.S. Employment Ratio
The chart above shows that the employment ratio in the United States has once again ticked up. Unless the fallout from the oil patch gathers steam, the job market still has enough momentum to look through temporary slowdowns. The United States is a long way from overheating, but it is getting harder and harder to justify keeping the policy rate near zero.

Events in Greece do hang over the global markets; it would be very easy for a Greek exit to trigger very bad things for global risk markets. My view that the eurocrats’ primary objective is that they do not want anything to interrupt their summer vacations. As a result, I think there is a good chance of the can being kicked yet again down the road, for at least a few months. Nevertheless, it appears that the long-term prospects are much gloomier.

Treasury Market Volatility

Chart: U.S. 10-year Treasury Yield and Volatility
The chart above shows the 10-year Treasury yield (top panel) and the associated historical (normal) volatility in the bottom panel. (The historical volatility is calculated over a 40 trading day window.)

Normal volatility is the standard deviation of daily (absolute) changes of the yield; it is expressed above in terms of basis points per day (100 basis points = 1%). This is also sometimes expressed as an annualised figure (you multiply the daily volatility by the square root of the number of trading days in a year).

This is a different convention from the way that is usually expressed in other markets (such as equities), where volatility is given in terms of the standard deviation of percentage changes of prices. Expressing the volatility in this fashion would make comparisons between different points of the yield curve meaningless (as it would just validate the fact that long-duration bonds have more price volatility than short-duration debt).

When we look at the data, we see that recent volatility is in no sense unusual. It is possible that intraday volatility is higher (courtesy of High Frequency Trading), but there is a simple solution to this volatility – turn off the price screens and go back to doing useful work.

Chart: 3-Month Change in 10-year Treasury Yield
Daily volatility matters if you are trading options. However, if prices are going up and down rapidly within a tight trading range, there is no reason for an asset allocator to care. What matters for asset allocation is how fast yields are moving in one direction. The chart above shows the 3-month change in the 10-year yield (on an end-of-month basis). It has been common for the 10-year yield to move 100 basis points over a quarter. Such an event is possible this year (assuming the Fed indeed hikes rates), but it is hard to see an overshoot much further than that. As a result, there is no reason to think that anything of particular interest will happen (for those of us without levered bond positions).

It should be noted that the German 10-year bund yield (not shown) has been more volatile than the U.S. 10-year Treasury Note. Apparently, it is not a good idea to buy 10-year paper at sub-0.50% yields. I had thought the Japanese experience in 2003 was enough to teach that lesson, but it seems that the current generation of traders had some new theories about bond valuation. A rapid cleanout of nonsensical positions is a standard market event, but such moves do not last too long. A serious bond bear market needs to be ratified by central bank rate hikes.

Log-Normal Versus Normal Volatility 

There is an alternative means of looking at the volatility of bond yields – log-normal volatility. This is calculated by taking the standard deviation of the percentage change in yields. (You can get the same effect by taking the standard deviation of the changes in the logarithm, hence the name.) For example, if the 10-year yield is 5%, and the log-normal (annual) volatility is 20%, that implies that the annualised standard deviation of the yield is 100 basis points (20% of 5%).

You can price fixed income options using either form of volatility (after making the appropriate conversion). However, the two models generate different predictions about bond yields. In a log-normal world, the daily changes in bond yields should become lower and lower as the yield drops towards zero. That is, if the log-normal volatility is unchanged, and the bond yield drops from 4% to 2%, the daily changes will be half the size. Using such a framework, negative rates are impossible. If you instead use a normal volatility, the size of the daily changes is independent of the level of rates. This makes it possible for the option-pricing model to predict negative interest rate outcome.

Looking back at the earlier chart, we see that volatility has not fallen that much since the early 1990s, despite the collapse in the level of yields. As a result, we see that real-world markets are somewhat closer to normal volatility than log-normal. (More sophisticated option-pricing frameworks allows volatility to act as a blend of these two cases, which allows for a better fit of this behaviour.)

Chart: 10-year JGB yield and volatility
Japanese yields offer a good deal of experience with a low rate environment. The 10-year JGB yield is less volatile than the U.S. 10-year yield, but it has kept stable despite the crazily low level of yields in 2015. The highest volatility was recorded in 1998, even though the yields were mainly below 2%. Therefore, we see that log-normal volatility is not the best description of yield volatility.

Concluding remarks

A certain amount of bond market turmoil around a rate hike cycle is to be expected, but there is no reason for anyone not directly involved in the fixed income markets to care.

See Also:


(c) Brian Romanchuk 2015

5 comments:

  1. Brian,

    Others seem to be looking at this differently ?

    https://seekingalpha.com/article/4351356-burden-of-bullish-bearish-meme-unleash-total-power-of-compounding-and-large-numbers-laws

    ReplyDelete
    Replies
    1. Not sure I see the link? I was commenting about volatility, not seasonality.

      Delete
  2. I just wanted you to take a look Brian.

    Remember Alan Longborn ?

    https://seekingalpha.com/author/alan-longbon#regular_articles


    Alan was a MMT through and through for years. A bit like you knows it inside out. Has been around for years in Bill's blog very early on.

    He writes for Robert Balan now and I was speaking with Alan at the weekend. This is what he said.

    " I have learned things from Robert P Balan that puts the MMTers to shame and shows they are wrong about some important things but still have the clearest view of things compared to the mainstream. "

    None of them will tell me what these things are...

    I've tried all weekend to no avail.

    This guy that Warren says uses fixed exchange rate anlysis. Is tied very closely with that group and knows Alan well.

    https://seekingalpha.com/user/7143701/instablogs


    Says we are all wrong on certain things.

    " never had a losing trade in Treasury-bond futures since 1979. Nominal gNp hit 19.2% in the 1st qtr 1981, the FFR to 22%, & AAA Corporates to 15.49%. My prediction for the peak in AAA corporate yields for 1981 was 15.48% (& that bonds would bottom in Oct). Predicted the month stocks bottomed in 82 & in 84. Predicted the 87 crash. Predicted the top in the Y2K bubble. Predicted that the top in stocks would be July 2007. Predicted the severe contraction in the 4th qtr of 2008 in January of that year. Identified the bottom in stocks as March 2009. The markets confused me only once - when the FED executed QE2 (but I nailed the bottom in the CPI in Jan 2011 i.e., 7 months before it bottomed out). "

    " Like Dr. William Barnett said (a former NSA Rocket Scientist).
    “the Fed should establish a “Bureau of Financial Statistics”. You can't duplicate this accounting today.
    1979: Double-entry Bookkeeping on a National Scale
    --------------------------
    Loans and investments 1229.8
    Cash and Due from Banks 169.5
    Total Assets—Total Liabilities and Net Worth 1480.3
    Demand Deposits 400.5
    Time deposits 675.8
    Borrowings 180.5 (principally e-$s since 1969)
    Currency outside the banks 106.1
    Reserve Bank Credit 128.3
    MONETARY AND BANKING CHANGES End of 1939 to end of 1979 (figures in billions of dollars)
    (1) Net effect on the volume of time and demand deposits and borrowing of all factors, except commercial bank credit (principally capital accounts) 13.5
    (2) Net expansion of commercial bank credit 1189.1
    (3) Net increased in time and demand deposits and borrowings 1202.6
    Source: Computed from data reported in All-Bank Statistics, U.S. 1896-1955
    Federal Reserve; and the Federal Reserve Bulletin
    The fact is that from a systems' standpoint the banks pay for their earning assets with new money not existing deposits. This drastically changes everything in macro. For instance, the source of time deposits is demand deposits, i.e., the bank collectively pay for what they already own (very stupid and less profitable). So the domestic banks could undercut offshore lending, FX.
    M1 = currency outside the banks plus DD, including U.S. Treasury General Fund Account
    M2 = M1 plus all time deposits in the DFIs "




    How do you think I predicted the two flash crashes, one in stocks, the other in bonds? Rates-of-change in monetary flows, volume times transactions' velocity = RoC's in P*T in American Yale Professor Irving Fisher's truistic "equation of exchange"."

    As my good friend told me: Dr. Leland J. Pritchard, in his letter 9/8/81: “you may have a predictive device nobody has hit on yet”.


    You can see the discussion here Brian

    https://seekingalpha.com/article/4356705-what-went-wrong-in-1971


    It's annoying me for 2 reasons


    a) I've known Alan for a long time pure MMT'r through and through ?



    b) This isn't the usual critique 's we get. They keep it to themselves and they know MMT.

    Robert Balan and Alan are smarter than this other guy they know.








    ReplyDelete
    Replies
    1. I don't have time to look at this, but the person who is doing most of the posting is Salmo Trutta on Seeking Alpha? Salmo just vomits nonsense in the comments on my articles at SA; I just ignore him. I do not really care to wade through endless tracts that consist of random observations about the U.S. banking system.

      Delete

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