Summary of My Post-CPI Tweets

February 15, 2017 1 comment

Below is a summary of my post-CPI tweets. You can (and should!) follow me @inflation_guy or sign up for email updates to my occasional articles here. Investors with interests in this area be sure to stop by Enduring Investments. Plus…buy my book about money and inflation, published in March 2016. The title of the book is What’s Wrong with Money? The Biggest Bubble of All; order from Amazon here.

  • The timing of Yellen’s testimony was useful for her. Given base effects, y/y CPI may drop to 2.1% from 2.2% today. So y’day she >>>
  • >>>could sound hawkish, having a sense that today she’d get a decent CPI. It’s base effects that could drop CPI – but that’s optics.
  • Last Jan, core CPI printed 0.293%. Anything less than 0.23% will cause y/y to tick downward. Feb is also a tough hurdle.
  • But these MAY be tough hurdles because of tricky seasonals. Certainly Jan’s number could be. But this is why we look at y/y.
  • Actually, the BLS revised some of that…core was 0.293% in Jan originally but now comparison is a trifle easier at 0.266%.
  • So revising my prior tweet: anything less than 0.20% will cause y/y to tick downward. Feb’s hurdle will be 0.25%.
  • Well howdy doo. Core CPI +0.31% m/m, far above consensus and pushing y/y to 2.3% (actually 2.26%) when it was expected to fall to 2.1%.
  • That’s a whoops.
  • That’s the highest m/m core in a decade. At least, after revisions have lowered some peaks.

bfmcedd

  • Housing y/y 3.12% from 3.04%, Apparel +1.0% from -0.04%. Medical Care 3.86% vs 4.07%.
  • Last 12 m/m figures from CPI. At least the last 5 look like a kinda scary trend. Probably illusory.

last12

  • Core services 3.1% y/y, unchanged. But core goods -0.2% vs -0.6% last mo.
  • That’s curious given dollar strength but a good reminder that the dollar isn’t inflation destiny.
  • So within Housing, Primary Rents slackened to 3.93% vs 3.96% y/y. OER also ebbed, 3.54% vs 3.57%.
  • So rise in housing was less important parts: household energy (3.51% vs 2.45%) and various furnishings. Again, those are core goods.
  • New and used motor vehicles, which is 6.6% of CPI, bumped up to -0.86% vs -1.03% y/y.
  • In Medical Care: drugs 4.85% vs 4.81%, Prof Svcs 2.94% vs 3.11%, Hospital 4.05% vs 4.28%. Again, goods not services.
  • Not sure how to feel about the goods bumps. On the 1 hand that’s what has held core down so possibly signif. But also less stable.
  • Core inflation EX housing, 1.35% y/y, up from 1.21% but still pretty low and down from the level of a year ago.
  • Core CPI back near highs, but not there yet.

bfm4f15

  • Hey, on the plus side this ought to help tomorrow’s 30y TIPS auction.
  • So here are the four pieces, in reverse order of stability. 1. Food & Energy. Not a surprising story but headline, not core.

fande

  • Core goods. This is the current surprise. Might be seasonal adj issue. But if this goes to 1%, it’s a big story.

coregoods

  • Core services less rent of shelter. Things like medical care. Have been softer, mild uptick this month. Core over 3% needs this.

coresvcsnoros

  • Rent of Shelter. No sign of any letup here, so no disinflation in sight.

ros

  • I guess the story of CPI today is that it’s a new story. It wasn’t housing, wasn’t medical care. It was the little stuff. Core goods.
  • That MIGHT mean that it’s a one-off, seasonal thing. But also could mean that inflation is broadening.
  • Here is a chart of the weight of CPI categories that are rising faster than 3%.

3pctweight

  • …and the weight of categories deflating. So recent rise is more about the deflationary tails ebbing.

less0weight

  • Early estimate of Median CPI: 0.26%, y/y to 2.60%. But median category is an OER subcategory so my estimate may be off.
  • A good time to remember not to put too much weight on one month’s number.
  • BUT, after Feb, 7 of the next 9 months will compare to prior year’s figures under 0.2%.
  • If we avg 0.2142% for rest of year on core CPI (that’s the avg of last 4 months we’ve seen), 2017 will come in at 2.70% core.
  • Thinking about inflation more? Think about reading my book:

cover

  • OK that’s all for now on CPI. One more note: I can’t think of a single way this is positive for equities. Or fixed-rate bonds.
  • If you’re a pension fund, that means you should read our recent article with some urgency:
  • Bottom line today is that CPI *may* be one-offs…but it’s hard to argue bearish on inflation with the highest m/m core in a decade.

I don’t have a lot to add to this, other than to point out that if Yellen was trying to sound hawkish yesterday, thinking she could back off today after a soft CPI, then she set a trap for herself. After a solid CPI, she will either have to double down on the hawkish rhetoric or somehow soften her remarks at an awkward time for that. I do not believe for a minute that Yellen, the most dovish Chairman in history, is eager to raise rates in March. But I also believe that she has set herself up to lose a lot of credibility now if the Fed fails to act. The one possible saving grace is that the FOMC meeting in March is on the same day as the next CPI figure, so depending on the month-to-month wiggle she might save some face.

But it is also possible, and I think increasingly probable, that the next CPI is also firm. I don’t think we will get another 0.3%, but an 0.25% would also be disturbing. With core goods the main contributor this month, and core services taking the month off, a resumption of the strengthening from core services is not out of the question.

Don’t read too much into this one number. But looking at the contour of the recent inflation data, you can be forgiven for taking precautions.

Categories: Tweet Summary

Pension Fund Perils: Why Conventional Pairing of LDI with De-risking Glide Paths Produces Inferior Outcomes

February 9, 2017 1 comment

Milla Krasnopolsky, CFA and Michael Ashton, CFA[1]

Combined use of traditional Liability Driven Investment (LDI) and funded status responsive de-risking strategies should be decoupled or rebuilt. Embedded inconsistencies in the treatment of risks in these two elements of what has become a popular pension strategy cause irreconcilable conflicts in their execution and imperils the positive pension fund outcome.

This article provides a critique of the combined LDI / De-risking Glide Path strategy as currently implemented by many pension plan managers and also provides an example of an alternative solution that better improves pension plan outcomes.

deriskingboxApproaches to pension risk management have passed though many phases over the past 40+ years.  Higher rate environments of the 1980s made liability immunization programs with treasuries very attractive, but traditional 60/40 or balanced fund strategies persisted as the dominant strategy for pensions.  As rates began their secular decline, funding levels continued to deteriorate and while liability-driven investing became popular again in the beginning of the new millennium, significant levels of underfunding prevented most pensions from fully matching their assets and liabilities.  A variety of partial risk mitigation solutions began to emerge as the lower rate environment of the past 20 years forced institutional investors to be exposed to higher levels of market risk.  New asset classes were introduced into pension plan portfolios in order to achieve higher returns and higher levels of diversification.  Adverse market volatility was further reduced through creative solutions that incorporated smart beta and risk allocation strategies that delivered lower-volatility at similar levels of long term return.  Other strategies sold liquidity back to the market in order to generate additional return in a low yielding environment.  Some risk-based approaches also introduced interest rate derivative overlay programs to extend interest rate duration of total assets along with equity risk reduction programs to reduce equity market risk.  Finally, de-risking glide paths – and ultimately liability risk transfer to insurance companies – became in vogue as companies continued to struggle with their asset-liability risk and found it expedient to pay insurance companies to assume the problem for them.

In recent years, much has been written about whether pension funds have sufficient assets to support their liabilities, and clearly the source of much of this angst is that…many of them don’t.  One thing that is clear is that after decades of chasing new and creative solutions, the problem of underfunded pension plans is still here and the debate about who should manage the assets, and how they should be managed, continues with ever-increasing urgency.

This article represents our contribution to this debate, with a special focus on the asset allocation requirements for cost effective pension plan de-risking.

 

Two Shortcomings of Traditional LDI and De-risking Strategies, as Combined

Type of risk

At this point it is important to differentiate the assets that function as liability hedges and those assets that better assist with the process of de-risking as the plan glides towards a fully hedged status.  Long duration bonds function as the best hedge for the liabilities, and as the plan’s funded status improves and the de-risking process proceeds, the allocation to bonds increases.  While bonds and bond-like derivatives are a core staple of liability-driven investing (LDI) strategies, for most underfunded plans that have a goal of full funding with some help from asset performance it is economically infeasible to allocate 100% of the assets to the liability-matching portfolio.  A gradual increase in bond assets over time as funding status increases is part of the de-risking asset allocation process.  This is an important distinction between LDI and the process of de-risking.  If the liability-matching assets allow the plan to better lock in the current funded status level, then it is only the remaining assets that allow that plan to reach the next funded status threshold in order for the plan to de-risk further.  Traditionally, these non-LDI assets are exposed to a significant amount of equity beta, as the long-term expected compensation from taking equity risk is positive.  While it is thought to be true that, in the long term, equity beta risk is well compensated, the trouble is that in the shorter time horizon of de-risking process the equity beta is very much dependent on market valuations that are not related to the valuation of the pension liabilities. Therefore, it becomes a tactical rather than a strategic decision to hold equities for a de-risking plan.

While all pension models focus on longer-term horizons, pensions in a de-risking mode have a much lower risk tolerance in the short term.  This has caused many pensions to allocate assets to a variety of alternative investments in order to diversify away from equity beta risk.  However, this practice also introduces other risks to the plan, some of which are illiquidity, currency, and/or additional credit default risk.  So there is an inconsistency: while pension funds are known for taking the very long view when it comes to illiquidity, if the sponsors are pursuing an LDI/de-risking strategy the additional illiquidity is counterintuitive, given the objective to be dynamic and nimble in the de-risking process.

But assuming that potential illiquidity is at least somewhat of a concern to a pension fund manager, then the Hobson’s choice between equity risk or illiquidity likely means that underfunded pension plans that are pursuing joint LDI/de-risking strategies are still carrying too much equity beta risk, or are slowing down the de-risking process while equity risk is mitigated through other less liquid investments, or both. Pension fund managers and their advisors sense this, but tend to reach a type of asset allocation compromise where pension returns may be less optimal and de-risking results are less effective.

So if equity beta isn’t desirable as unrelated to the liability, and illiquidity of many other alternatives make them less-desirable for dynamic rebalancing into LDI assets, what is the most effective way to replace the equity beta for a de-risking plan?  What other forms of beta and/or alpha are appropriate in aiding in the process of de-risking?  From the standpoint of Markowitz efficient frontier generation, risk is a function of return variance and the covariance of the returns of the eligible portfolio elements. Beyond that, to the optimization routine risk is risk. That is, it doesn’t matter whether the risk comes from beta or from alpha.  From the standpoint of the de-risking process, when it comes to the non-LDI assets or return generating assets, alpha is preferred to most beta since alpha is more process-dependent as opposed to market-dependent.   In the shorter-term horizon of de-risking, non-LDI beta introduces more risk.  So our only choice seems to be some combination of liquid alpha and/or well compensated liquid beta that has some correlation to liabilities.  This particular beta may be different from how the liability matching or LDI assets are invested and doesn’t need to match the performance of the liabilities, but should have a positive correlation with liability performance.  That’s a tall order.

Some of the more publicized alpha alternatives are hedge funds, private investments in equity or debt of corporations, or real estate.  We don’t intend to dive into the merits and disadvantages of these or other alternative investments on a stand-alone basis but will only superficially observe their fit in a de-risking framework.  Many hedge funds return as much beta as alpha – indeed, the fact that there are successful hedge-fund replication techniques is virtual proof that many hedge funds are actually beta masquerading as alpha. The obvious visual correlation between hedge fund returns and equity returns, too, should make one suspicious that hedge funds are a pure source of alpha (see Chart, source Bloomberg, comparing the HFRI Fund of Funds Composite Index to the S&P 500).

hfriFigure 1: HFRI Fund of Funds Composite Index vs S&P 500

While those hedge funds or private investments that have a higher correlation to fixed income beta may benefit plans with a long time horizon, they suffer from varying degrees of illiquidity, which impedes the de-rising process as previously discussed.

While there may be other examples for a better alternative, we can provide one strategic example that better fits the combined LDI / de-risking criteria we have discussed in this article.

 The Better Alternative

We have addressed above the type of risk that pension funds do not want to have. But it behooves us as well to point out one type of risk that pension funds really ought to have, and yet tend to be underinvested in: inflation exposure, or more accurately real interest rates.

There is a competent literature about the importance of inflation-linked assets to the pension plan.[2] Importantly, inflation-linked assets are relevant even if the pension benefits are not themselves inflation-linked, since for most pension plans the formula which links the work history of active participants to their future retirement benefits implicitly means that pension benefit accruals for a particular employee are higher the more that employee earns. Since wages generally rise at least partly because of inflation, this implies that any pension fund with active participants still accruing benefits does in fact have some inflation exposure.

But the importance of inflation to the pension plan goes beyond that liability-side insight. Additionally, pension assets are exposed to inflation – and, especially, large changes in inflation – because on the asset side the majority of the assets of most plans are invested in equities and nominal fixed-income. Both of these asset classes are terribly exposed to increases in inflation, especially when inflation rises above 3-4%.[3]

We can go still further. While the effects just mentioned are well-established in the literature, one additional benefit from owning inflation-linked assets has not been discussed as far as we can tell, and that is this: the relative value of inflation-linked bonds, compared to nominal bonds, is related to the business cycle and/or level of interest rates level in the same way that corporate spreads are – but without default risk. The chart below (source: Bloomberg data) highlights the connection between credit spreads and 10-year breakevens.[4] This is important because for most pension funds, the relevant interest rate for discounting liabilities is not the risk-free Treasury rate, but a risky corporate rate; therefore, the liability has credit spread risk and an asset that co-moves with credit spreads – especially without actually having credit risk – is valuable.

creditvsbreaksFigure 2: Inflation spreads (“Breakevens”) vs Credit spreads

In our opinion, given a choice between equity beta and inflation/real rate beta, there is no choice: inflation-linked assets are clearly the more valuable risk for a pension fund to own.

Now, pension plans that are pursuing de-risking along with LDI are typically loathe to replace equity risk, given its advantage (over a full cycle, although not necessarily at any given point) in expected return, with real interest rate risk. But inflation-linked markets have an additional benefit, at least in 2017 – they are inefficient, and produce myriad opportunities to generate alpha along with their useful beta. Indeed, we have designed an investment strategy that addresses all of these requirements:

  • Historical return commensurate with equity returns, with slightly lower total risk
  • Beta from inflation-linked bond markets, which is relevant to pension fund liabilities
  • Risk sourced from useful beta, as well as alpha
  • Implied credit spread exposure, without actual credit risks, which is relevant to pension fund liabilities
  • Superior liquidity to “alts” such as real estate, private equity, or hedge funds – which is more consistent with the de-risking mandate

We call this strategy “Enhanced Systematic Real Return.” In a nutshell, this strategy holds the combination of inflation-linked bonds and breakevens that most efficiently adds inflation protection for a given level of interest rates, and adjusts these proportions based on the richness or cheapness of inflation-linked bonds to capture additional alpha.[5]

 

Magnitude of risk

After determining a different, if not more efficient risk vehicle for the non-LDI assets we now turn to the discussion of how much of this risk should be taken at every point of the glide path.  Should the risk allocation to return generating risk assets (i.e non-LDI assets) only depend on the dollars allocated to these investments or should the risk allocation be independent of dollars allocated and vary based on the level of leverage and/or asset composition?

Not All Risk is Bad

As we have already alluded, prudent risk has some place in the management of a pension fund on a glide path. Yet, as with the villain in the black hat, we have been conditioned to look at the word “risk” and recoil. But not all risk is bad. Certainly, with LDI approaches risk is a negative – after all, the goal of LDI is to maximize the funded status (difference between assets and liabilities), subject to a limit on the maximum volatility (risk) of the funded status. In that construction, there is no doubt that risk is bad, or anyway that less risk is better. But risk is not necessarily bad for de-risking.

This seems counter-intuitive. If we are trying to remove risk, doesn’t that imply that risk is bad? Yes – as we just said, risk is bad for the LDI-driven mandate. But the plan that takes less risk has fewer opportunities to reach de-risking thresholds. That is, the more that you de-risk the longer the next increment of de-risking takes. In this context, it is actually helpful to retain more rather than less risk in the non-LDI assets at each de-risking step.

Here is an analogy from basketball: consider the player who constantly heaves up three-point shots. He shoots a lower percentage from beyond the arc, and so the variance of his scoring is quite a bit higher than his variance shooting short jumpers or layups. Let us suppose that on average, he scores the same amount per game whether he shoots three-pointers or short jumpers. In an asset management context, we would say that this is a “non-optimized” shooter. He should aim for the same average scoring with lower volatility, right?

Now let us suppose that in a particular game, this player’s team is down by 18 points in the final quarter. The coach sends the player onto the court. If this coach is from the pension industry, he instructs his shooter to take only safe shots, because that is how he maximizes his Sharpe Ratio. But if this is actually a basketball coach, he orders his player to take as many three-pointers as he can. Why? He does this because in this situation, risk is good. A strategy of only taking safe shots is guaranteed to lose in this context; only a highly-volatile strategy has a chance of working.[6]

In the same way, prudent addition of volatility as the plan is de-risking helps to de-risk a plan that is under water. So we can see that there is a tension here, and one that is routinely ignored in most LDI/de-risking plans: more volatility is helpful for de-risking, but hurtful inasmuch as it departs from the LDI mandate to maximize the return/risk tradeoff for the funded status. This leads to the phenomenon that is common today, of “hurry up and wait.” As we noted previously: the more that a fund has been de-risked, the longer the next increment of de-risking takes. Each reduction of the proportion of return generating assets to total assets significantly increases the average time until the next de-risking point is reached, as the table below[7],[8] illustrates:

table1Table 1: Reducing return-generating assets will tend to increase time to next trigger

This is problematic. By de-risking, this plan is becoming too conservative as it approaches being fully funded. We can show that the plan reaches a fully-funded status more quickly when it prudently avoids full de-risking. What happens when we allow leverage, and maintain the total portfolio risk even as the bond allocation increases at each trigger? The following table shows the significant result:

table2Table 2: By maintaining portfolio risk to return-generating assets, de-risking proceeds apace.

 

Combining the Right Type, and the Right Magnitude, of Risk

When the pension plan pursues a strategy that focuses on risks sourced from alpha and the “right kinds” of beta sources that will tend to match the liability, and de-risks in a way that recognizes that some risk helps the de-risking task, then the combined result can be powerful. The chart below (Source: Enduring Intellectual Properties, Inc) compares this new approach with the “classic” LDI plus de-risking approach. The dashed lines represent the “classic” approach, while the solid lines represent an approach that uses our “Enhanced Systematic Real Return” strategy as a substitute for the equity risk of the traditional strategy. In each case, this imaginary pension fund starts year zero at 60% funded, and liabilities grow with the Bloomberg/Barclays/Lehman U.S. Long Government/Credit Index. Also in each case, the top line represents the 90th percentile outcome of the Monte Carlo simulation; the bottom line represents the 10th percentile, and the middle line represents the median outcome.

comparativeglidepathsFigure 3: Proper types and magnitudes of risks produce preferable pension outcomes.

There are several facets of this chart worth noting.

Importantly, observe how the median outcome line is linear with our approach, but flattens out with the traditional de-risking approach. This phenomenon is the visual counterpart to Tables 1 and 2; it illustrates how the closer one gets to being fully funded with a traditional glide path, the slower the funded status converges. Our approach, as highlighted in Table 2, is designed to remove that effect. The benefits of that approach aren’t only felt on the median outcome, but are apparent on every path as the funded status moves above 75%.

Also, observe that the superior “good” outcomes aren’t “paid for” by much worse “bad” outcomes. After all, we could have had even better “good” outcomes if we took lots of extra risk. But in that case, the benefit would have come at a price, and we would see it manifesting in much worse “bad” outcomes. The outcomes here are actually skewed to the positive side.

Finally, although you cannot tell this from the illustration, you should know that this simulation assumes that stocks and bonds have expected returns that are somewhere near their historical mean returns. Unfortunately, presently this seems a generous assumption for the traditional approach. It seems more likely that, going forward, pension plans which are invested heavily in equities will be drawing from a distribution with worse-than-average characteristics due to the high starting valuations. Ditto, of course, for fixed-income…but at least bonds affect both sides of the LDI equation.

Summary

LDI and de-risking glide paths can be combined under certain conditions, but current implementation practices create inconsistencies in how risks are treated and do not facilitate achievement of strategic goals.

Asset beta risks that do not match liability beta risks are useful only in a tactical setting, and then only if they are associated with exceptional returns (that is, the market is cheap tactically).

More effort is required to search out new sources of liquid alpha and beta that facilitate the de-risking process. We have produced one that we believe is useful in this context.

As the plan de-risks along the glide path, the level of risk in the non-LDI assets should be adjusted to preserve a quantum of variance that is useful in the de-risking process, as opposed to just mechanically adjusting allocation dollars in a simple glide path.


[1] Milla Krasnopolsky is an investment strategist and investment manager. Milla held previous positions as a Managing Director of Fixed Income Markets and Strategic Solutions at General Motors Asset Management and as a Principal and Senior Investment Consultant at Mercer Investments.  Michael Ashton is the Managing Principal of Enduring Investments and CEO of Enduring Intellectual Properties, Inc.

[2] For the iconic example, see Siegel and Waring, “TIPS, the Dual Duration, and the Pension Plan” (Financial Analysts Journal, September/October 2004).

[3] Remarkably, the myth that common stocks confer some inflation protection has survived decades of contrary experience, both before and after Zvi Bodie’s classic “Common Stocks as a Hedge Against Inflation” (Journal of Finance, Vol. 31, No. 2, May 1976), in which he concluded forcefully “The regression results…leads to the surprising and somewhat disturbing conclusion that to use common stocks as a hedge against inflation one must sell them short.”

[4] The 10-year simple “breakeven” is merely the yield difference between the 10-year nominal Treasury yield and the 10-year TIPS real yield; it represents roughly the amount of future inflation at which an investor would be indifferent between the two types of bonds.

[5] It would be inappropriate to discuss the fine details of this strategy in a thought piece such as this. However, we thought it important to point out that demand for a solution with these characteristics is not hopeless or uninformed. There does exist at least one such solution, and probably others!

[6] This idea isn’t exactly alien in finance: if you own an out-of-the-money option, a higher implied volatility increases your delta while if you own an in-the-money option, a higher implied volatility decreases your delta. It’s just alien in pension fund management.

[7] Both Table 1 and Table 2 represent simplified examples where LDI hedging assets and pension liabilities are proxied by the same long-duration bonds, and future pension contributions are excluded from the analysis.

[8] Table is based on a Monte Carlo simulation of a pension fund that begins with the indicated funding status and allocated as shown until it reaches the next de-risking trigger. Returns for stocks and bonds are simulated; the correlation from the last five years is used. The importance of the table isn’t derived from the precision of the assumptions, but from the illustration of the increased difficulty in reaching the next de-risking increment when the fund is already de-risked substantially.

Entering the RINF Cycle

February 6, 2017 Leave a comment

Because I write a lot about inflation – we all have our spheres of expertise, and this is mine – I am often asked about how to invest in the space. From time to time, I’ve commented on relative valuations of commodities, for example, and so people will ask how I feel about GLD, or whether USCI is better than DJP, or whether I like MOO today. I generally deflect any inquiry about my specific recommendations (years of Wall Street compliance regimes triggers a nervous tic if I even think about recommending a particular security), even though I certainly have an opinion about gold’s relative value at the moment or whether it is the right time to play an agriculture ETF.

But I don’t mind making general statements of principle, or an analytical/statistical analysis about a particular fund. For example, I am comfortable saying that in general, a broad-based commodity exposure offers a better long-term profit expectation than a single-commodity ETF, partly because of the rebalancing effect of such an index. In 2010 I opined that USCI is a smarter way to assemble a commodity index. And so on.

When it comes to inflation itself, however, the answers have been difficult because there are so few alternatives. Yes, there are dozens of TIPS funds – which are correlated each to the other at about 0.99. But even these funds and ETFs don’t solve the problem I am talking about. TIPS allow you to trade real interest rates; but when inflation expectations rise, real interest rates tend also to rise and TIPS actually lose value on a mark-to-market basis. This can be frustrating to TIPS owners who correctly identify that inflation expectations are about to rise, but lose because of the real rates exposure. What we need is a way to trade inflation expectations themselves.

When I was at Barclays, we persuaded the CME to introduce a CPI futures contract, but it was poorly constructed (my fault) and died. Inflation swaps are available, but not to non-institutional clients. Institutional investors can also trade ‘breakevens’ by buying TIPS and shorting nominal Treasuries, since the difference between the nominal yield and the real yield is inflation expectations. But individual investors cannot easily do this. So what is the alternative for these investors? Buy TIP and marry it with an inverse Treasury ETF? The difficulties of figuring (and maintaining) the hedge ratio for such a trade, and the fact that you need two dollars (and double fees) in order to buy one dollar of breakeven exposure in this fashion, makes this a poor solution.

There have been attempts to fill this need. Some years ago, Deutsche Bank launched INFL, a PowerShares ETN that was tied to an index consisting of several points on the inflation-expectations curve. That ETN is now delisted. ProShares at about the same time introduced UINF and RINF, two ETFs that tracked the 10-year breakeven and 30-year breakeven rate, respectively. UINF was delisted, and RINF struggled. I lamented this fact as recently as last March, when I observed the following:

“Unfortunately, for the non-institutional investor it is hard to be long breakevens. The CME has never re-launched CPI futures, despite my many pleadings, and most ETF products related to breakevens have been dissolved – with the notable, if marginal, exception of RINF, which tracks 30-year breakevens but has a very small float. It appears to be approximately fair, however. Other than that – your options are to be long a TIPS product and long an inverse-Treasury product, but the hedge ratios are not simple, not static, and the fees would make this unpleasant.”

And so when people asked me how to trade breakevens, when my articles would mention them, I had to shrug and share my distress with them, and say “someday!”

But recently, this started to change. As TIPS late last year awoke from their long slumber, and went from being egregiously cheap to just typical levels of cheapness (TIPS almost always are slightly cheap to fair value), the RINF ETF also woke up. The chart below shows the number of shares outstanding, in thousands, for the RINF ETF.

rinfsoTo be sure, RINF is still small. The float – although float is less critical in an ETF that has a liquid underlying than it is in an equity issue – is still only around $50mm. But that is up 1200% from what it was in mid-November. The bid/offer is still far too wide, so as a trading vehicle RINF is still not super useful. But for intermediate swing trading, or as a longer-term hedge for some other part of your portfolio…it’s at least available, and the increase in float is the most positive sign of growth in this area that I have seen in a while. So, if you are one of the people who has asked me this question in the past: I no longer have a fear of an imminent de-listing of RINF, and it’s worth a look.

Categories: New Products

The Fed Needs More Inflation Nerds

January 30, 2017 5 comments

Earlier today I was on Bloomberg<GO> when the PCE inflation figures were released. As usual, it was an enjoyable time even if Alix Steel did call me a ‘big inflation nerd’ or something to that effect.

The topic was, of course, PCE – as well as inflation in general, how the Fed might respond (or not), and what the effect of the new Administration’s policies may be. You can see the main part of the discussion here, although not the part where Alix calls me a nerd. A man has some pride.

My main point regarding the PCE report was that PCE isn’t terribly low, but rather right on the long-run average as the chart below (all charts source Bloomberg) shows. Of course, PCE has been lagging behind the rise in CPI, but because it had been “too tight” previously this isn’t yet abnormal.

spread

However, in the interview I didn’t get to the really nerdy part. Perhaps my ego was still stinging and so I didn’t want to highlight the nerdiness?[1] No matter. The nerdy part is that the reason PCE is low is actually no longer because of Medical Care, but because of housing. This next chart plots the spread of core CPI over core PCE, through last month’s figures, versus Owners’ Equivalent Rent (OER).

vs-housing

Housing has a much higher weight in the CPI than in the PCE, and as you can see the plodding nature of OER means that the correlation is somewhat persistent because housing inflation is somewhat persistent. Right now, OER (which, frankly, I thought would have leveled off by now) is rising and showing no signs of slowing, and this fact has served to widen the CPI-PCE spread back to its historical average and likely will cause it to widen to an above-average level. I suppose the good news there is that it is still true that outside of housing, core inflation is still not rising aggressively. Core services ex-housing are looking perkier, but core goods continue to languish as the dollar remains strong. The strength of the dollar almost beggars belief if it’s true that the rest of the world hates us now, but it is what it is.

The bigger point, for markets, is “so what?” There is nothing about a 1.7% core PCE that presents any urgency for Chairman Yellen. As I said on the program: as Yellen approaches the end of her chairmanship (in January 2018, since she insists Trump won’t chase her out before), I believe it is much more likely that she wants to be remembered for pushing the unemployment rate very low – because she believes inflation is easily controlled – than that she wants to be remembered for being a hawk that stopped inflation from getting going. She isn’t worried about inflation, and so the question is whether she wants to be criticized for adding “too many” jobs, or not adding enough. Not that monetary policy has much to do with that, but I believe she clearly will err on the side of keeping policy too loose. The Fed isn’t tightening this week, and I find it unlikely that they will tighten in March, unless inflation expectations rise considerably further than they have already (see chart of 5y5y inflation forward from CPI swaps, below). Even after the big rally since late last year, 5y5y is well below the long-term average through 2014.

5y5y

And even if inflation expectations do rise further, the excuse from the chair will be easy: expectations are rising because the end (and possible reversal) of the globalization dividend and the imposition of tariffs will lead to higher prices. But there is nothing that Fed policy can do about this – it is a supply-side effect, just as high oil prices due to OPEC production restraints would represent a supply-side effect that the Fed shouldn’t respond to. So the excuses are all there for Dr. Yellen. History will show that she missed a chance to shrink the Fed’s balance sheet and avert the worst of the next inflationary upturn, but that history will not be written for some time.

[1] Ridiculous, of course. I embrace my nerdiness, at least when it comes to inflation.

Categories: CPI, Economy, Federal Reserve Tags:

Summary of My Post-CPI Tweets

January 18, 2017 Leave a comment

Below is a summary of my post-CPI tweets. You can (and should!) follow me @inflation_guy or sign up for email updates to my occasional articles here. Investors with interests in this area be sure to stop by Enduring Investments. Plus…buy my book about money and inflation, published in March 2016. The title of the book is What’s Wrong with Money? The Biggest Bubble of All; order from Amazon here.

  • Last CPI of 2016…fire it up!
  • Core +0.23%, a bit higher than expected. Market was looking for 0.16% or so.
  • y/y core CPI rises to 2.21%. The core print was the second highest since last Feb.
  • For a change, the BLS has the full data files posted so brb with more analysis. Housing subcomponent jumped, looking now.
  • Just saw this. Pretty cool. Our calculator https://www.enduringinvestments.com/calculators/cpi.php … pretty cool too but not updated instantly.
    • BLS-Labor Statistics @BLS_gov: See our interactive graphics on today’s new Consumer Price Index data http://go.usa.gov/x9mMG #CPI #BLSdata #DataViz
  • As I said, housing rose to 3.04% from 2.90% y/y. Primary Rents jumped to 3.96% from 3.88%; OER 3.57% from 3.54%.
  • Household energy was also higher, so some of the housing jump was actually energy. But the rise in primary rents matters.
  • Will come back to that. Apparel y/y slipped back into deflation (dollar effect). Recreation and Education steady. “Other” up a bit.
  • In Medical Care, 4.07% vs 3.98%. That had recently retraced a bit but back on the + side. Drugs, Prof. Svcs, and Hospital Svcs all +
  • Medicinal drugs. Not a new high but maybe the retracement is done.

drugs

  • Core services up to 3.1% from 3.0%; core goods -0.6% vs -0.7%.
  • That’s consistent with our view: stronger USD will keep core goods in or near deflation but it shouldn’t get much worse.
  • The dollar is just not going to cause core deflation in the US. Import/export sector is too small.
  • Core ex-housing rose to 1.20% from 1.12%. Still not exactly alarming!
  • Not from this report, but wages are worrying people and here’s why:

atlfedwages

  • However, wages tend to follow inflation, not lead it. I always add that caveat. But it matters for Fed reaction function.
  • Next few months are the challenge for renewed upward swing in core CPI – Jan and Feb 2016 were both high and drop out of the y/y.

corecpi

  • Early guess at Median CPI, which I think is a better measure of inflation…my back of envelope is 0.24% m/m, 2.61% y/y…new high.
  • CPI in 4 pieces. #1 Food & Energy (about 21%)

fande

  • CPI in 4 pieces. #2 Core Goods (about 20%)

coregoods

  • CPI in 4 pieces. #3 Core Services less Rent of Shelter (about 27%)

coresvcslessros

  • CPI in 4 pieces. #4 Rent of Shelter (about 33%)

ros

  • This is why people are worried re’ inflation AND why people dismiss it. “It’s just housing.” Yeh, but that’s the persistent part.
  • Scary part about rents is that it’s accelerating even above our model, and we have been among the more aggressive forecast.
  • OK, that’s all for this morning. Anyone going to the Inside ETFs conference next week? Look me up.

We end 2016 with the outlook in limbo, at least looking at these charts – unless January and February print 0.3% on core inflation, core CPI will be hanging around 2% for at least the next few months. Median inflation is more worrisome, as it will probably hit a new high when it is reported later today, but it doesn’t get the ink that core CPI or core PCE gets.

To my mind, the underlying trends are still very supportive of a cyclical (secular??) upswing in core inflation. Here’s a summary of two of the pieces that people care about a lot. Housing is much bigger, but slower; Medical Care is more responsive, but smaller.

lastchart

I suspect that chart is enough to keep most consumers jittery with respect to inflation, but as long as retail gasoline prices stay below $3/gallon there won’t be much of an outcry. But that doesn’t matter. M2 money growth accelerated throughout 2016 as the economy improved, and ended the year at 7.6% y/y. Interest rates are rising, which will help push money velocity higher. It’s hard to see how that turns into a disinflationary outcome.

Categories: CPI, Tweet Summary

The Yield Curve is Critical of Fed Credibility

I was planning to write an article today about the shape of the yield curve. Since the Global Financial Crisis, the Treasury curve has been very steep – in early 2010 the 2y/10y spread reached almost 300bps, which is not only unprecedented in absolute terms but especially in relative terms: a 300bp spread when 2-year yields are below 1% is much more significant than a 300bp spread when 2-year yields are at 10%.

2s10s

But what I had planned to write about was the phenomenon – well-known when I was a cub interest-rate strategist – that the yield curve steepens in rallies and flattens in selloffs. The chart below shows this tendency. The 5-year yield is on the left axis and inverted high-to-low. The 2y/10y spread is on the right axis. Note that there is substantial co-movement for the recession of the early 1990s, throughout the ensuing expansion (albeit with a general drift to lower yields), in the recession of the early 2000s, the ensuing expansion, and the lead-up to the GFC.

and5yyields

I was ready to point out that the steepening and flattening trends tend to be steady, and I was going to illustrate that they feed on themselves partly for this technical reason: that when the curve is steep, steepening trades (selling 10-year notes and buying duration-weighted 2-year notes, financing both in repo) tend to be positive carry and therefore easier to maintain, while on the other hand when the curve is flat the opposite tends to be true. So the actual causality of the relationship between steepening and rallies is more complex than it seems at first blush.

It would have made a very good article, but then I noticed that since 2010 or so the tendency has in fact reversed!

Specifically, from 1987-1995 the correlation of the level of the 5-year spread to the level of the 2s/10s spread was -0.78. From 1995-1999, the correlation flipped to +0.48 (but I didn’t bother to de-trend the data and I suspect that correlation stems more from the strong, 350bp decline in interest rates from 1995-1999). From 1999-2009, the correlation was -0.81. Since 2010, the correlation is +0.60: the curve has tended to flatten in rallies and steepen in selloffs. And, in the recent bond market selloff, the curve steepened as long rates rose further than short rates.

This is interesting. Clearly, carry dynamics cannot explain why the relationship is inverted. I think the answer, though, is this: since 2010, the overnight has been anchored. That isn’t different than in the past – from late 1992 to early 1994, the Fed funds target was anchored at 3%. But the difference is that back then, traders acted as if the Fed might eventually move the overnight rate in a meaningful way. Since 2010, investors and traders have attributed no credibility to the Fed, with virtually no chance of a substantial move over a short period of time. Accordingly, while short interest rates historically have tended to be the tail wagging the dog, while longer-term interest rates move around less as investors assume the Fed will remain ahead of the curve and keep longer-term inflation and interest rates in a reasonable range…in the current case, short term rates don’t move while longer-term rates reflect the market belief that rates will eventually reach an equilibrium but over a much longer period than 2 years as the Federal Reserve is dragged kicking and screaming.

I happen to agree, but it isn’t a great sign. I suppose it was destined, in a way – “open mouth” operations can only work in the long run if the Fed is credible, and the Fed can only be credible in the long run if it delivers on its promises. But it hasn’t. This is probably because the Fed’s forecast have been worse than abysmal, meaning its promises were based on bad forecasts. In such a case, changing one’s mind when the data changes is the right thing to do. But even more important, if your forecasts are frequently wrong, is to shut up and stop trying to move markets where you want them with “open mouth” operations. I have said it for 20 years: the worst thing Greenspan ever did was to make “transparency” a goal of the Fed. They’re just not good enough at what they do to make their activities transparent…at least, if they want to maintain credibility.

* * *

Administrative Note: On Monday I will be conducting the third and final in a series of webinars on inflation and inflation investing. This series will be done on the Shindig platform, sponsored by Enduring Investments, in cooperation with Investing.com. This webinar is on “Inflation-Aware Investing.” You can sign up directly with Shindig here, or find the webinar link at Investing.com.

A (Very) Long History of Real Interest Rates

December 23, 2016 3 comments

One of the problems that inflation folks have is that the historical data series for many of the assets we use in our craft are fairly short, low-quality, or difficult to obtain. Anything in real estate is difficult: farmland, timber, commercial real estate. Even many commodities futures only go back to the early 1980s. But the really frustrating absence is the lack of a good history of real interest rates (interest rates on inflation-linked bonds). The UK has had inflation-linked bonds since the early 1980s, but the US didn’t launch TIPS until 1997 and most other issuers of ILBs started well after that.

This isn’t just a problem for asset-allocation studies, although it is that. The lack of a good history of real interest rates is problematic to economists and financial theoreticians as well. These practitioners have been forced to use sub-optimal “solutions” instead. One popular method of creating a past history of “real interest rates” is to use a nominal interest rate and adjust it by current inflation. This is obvious nonsense. A 10-year nominal interest rate consists of 10-year real interest rates and 10-year forward inflation expectations. The assumption – usually explicit in studies of this kind – is that “investors assume the next ten years of inflation will be the same as the most-recent year’s inflation.”

We now have plenty of data to prove that isn’t how expectations work – and, not to mention, a complete curve of real interest rates given by TIPS yields – but it is still a popular way for lazy economists to talk about real rates. Here is what the historical record looks like if you take 10-year Treasury rates and deflate them by trailing 1-year inflation:

dumbrealThis is ridiculously implausible volatility for 10-year real rates, and a range that is unreasonable. Sure, nominal rates were very high in the early 1980s, but 10%? And can it be that real rates – the cost of 10-year money, adjusted for forward inflation expectations – were -4.6% in 1980 and +9.6% in 1984? This hypothetical history is clearly so unlikely as to be useless.

In 2000, Jay Shanken and S.P. Kothari wrote a paper called “Asset Allocation with Conventional and Indexed Bonds.” To make this paper possible, they had to back-fill returns from hypothetical inflation-linked bonds. Their method was better than the method mentioned above, but still produced an unreasonably volatile stream. The chart below shows a series, in red, that is derived from their series of hypothetical annual real returns on 5-year inflation-indexed bonds, and backing into the real yields implied by those returns. I have narrowed the historical range to focus better on the range of dates in the Shanken/Kothari paper.

skreal

You can see the volatility of the real yield series is much more reasonable, but still produces a very high spike in the early 1980s.

The key to deriving a smarter real yield series lies in this spike in the early 1980s. We need to understand that what drives very high nominal yields, such as we had at that time in the world, is not real yields. Since the real yield is essentially the real cost of money it should not ever be much higher than real potential economic growth. Very high nominal yields are, rather, driven by high inflation expectations. If we look at the UK experience, we can see from bona fide inflation-linked bonds that in the early 1980s real yields were not 10%, but actually under 5% despite those very high nominal yields. Conversely, very low interest rates tend to be caused by very pessimistic real growth outcomes, while inflation expectations behave as if there is some kind of floor.

We at Enduring Investments developed some time ago a model that describes realistically how real yields evolve given nominal yields. We discovered that this model fits not only the UK experience, but every developed country that has inflation-linked bonds. Moreover, it accurately predicted how real yields would behave when nominal yields fell below 2% as they did in 2012…even though yields like that were entirely out-of-sample when we developed the model. I can’t describe the model in great detail because the method is proprietary and is used in some of our investment approaches. But here is a chart of the Enduring Investments real yield series, with the “classic” series in blue and the “Shanken/Kothari” series in red:

endreal

This series has a much more reasonable relationship to the interest rate cycle and to nominal interest rates specifically. Incidentally, when I sat down to write this article I hadn’t ever looked at our series calculated that far back before, and hadn’t noticed that it actually fits a sine curve very well. Here is the same series, with a sine wave overlaid. (The wave has a frequency of 38 years and an amplitude of 2.9% – I mention this for the cycle theorists.)

endrealsine

This briefly excited me, but I stress briefly. It’s interesting but merely coincidental. When we extend this back to 1871 (using Shiller data) there is still a cycle but the amplitude is different.

endreallong

So what is the implication of this chart? There is nothing predictive here; about all that we can (reasonably) say is what we already knew: real yields are not just low, but historically low. (Current 10-year TIPS yields are higher than our model expects them to be, but not by as much as they were earlier this  year thanks to a furious rally in breakevens.) Money is historically cheap – again, we knew this – in a way it hasn’t been since the War effort when nominal interest rates were fixed by the Fed even though wartime inflation caused expectations to rise. With real yields that low, how did the war effort get funded? Who in the world lent money at negative real interest rates like banks awash in cash do today?

That’s right…patriots.

1986-004-223Frankly, that makes a lot more sense than the reason we have low real interest rates today!

Categories: Good One, Investing, Theory, TIPS
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