Market Goes "Full Bitcoin"

Authored by Lance Roberts via RealInvestmentAdvice.com,

Market Review

What the “heck” was that?

This past week seemed to be the story of Christmas coming early. Earlier this week the markets surged higher on hopes that “Ole’ St. Tax Cuts” would soon be here. But that dream seemed to be short-lived on Friday, at least at the open, as General Mike Flynn seems to embody the “Grinch” trying to steal Christmas.

But at the end of it all, not much actually changed. Well, except for the fact that volatility not only made an appearance as stock prices swung wildly in both directions, but also in Treasury rates. As expectations of tax reform grew, rates spiked higher but then sank just as quickly as fears of turmoil in the Administration sent money into the safety of bonds.

As shown above, despite all of the “sound of fury” the S&P advanced 1.53% for the week while rates, not surprisingly as money rotated from “safety” to “risk,” ticked up from 2.3% to 2.4%. However, while volatility finished week only up mildly, intra-week we saw volatility jump to nearly 15 before settling back at 11.

The sharp advance, as the market went all “bitcoin,” pushed well into 3-standard deviation territory above the longer-term moving average with overbought conditions pushing extremes. While the backdrop remains decidedly bullish, the sharp moved higher has all the earmarks of an exhaustion move which suggests some profit-taking cool things off over the next couple of weeks. 

While the market is extremely overbought, the bullish trends remain intact. Furthermore, the month of December tends to bullish for equities which keeps portfolios allocated towards equity risk currently.

With the tax bill now out of the Senate, the real work begins as the House bill and Senate bill will go to conference to work out the rather substantial differences between the two bills. With neither bill even remotely approaching a “fiscally conservative” that will actually lead to stronger economic or reduced debts and deficits, it is a huge windfall for corporations.

This, of course, raises the question as to how much of the “tax cuts” are already priced into the markets.

One thing to be cautious of is the possibility this could well be a “buy the rumor, sell the news” event as we move into the New Year. As I stated last week, I see two potential outcomes:

1. A tax bill clears Congress reducing taxes which leads to tax-related selling by money manager to lock in gains at a lower tax rate that will not have to be paid until 2019, or;


2. The tax bill fails, a still likely scenario, which leads to tax-related selling by money manager to lock in gains on which taxes will not have to be paid until 2019, 

Let me repeat from the last newsletter:

“As I see how December plays out, I will be seriously looking at adding a short-hedge to portfolios before year end. I will keep you apprised.”

This weekend, I am traveling to Florida to give a presentation on the markets and will be joined by some of my friends like Chris Martenson and Nomi Prins. It promises to be fun and I will fill you in on any great insights next week.

The Bitcoin Ramp – Is It Sustainable?

by Michael Lebowitz, CFA

The explosive rise of Bitcoin (BTC) has taken the investing world by storm, and for good reason. Over the past six months alone BTC has quadrupled in value. Since 2012, it has risen over 200,000%. To put that into context, had one invested 10k in 2012 they would be worth over $20 million today. The graph below shows the meteoric rise.

There are predominantly two camps with strong opinions on what the future holds for BTC. One generally believes it to be the currency of the future while the second camp thinks BTC is another financial bubble. Given BTC’s increasing popularity we thought it would be helpful to present these two competing perspectives and then offer our own assessment.

Believers

Believers in BTC claim it is quickly becoming a widely accepted global currency. To better understand their view let’s see how BTC meets the definition of a currency, both as a means of transacting (money) as well as a store of value.

Money: money is anything that two parties can agree is acceptable in exchange for goods and services. For example, if I pay you a case of beer to mow my lawn, the beer, in this instance, is money. However, for “money” to be widely accepted, the masses must ascribe similar value to it.  While there is an increasing number of vendors accepting BTC, it is nearly impossible to use BTC to meet your everyday needs. Further, the value, or price of money, needs to be relatively stable to be effective. If a dollar bill bought you a case of beer today, but only a single bottle tomorrow and a keg the following week, few consumer or vendors would trust the dollar’s value. BTC’s value can fluctuate 5-10% on an hourly basis

Store of value: a store of value is something that allows one to save money and retain its value. When we save money we want comfort in knowing the money we earned can buy us the same amount of goods and services tomorrow that it can buy today. Again, the extreme volatility of the price of BTC makes it difficult to project how much purchasing power a BTC will buy you in the future. All currencies fluctuate but typically nowhere near the degree we are witnessing in BTC.

If the extreme price movements of BTC subside it is possible that BTC can serve as a widely accepted currency and the believers could be correct.

Deniers

A second camp believes BTC is a financial bubble. The chart below compares BTC to other recent investment fads.

You will notice in all instances above the bubbles rise steadily in price before transitioning to an exponential increase prior to collapse. Often, in the so-called euphoric phase, prices go well beyond the point most investors think is reasonable. In this respect, BTC is following the path of prior bubbles.

Bubbles are not solely defined by price movements, but more importantly by a lack of supporting fundamental value. If you subscribe to the value of BTC as does the first camp, the rapid increase in price may well be justified. If you believe there is no value, BTC is showing the classic pattern of most bubbles.

Our Take

We believe BTC can rise even further from current levels. That said, we question whether it has any meaningful fundamental value. In the textbook on sound investing, Security Analysis, Benjamin Graham, and David Dodd define investing as follows:

“An investment operation is one which, upon thorough analysis promises safety of principal and an adequate return. Operations not meeting these requirements are speculative.”

Based on this very clear definition of terms, there is no way to classify BTC as anything other than speculation. Furthermore, while we agree with those in camp one that BTC might one day be universally accepted as money and a reliable store of value, we have one major problem with which to contend.

To help you grasp our issue, consider that an investor who bought Bitcoin a few years ago and sold it today would have accumulated a remarkable gain. Even better, unlike a capital gain on stocks, bonds, real estate and all other financial assets, that profit is tax-free.

Now ask yourself, how long will the government allow investors to avoid paying taxes on gains in BTC? Further, will the U.S. government, or any other government, cede control of its currency and ultimately the economy? We expand on this concept below from a primer we wrote on cryptocurrencies- Salt, Wampum, Benjamins – Is Bitcoin next?

The preamble to the U.S. Constitution states the purpose of the Federal government is to:

“…form a more perfect union, establish justice, insure domestic tranquility, provide for the common defense, promote the general welfare, and secure the blessings of liberty to ourselves and our posterity.”

In other words, the government’s role is to protect the freedoms and liberties of its citizens. If the government has no ability to fund itself and is unable to provide defense and law enforcement it cannot uphold the Constitution. More precisely – the sovereignty of any nation, regardless of its form of government, rests upon the strength and integrity of its currency.

Summary

There may still be gains ahead for BTC, but the volatility of its price and still low adoption as a means of transacting pose obvious problems. The bigger risk, however, is given government incentives to impose taxes on the public and manage economic activity, the speculative value currently being ascribed to BTC does not seem durable and is therefore unlikely to survive.

Here’s What Works For Me

by Doug Kass

“And I said to myself, ‘This is the business we have chosen."” –Hyman Roth, “The Godfather” 

To me, stock price deception is seen with more frequency today than in any time in modern investment history.

Our markets, influenced by massive central bank liquidity and dominated by passive strategies (ETFs, risk parity, and volatility trending), not only are inhibiting price discovery but also are artificially influencing price action — “buyers live higher and sellers live lower” — to both the upside and downside.

In some measure, this is reducing the authenticity and validity of stock prices and charts and is hurting the value of technical analysis, which may be basing its decisions, in part, on artificial patterns/prices/data. On the other hand, it benefits those who view the market without emotion and who are willing to buy extreme weakness and sell extreme strength.

Yesterday underscored the reasons why and how I look at stocks. I would emphasize, again, that I do not have a concession on the process and I recognize that others have different approaches that provide good investment returns.

But I have a logic in my approach and Wednesday’s bifurcated action and its selective and often extreme volatility underscores some of these principles that I have adopted over the last four decades and provides some additional lessons:

* Avoid Volatile and Unpredictable Stocks — It’s Gambling: In the last two days, Riot Blockchain Inc. (RIOT) has had a range from about $12 to $25. There has been no news to account for that volatility and random action.Other collateral bitcoin plays such as Social Reality Inc. (SRAX) and Xunlei Ltd. (XNET) have had similarly large trading ranges. No specific company news there, either. Given my risk profile, I never will trade in these stocks. Others believe differently and believe they successfully can skate on this thin ice, but I will stick to my risk appetite, and I believe all but a few professionals may be kidding themselves in rationalizing these stocks “tradeability.” This also explains my reluctance to trade bitcoin, which had a trading range yesterday of $9,290 to $11,377 — again, on no news.

 

* No Matter What the Charts Say, I Prefer to View Every Trade/Investment Based on an Assessment of Reward vs. Risk — Seize Those Opportunities: The dynamic of an upside/downside calculation and determining discounts or premiums to intrinsic value form the basis for my trading and investment decisions. Recently, I successfully traded two retail stocks, Macy’s Inc. (M) and Dillard’s Inc. (DDS) , on this basis. Consider Twitter Inc. (TWTR) , which at $22 a share looked technically solid. Nevertheless, I sold off a large portion of my position between $22 and $22.50 recently based on an assessment of a less-favorable upside/downside ratio. Others bought based on an improving chart. Both I and they are likely comfortable with our decisions, but the purpose of this missive is to further explain my tenets and methodology.

 

* There Are Many Great Charts That Lie at the Bottom of the Sea: Though one or two days don’t make a market, the artificiality of the markets may be underscored by two stocks yesterday — Micron Technology Inc. (MU) and Square Inc. (SQ) . Both recently looked fantastic technically. Embraced by many a talking head in the business media, both have been schmeissed in recent sessions. Like the Nasdaq 100 ((QQQ) was down $3 yesterday), they all looked good on the charts until they didn’t, and all provided little indication to prepare traders for the reversals. At times like these, it is increasingly dangerous to buy stocks on breakouts. Buying calls on these stocks moves one further to the end of the risk curve. This strategy may work well for some time in a trending market, but a swift directional change can evaporate profits and eviscerate a portfolio. Again, such a strategy should be limited to professionals, and even that body of traders may suffer from a steady diet of options activity, as academic studies show.

 

* Do Not Underestimate the Impact of Price Momentum Strategies on Individual Stocks and Sectors: Over the last month, technology, especially of a FANG kind, has soared and other areas such as retail have collapsed. The possible artificiality of both moves was evident in the reversals this week and yesterday. Amazon.com Inc. (AMZN) , as an example, was down by more than $45 on no news yesterday. Retail stocks such as M and DDS rose by 10% on Wednesday and 20% in the last week, also on no news. This may underscore (1) the reduced value of analyzing stocks on price technically, and (2) that opportunities are provided for those who are emotionless and have a sense of intrinsic values and legitimate upside/downside calculations.

 

* A Diversified Portfolio Is a Preferable Course: Jim “El Capitan” Cramer detailed the value of this approach late yesterday in a well-thought-out column, “‘Am I Diversified?’ May Be Boring, but It Can Help Avoid the Pain.” Please reread it. As a matter of course, and as most are now aware, I keep my individual stock positions as a low percentage of my total overall portfolio and often have 40 to 50 portfolio names. I am always diversified in position size (typically at about 2% to 3% each) and in sector exposure (limited to 15% of the portfolio). Recognize that when a trader or investor is only buying “good” charts, that is not being diversified. Rather, it is part of a process that leads to a binary outcome that may end badly given the likely artificiality of prices.

Bottom Line

The artificiality of stock prices has accelerated in recent years with the domination of passive investment strategies.

I will not trade/invest in stocks solely on the basis that they “look good” on the charts in this sort of setting, which is dominated by influences that create an under-appreciated degree of price deception.

For these reasons and others I will not buy breakouts and sell breakdowns; this may be the wrong approach in the environment we are now in.

Rather, an approach to buying value and breakdowns and selling seemingly irrationally based prices and breakouts is my investment cup of tea based on the fundamental and dynamic assessment of intrinsic values relative to the current prices.

Others disagree and I respect their ability to navigate differently. I am not taking a shot at their approaches; rather, I am saying what serves me well and what may serve the majority of conservative risk-based investors and traders well.

This is how I am handling the markets these days, and, frankly, will forever.

And … buckle up.

Citi"s Shocking Admission: "There Is A Growing Fear Among Central Bankers They"ve Lost Control"

Earlier we showed a variation on a VIX chart from Citi"s Hans Lorenzen which, if it doesn"t impress, or scare you, then nothing probably will.

However, leaving readers unimpressed - and unscared - will not satisfy Lorenzen, which is why the credit strategist who works together with the godfather of rational doom, Matt King, and has been warning for weeks that now is the time to sell credit, unloads in one of the more effusive missives of dripping negativity to hit during this holiday week when one after another equity sellside analyst has been desperate to outgun each other with their ridiculous 2018 year end S&P forecasts.

And while Lorenzen touches on many things, at its core, his warning is straight out of Shumpeter: the longer nothing changes, the greater the crash will ultimately be, a topic which DB"s Aleksandar Kocic dissected over the summer, even defining an entirely new term in the process: metastability.

 

So without further ado, here is Lorenzen explaining why "embellishing the status quo will be the market’s undoing.

Ultimately, extreme valuations, the lack of risk premia, and a lack of responsiveness to tail risks are merely symptoms. The real question is what the skewed incentive structure resulting from that backstop has done to the fabric of markets after so many years. To our minds the answer is that trades and strategies which explicitly or implicitly rely on the low-vol environment continuing, are becoming more and more ubiquitous.

 

Realised historic vol is de facto an exogenous input to much of the risk management framework that underpins modern finance. With lookbacks extending a few years, an extended period of market stability reduces VaR measures and improves Sharpe ratios. Both allow / encourage investors to take more risk – driving valuations higher and vol lower still, creating a self-reinforcing dynamic. Intuitively, returns should follow flows – money is deployed and the asset price goes up. But in the real world the causation works the other way.

What this means in real-world terms:

Long periods of one-way markets breed survivor biases. The fund manager with lots of beta outperforms, the cautious fund manager underperforms. Either the latter gets on the bandwagon or soon enough outflows from the fund will ensue. Over time, fewer and fewer “critics of the regime” are left standing.

 

In an asset class where the upside is constrained, like in credit, that dynamic is further reinforced by the fact that a fund manager has to take more and more beta relative to benchmark in order to sustain the level of excess carry that will merely cover costs. The lack of volatility and the super high correlations between credits and the index (Figure 24), leave precious little scope for alpha (Figure 25).

Here we can add another piece to the short vol conundrum, because the closer spreads get to the lower bound, the more explicitly being long credit in itself becomes a short-vol position. With less and less upside remaining, owning credit risk become a question of generating a small amount of carry (or premium) for taking future downside risk – essentially, akin to selling a put option.

Meanwhile, as spreads collapse, as dol implied and realized vol, we are all “happily” ignoring that more risk is being issued into the market than ever before (Figure 26) and that the credit quality of the market keeps slipping – for the first time ever the market cap of the BBBs is about to overtake the rest of the € IG index (Figure 27).

What happens next should be familiar from the last financial crisis: the infamous step up in risk:

When the conventional asset class of choice no longer offers a “decent” return potential, money looks to the next one on the quality spectrum for a pickup. IG funds holding BBs and AT1. DM funds buying EM debt. European and Asian funds holding more and more $ fixed income. Corporates moving their liquidity from money markets to short-dated IG credit funds. Mandate creep in the investment criteria. Even synthetic structured credit is making something of a comeback. The list of tourist trades goes on and on. Most of these too are predicated on the status quo - if volatility and risk premia were to rise, retrenchment back towards the original / natural asset allocation would be swift and uncompromising.

And then, one day, the market will finally discount that the central banks are no longer set to injection trillions in liquidity: that"s the moment the public finally begins to admit the emperor is not wearing any clothes.

You could rightly argue that many of these factors are generic to every bull market. The fact that volatility clusters is exactly because of these (and other) selfreinforcing dynamics. But the implicit ceiling on vol / cap on downside from the central bank backstops has, in our view, allowed them to run for much, much longer than would have been possible in a market operating on its own devices.

 

You could argue that there is nothing to worry about as long as fundamentals remain strong. But those looking at the economic data, corporate earnings or leverage trends to indicate the next turn in markets are looking in the wrong place, if you ask us. Over the last 50 years, only 2 out of 19 corrections in US credit were led by a recession. 12 had no overlap with a  recession at all. In half the corrections, there wasn’t even a discernible turn in the leading economic indicator beforehand. Plainly, there is a long history of market corrections being triggered by other factors than fundamentals – Black Monday in 1987 and the correlation crisis in 2005 are two obvious examples.

Still, judging by the current state of the market, Citi writes that traders "evidently don’t expect a sharp market correction to happen tomorrow."

While the probability of a next-day loss still feels quite low there is an obvious temptation to stay invested a little bit longer for professional investors, tasked not with delivering a return of money, but a return on money and with high frequency. The process of judging that near-term probability manifests itself in the frenzied search for “triggers”. Surely, if one could just get a slightly better call on the next trigger, then it’d be possible to get out just in time before everyone else jams the exit? We don’t dismiss the importance of triggers. Indeed,  when you look back at the last fifty years, nearly every major correction in credit can be associated with a triggering event (Figure 28). With hindsight everything is easy.

Here Citi has some advice: don"t look for triggers; instead focus on the big picture.

We are sceptical that hunting for the next trigger is worth the effort. If a trigger seems obvious, then it’s probably obvious to everyone and chances are it will be too late. Triggers are often latent – the long-term problem is obvious, but it is ignored until suddenly it explodes without much warning (think the Greek sovereign debt crisis). Multiple factors often have to  combine to create a triggering event – the GFC wasn’t just about sub-prime, it was about excessive leverage, inadequate regulation, unchecked financial innovation, misaligned rating methodologies, inadequate backstops and a host of other things. The last couple of years have seen several widely peddled “triggering events” crystallise with remarkably little shake out.

So what about the big picture? Here one can argue that in recent years the market simply wasn’t vulnerable with so much central bank money behind it. However, Lorenzen believes that "2018 is different." As we see it, it is now increasingly vulnerable to a mid-cycle, “technical” correction, based on what we have discussed above:

• Central bank asset purchases are set to be the smallest in a decade (Figure 29). A $1tn of incremental demand versus 2017 is needed from private sources.


• At least in the US, the opportunity cost of not being invested in credit (i.e. the yield differential to 3m LIBOR) is likely to be the smallest since 2007.


• The perception of a backstop has facilitated a multitude of trades and strategies that are contingent on a low level of volatility in an increasingly crowded space. Now that backstop is moving “out the money”.


• Vol is near historic lows and has been so for longer than ever before. More risk than ever before is being issued into a credit market where spreads, on a like-forlike basis, are close to the 2007 tights and where breakevens are wafer thin.

Lorenzen then branches into some chaos theory for good measure:

In the context of a self-reinforcing, herding market, the pivot point where the marginal investor is indifferent between putting more money back into risk assets and holding cash instead is fluid. But when the herd suddenly changes direction, the result is a sharp non-linear shift in asset prices. That is a problem not only for us  trying to call the market, but also for central bankers trying to remove policy accommodation at the right pace without setting off a chain reaction – especially because the longer current market dynamics run, the more energy will eventually be released.

And while not intended to be a conclusion, or even a punchline, the next line from the Citi strategist should scare the living daylights out of anyone: it is a direct admission that central bankers have now lost control.

That seems to be a growing fear among a number of central bankers that we have spoken to recently. In our experience, they too are somewhat baffled by the lack of volatility and concerned about the lack of response to negative headlines.... Our guess is that sooner or later in the process of retrenchment they

will end up going too far – though that will only be obvious with

hindsight.

Frankly, that"s about the scariest admission from one of the world"s biggest banks that we have read in a long time.

* * *

As for how this period of cataclysmic metastability ends, here is Lorenzen"s dire conclusion:

In a fairy tale, turning points come suddenly and unexpectedly. Everything that has long been taken for granted is suddenly in pieces. In that sense markets are not all that different. People have gotten used to the paradigm that has been built up since the Great Financial Crisis. It has been tested on several occasions – 2011, 2012 and 2015 – and on each occasion central banks have overcome the challenge, thus ultimately reinforcing the regime.

 

The emperor in Andersen’s story was only able to parade around naked because the social norms, customs, conventions and vested interests that had built up over time were so strong that even the blatantly obvious was better left unspoken.

 

Similarly, the low risk premia, the low level of volatility, the lack of responsiveness to tail risk and spillover of systemic events, the reluctance to sell etc. to us are all indications that the market now has an almost Pavlovian response to central bank liquidity. The mere thought of it is enough to still leave us salivating, even when it is patently in the process of being turned off. Yes, excess liquidity will remain in the system even after central bank net asset purchases fall to zero, but as we have argued, if that money has chosen to stay out of the securities  market now, then why should it seamlessly come flowing in at these valuations when the backstop is moving out the money?

 

While our conviction in the exact timing and magnitude of the paradigm shift is admittedly low – hence the deliberately very wide range in the scenario forecasts – it is unwavering  when it comes to the broader point that central bank asset purchases will remain the key driver of markets. Exactly because trades and strategies have been built up around an assumption of the status quo, we fear that the inflection point, if / when it comes will be anything but smooth and linear. Indeed, the longer we remain in the current paradigm, the greater the chance that it  ends up being both sharp and painful.

 

One of our favourite quotes pertains as much to markets as it does to economics:

 

“In economics, things take longer to happen than you think they will, and then they  happen faster than you thought they could.”

    ? Rudiger Dornbusch

 

Surely, that is a sentiment which the emperor who had his vanity and pride shattered so abruptly from the least likely angle would recognise all too well?

We end with one of our favorite pictures: the one we call Yellen"s moment of epiphany haw it all ends.

No wonder the Fed chair can"t wait to get the hell out...

BofA"s Apocalyptic Forecast: Stocks Flash Crash, Bond Bubble Bursts In H1 2018, War May Follow

Having predicted back in July that the "most dangerous moment for markets will come in 3 or 4 months", i.e., now, BofA"s Michael Hartnett was - in retrospect - wrong (unless of course the S&P plunges in the next few days). However, having stuck to his underlying logic - which was as sound then as it is now - Hartnett has not given up on his "bad cop" forecast (not to be mistaken with the S&P target to be unveiled shortly by BofA"s equity team and which will probably be around 2,800), and in a note released overnight, the Chief Investment Strategist not only once again dares to time his market peak forecast, which he now thinks will take place in the first half of 2018, but goes so far as to predict that there will be a flash crash "a la 1987/1994/1998" in just a few months.

Contrasting his preview of 2018 with the almost concluded 2017, Hartnett sets the sour mood with his very first words, stating that he believes "2018 risk asset catalysts are much less bullish than in 2017" for the simple reason that the bearish positioning going into 2017 has been completely flipped: "positioning now long, not short; profit expectations high, not low; policy close to max stimulus; peak positioning, peak profits, peak policy stimulus means peak asset returns in 2018."  He also goes on to point out that the historical omens are poor:

• Bull market in S&P500 would become the longest ever on August 22, 2018 (and the second biggest ever at 2863 on S&P500).


• Equities have only outperformed bonds for seven consecutive years on three occasions in the past 220 years (the last time was 1928 - Chart 1).

Having read Hartnett for many years, we can sense an almost tangible undertone of anger and frustration at central banks for making his bearish forecasts for 2 years in a row go up in a puff of smoke. Which probably explains why one of BofA"s best strategists has decided to double down, and raise the stakes beyond a simple market crash, and to a flash crash, if only for dramatic impact.

But before we get there, here is Hartnett"s explanation why the market will peak in the first half of 2018:

The Big H1 Top

We forecast a H1 top in risk assets as the last vestiges of QE, the passage of US tax reform and robust early year EPS revisions incite full investor capitulation into risk assets. Potential targets are SPX 2863, CCMP 8000, with US government bond yields moving >2.75%.

 

We start 2018 with a pro-risk asset allocation of equities>bonds, EAFE>US, gold>oil, bullish US dollar.

 

We believe the air in risk assets is getting thinner and thinner, but the Big Top in price is still ahead of us. We will downgrade risk aggressively once we see excess positioning, profits and policy.

 

Peak positioning would be signaled by…

• BofAML Bull & Bear Indicator exceeds “sell signal” of 8 (Chart 2);


• Active mutual equity funds start to see inflows;


• BofAML GWIM equity allocation exceeds 63%, an all-time high (currently 61%).

How to know if/when peak profits arrived?

US ISM dips below 55: needs to end 2018 >55 to beat consensus global EPS estimate of 10.5% (Chart 3); Inverted yield curve, which in seven out of seven occasions in the last 50 years has been the prelude to recession.

 

 

More to the point, how to know that peak central bank policy has arrived?

• Q2 peak in G4 central bank liquidity of $15.3tn: net central bank buying of financial assets drops from $1.5tn in 2016 and $2.0tn in 2017 to nearly zero in 2018;


• US tax reform passed, after which investors must discount tighter, not earlier economic policies.

Which brings us to Bank of America"s "big long" trade: volatility, and the stark prediction that in just a few months, a 1987-type flash crash which will wipe out trillions in market cap, is imminent.

The Big Long: volatility

 

Second, we believe that peak positioning, profits, and policy in 2018 will engender peak asset price returns and trough volatility. In 2017, stock market volatility fell to 50-year lows, bond volatility fell to 30-year lows, ETFs accounted for 70% of daily average global equity volume, the AUM of quant hedge funds is now $432bn (up $271bn since 2009).

 

A flash crash (à la ’87/’94/’98) in H1 2018 seems quite likely, in our view, as the major sedative of volatility, the central banks, start to withdraw liquidity.

According to Hartnett, the right way to to trade the upcoming flash cash and the "Big Long is throguh a combination of  long 2yr/short 10yr Treasuries, long TIPS steepener vs flattener in OATei, long SPX put ratio calendar, long Russian equities.

As an added "bonus", in addition to a "big long", the BofA strategist also has a "big short" trade, which perhaps not surprisingly, is in credit.

The Big Short: credit

 

Third, we believe that higher inflation, higher corporate debt levels, higher bond volatility and the end of the QE era will be most damaging for corporate bonds.

 

The big 3 consensus assumptions are: Goldilocks, no Fear of Fed/ECB, and no Mean Reversion. The game-changer is wage inflation, which on our forecasts is likely to become more visible. Wage inflation would shatter consensus via higher credit spreads. 3½% US wage growth, 2½% US CPI, and 2% Eurozone CPI are all inflation levels likely to increase volatility and credit spreads.

For those looking to trade in advance of the bursting of the credit bubble, BofA"s advice: go long CDX HY & iTraxx XOVER.

* * *

Finally, if that wasn"t bad enough, in addition to the combined bursting of the short-vol and long credit bubbles, BofA has one final prophecy: "the biggest risk of all is that the structural “Deflationary D’s” (excess Debt, aging Demographics, tech Disruption) cause wage inflation to again surprise to the downside." Here"s why:

The Big Risk: tech bubble

 

Finally, we believe the biggest risk of all is that the structural “Deflationary D’s” (excess Debt, aging Demographics, tech Disruption) cause wage inflation to again surprise to the downside. The era of excess liquidity, bond yields fall, and the Nasdaq goes exponential. 2018 calls for the big top, big volatility long, big credit short, all once again prove to be way too early. An “Icarus unleashed” bubble nonetheless could end in 2019 with a bear market on hostile Fed hiking, Occupy Silicon Valley and War on Inequality politics.

Translation: the Fed - having created the record wealth, income and class divide that resulted in Brexit, Trump and a wave of nationalism across Europe - is unable to stop, and unleashes civil, and perhaps world war as its final act.

How to hedge against "the biggest risk of all"? Hartnett has two words of advice: buy gold.

"How To Forecast Markets": A Departing Top JPMorgan Strategist Reveals What He Learned After 30 Years

One of the most popular JPMorgan analysts, traders and commentators, Jan Loeys, head of global asset strategy and author of the weekly "The JPMorgan View" piece is moving on (to a different, non-client facing part of the company), and is using his last weekly address to JPM clients to recap the main lessons he has learned over his 30 year career.

For those carbon-based traders who still trade on the basis of fundamental analysis, inductive reasoning, and discounting, and forecasting the future - instead of merely relying on the fastest laser-based algos to react to the news or hoping for central bank bailouts - we have excerpted the entire piece, and are excited to note that while Loeys may be leaving, he will be replaced by two of our favorite JPM analysts and commentators, Nikos Panigirtzoglou and Marko Kolanovic, who under John Normand will take over as JPM"s new Cross-Asset Strategy team.

So, without further ado, here is the latest, and last, from JPM"s Jan Loeys, explaining "What have I learned?" after 30 years of doing this...

What have I learned?

How to forecast markets?

• The theory and empirical literature of Finance are the best starting point as they deal directly with asset prices. Next are macro economics and statistics. Markets are not Math or Engineering, but a forever learning and adapting system with all of us observing and participating from the inside. Quantitative techniques are indispensable, though, to deal with the complexity of financial instruments and the overload of information we face. Empirical evidence counts for more than theory, but you need theory to constrain empirical searchers and avoid spurious correlations.


• The starting point of Finance is the Theorem of Market Efficiency which posits that under ideal conditions what we all know should be in the price. Only new information moves the price. Hence, it is changes in expectations about the future that drive asset prices, not the level of anything.


• How to forecasts view changes? The good news is that changes in opinions about fundamentals such as growth and inflation tend to repeat. This is one driver of momentum in asset prices, and is likely driven by the positive feedback between risk markets and the economy that forecasters naturally find very difficult getting ahead of.


• I live by Occam’s Razor: If you can explain the world with one variable, don’t use two. This keep-it-simple rule does not deny that reality is complex, nor does it say anything about simple minds. It forces one to focus on the most important fundamental drivers of markets and to cut out the clutter. It reduces the risk of becoming a two-handed strategist.


• The mode and the mean. There is a fundamental difference between an asset price and a forecast. A forecast is a single outcome that you consider the most likely, among many. In statistics, we call this the mode. An asset price, in contrast, is closer to the probability-weighted mean of the different scenarios you consider possible in the future. When our own probability distribution for these different outcomes is not evenly balanced but instead skewed to, say, the upside, the market price will be above our modal view. Asset prices can thus move without a change in modal views if the market perceives a change in the risk distribution. An investor should thus monitor changing risk perceptions as much as changing modal views.

• Do markets get ahead of reality? They do, yes, exactly because asset prices are probability-weighted means and the reality we perceive is coded as a modal view. Information arrives constantly and almost always only gently moves the risk distribution around a given modal view. Before we change our modal view of reality, the market will have seen the change in risk distribution and will have started moving already.


• Are some markets faster than others? I hear frequently in one market, say equities, that they are monitoring other markets, such as credit or bonds, for early signs on what stocks will do. But I hear the reverse frequently in the bond world. I do not like either view and just assume that all markets react at the same speed as they see all information at the same time.


• Levels or direction? In our business, we are asked to forecast asset prices and returns. I have found this very hard but fortunately have had the luxury to be able to stick to forecasting market direction rather than outright asset price levels. In markets that are close to efficiently priced, what we know is already in the price and we cannot really use that same information to make a coherent case for an asset price level that much different from today. All I have been able to do is to make a case that there are mild-to-decent odds in favor of the market going in one direction rather than the other. We have been much more successful in forecasting direction than actual asset price levels, and it is the direction that is more important for strategy.


• Top down or bottom up? In assessing the outlook for a market or an economy, should you start judging individual countries, sectors, and companies and then add them up to the overall market, or should you start from the top down? As a macro strategist, I naturally think top down, arguing I sit on top of a tall building, seeing where all the traffic and capital is going. But I know that from that high up, I do not see any potholes. For that, I have been relying on my local analysts to tell what conditions prevail on their street. And they in turn ask me what I can see from high up. I have found that it is the dialogue between bottom-up and top-down thinking that is most fruitful. Our economists do this quite well: they start the global forecast from the country level up, but then look at a host of global signals to put pressure on the bottom-up forecasts.


• The US as the indispensable market. Applying this top-down thinking, should we therefore start strategy at the global level and then drill down to regions and sectors, or should we follow the more common approach of starting with the USD market and economy, and then analyze the rest of the world as a spread market? I have done the latter. This is not only because we have the longest return series in the US and the US market and economy have been more stationary than others, but also because dollar assets are half of the investable world as many non-US entities both fund and invest in dollars.


• Rules versus discretion? You need both. I have tried to have logical arguments to buy or sell certain assets, based on Finance. And I have tried to corral evidence that the signals I use have in the past had the assumed impact on asset prices. Each of these then became a rule, of the form: If X>0, buy A, and vice versa. As we collected these rules, and published them in our Investment Strategies series, the question came up naturally whether we should not simply make our investment process driven by a number of empirically proven rules, and to banish any discretion (emotion?) from the process. Over time, we converged on a mixture of the two as pure rules ran into the problem that the world is forever changing, partly as every one else figures out the same rule and then arbitrages away the profit, and partly as economic structures and regimes similarly change over time in a way that we cannot capture with simple rules.


• Much as I have been talking a lot about cycles, I do not think of the world as a stationary system described by a set of parameters that we steadily get to know more about. Instead, as economists we think of people constantly optimizing their objectives, under the constraints they face. Aside from truly exogenous shocks to the system, the main difference between today and yesterday is that today, we know what happened yesterday and that information allows us to constantly fine tune and thus change our behavior. That is, we constantly learn from the past, much to try to avoid making the same mistakes. At the macro level, this means that the system is constantly evolving. As Mark Twain said, “History doesn’t repeat itself, but it often rhymes”. As investors, we should look at the market as billons of people all learning and adapting. The best investors are those who get ahead of this by learning faster and understanding better how others are learning.


• Expectations are adaptive. Markets should be purely forward looking into the future and treat the past as just that, the past. The problem we have is that the only information we receive is from the past. Ages ago, a debate raged in economics on whether expectations for say inflation are rational, or adaptive. The term rational was meant to denote that investors plug in all the info they have into their model of what will drive the future and derive from that the most efficient forecast. That is, investors do not slavishly extrapolate the past. True in principle. But we also find that as new information arrives, all of it past, investors constantly update these rational priors as new data steadily challenge them. In effect, then, market expectations for future fundamentals on earnings, inflation, defaults and such come close to adaptive, moving averages of past performance.


• Risk premia are about risk and uncertainty. This sounds obvious, but is frequently overlooked. It means that even when nothing surprising is happening, that by itself is surprising against markets that are priced for a certain volume of surprises. When nothing happens and data come out as expected, the market updates in an adaptive sense its uncertainty, and risk premia come down.


• Flows, positions, and supply and demand. Economics teaches us that supply and demand determines price. That is true also for asset prices, and explains the high interest in information on flows. Applying this dictum is not easy, though, as we cannot measure future intended supply and demand, aside from governments’ budget plans. All we measure ex post is transactions at a price that then equated supply with demand. For every seller in the past, there was a buyer, with the price moving to create this equilibrium. Only the movement in prices can tell us whether intended demand exceeded or fell short of supply. Given that we know how prices changed, flow data do not tell us much more.


• I have a different gripe about position surveys. If you tell me that you are long or OW asset class X, then I must conclude investors are long and advise you to sell. You know that, and thus should not tell me that you are long. I thus do not “trust” survey data.


• This is not to say that flow and position data are useless. We instead find that more detailed understanding of how different types of investors, each with their own restrictions and objectives, interact with the plumbing of the system, has allowed us to make better investment decisions. It led us to start 10 years ago a dedicated Flows & Liquidity weekly managed by my colleague Nikos Panigirtzoglou that is one of our top three publications by readership.


• Central banks and QE do not “cause” asset price inflation. It is often argued, and our own language has come dangerously close to it, that easy money by central banks has massively and artificially inflated asset prices and that a QE unwind will thus deflate them. I do not like to think in those terms. Easy money may be the proximate cause of high asset prices, but is not the ultimate one. All central bankers try to do is to search for the non-inflationary equilibrium level of rates driven by the supply and demand for capital as well as inflation expectations. In this cycle, higher global savings from EM and corporates, depressed capital spending, consumer delevering and public sector austerity have created a surplus of savings over investment that is the real cause of low interest rates and high asset prices. If central money was too easy, we would have also seen much faster growth and higher inflation, which we did not get.


• Market volatility is not a mystery but should be thought of as fundamental volatility, of growth, earnings, inflation, plus technical forces which are largely due to leverage, positions, market plumbing and such. Another way of looking at vol is as a function of the number of shocks and surprises hitting the system, the propagation and contagion forces around them (mostly leverage) and the shock absorbers that counteract them (largely central banks).

Where is alpha?

• The Theorem of Market efficiency, which implies investors can’t beat the market, implies that asset prices will follow random walks, with drift and that asset price changes will be white noise, with no serial correlation. There are thus only two possible inefficiencies to be exploited: positive serial correlation, which we call Momentum, or negative serial correlation, which we call mean reversion, or Value (to become valuable, asset prices need first to go down, or fundamentals need to improve faster than the price). It is an empirical question which dominates where. At the asset class and sector level, we have found that Momentum dominates, while within the fixed income world, Value is more important.


• The Theorem of Market efficiency assumes frictionless markets. Hence, cross-sectionally, we need to focus on areas where there are frictions due to different regulations, business practices, or investment objectives. Most profitable for me have been differences between currencies and industry segmentation between HG and HY, EM and DM, and bonds and equities.


• Across time, market momentum at the macro level has been the best way to earn excess returns. I discussed above how some of this is due to the momentum in view changes. More fundamentally, in open markets, we frequently face a Fallacy of Composition according to which rational and equilibrating behavior at the micro level becomes destabilizing at the macro level. The free market is very good at motivating entrepreneurship and rational behavior at the micro level, but is subject to constant booms and busts at the macro level. Central banks try to control this instability through counter-cyclical policies but can’t undo it all.


• Trade the risk bias. Even when markets price in exactly our modal views, I find it useful to consider how prices will move on new information and then try to position on any skew in the outlook. If I find that a particular price or spread will move a lot more on bullish than on bearish news, then I will position bullishly. This works at the portfolio level if I can combine different unrelated risk biases.


• Is there now so much information that everyone sees at the same time that alpha is dead? To some extent, yes, as reflected by the inability of the hedge fund world to offer better returns than a simple bond and equity portfolio with the same volatility over the past 10 years. Still, while alpha is weaker, I don’t think it is truly dead, as allocation across asset classes is still working well, even as it seems harder to earn alpha within asset classes.


• Is passive investing destroying alpha? No. it should actually make it easier if a lot more investors choose to allocate passively and therefore leave opportunities to the reduced number of active managers. I do feel the move to passive is largely within asset classes (i.e., stock picking) and that the arrival of liquidity passive products (ETFs) has made active asset allocation a lot easier. I think many managers have moved from active stock picking to active asset allocation.


• How to analyze risk? Risk is not the same as past vol, but the surprise that will hurt your portfolio. I have never found it useful to make long list of all the things that can go wrong over the next year. Instead, I start from the premise that the big risks that will have an impact at the macro level almost always start as small ones. I have called these local brush fires, of which there are always a bunch and of which I need to decide which will become a wildfire. This does not solve the problem fully but at least reduces the number of risks to monitor.


• Geopolitics? I have generally ignored these risks, primarily as I do not have a model to understand or project them. When they do become market relevant, they typically hit us so fast that is too late to do much about them.

How to put it together?

• I like a Lego approach to TAA of one trade at the time. In theory, an active money manager should translate their ideas into expected returns and risks and then use portfolio optimization to calculate an efficient frontier of the highest return portfolios by levels of risk.


• I started that way decades ago as a young strategist and ran into numerous problems of how to assess all the necessary return, volatility and correlation parameters over multiple horizons. I found that the more assumptions you have to make, the greater the probability of putting in numbers for which you have no idea. The well-known Black-Litterman approach tries to deal with this from a Bayesian point of view, starting with the parameters implied by market outstandings, but I had problems with why these parameters would make sense, and how to dynamically change portfolios on constantly incoming new information and ideas.


• I then moved to greatly simplify my process of converting views into portfolios in two ways. First was to postulate that any active portfolio is a passive benchmark portfolio plus a number of zero sum deviations of under- and overweights against that benchmark that I think about as indifferent to what benchmark is used. That allowed me to separate the active overlay portfolio from the underlying benchmark and give each global investor the same OW/UW advice, irrespective of their benchmark.


• The second simplification was to think of each single active view as a single trade that needs to stand on its own, with its own drivers and logic. If the latter turn, I exit the trade, without changing the other trades.


• Does that mean I ignore correlations? Yes and no. When building a portfolio of active trades, I start with a target overall active risk (e.g., 1% VaR). The lower the correlations between my different trades, the higher the VaR I can allocate to each individual trade. But as we actively turn off trades and add new ones, I will not constantly move the whole portfolio around.


• This is partly as I find correlations unstable and hard to forecast. The past correlation between two assets or positions depends on what was driving them. Bonds rallying because of monetary easing will be bullish for stocks and the equity bonds correlation will be positive. Bonds gaining because of low inflation on weak growth will correlate negative with equities. I am very wary of extrapolating past correlations and will generally not base recommendations on them.


• Sizing risk by track record and hot hands. It is not only important to have the right trade on but also to make sure to have the right amount of risk allocated to each. I start with a target amount of tactical risk which I think about in Value of risk, in dollar terms or percent of AUM. I then decide whether today is a good time to take a lot of risk, or a bad time. If we are been on a roll making money, then we probably have a better sense of the direction of markets and I then take more than average risk.


• Next comes deciding where to take this risk. I look here at track records, both long term and more recent. I have found over the past 30 years that certain areas are “easier” to make money than others. They are broad asset allocation (risk on, risk off), cross country in bonds and FX, and credit spreads. The harder ones are bond duration, and country and sector selection in equities. I aim to make sure I generally take more risk in the easier areas.


• Finally, I check where we have been doing better more recently. At times, we have a cold hand in certain areas, and I then reduce their risk budget until performance picks up, and vice versa. In effect, I assume momentum in success.


• The conflict between consistency and diversification. Given how efficient markets generally are and that I do not really have superior information, I try not to get too cocky about my ability to beat the market. I assume my success rate for any individual position will be only just over 50/50. How then to get a portfolio with a success rate that is well above 50/50? The trick is to choose positions and OWs/UWs that are not correlated to each other. That is easier said than done because our mind naturally veers to creating consistency.


• I have found only one way to create diversification in trades, which is to make them go through different brains and ways of thinking. As a research strategy CIO, I had to make sure I do not dictate all trades, as they would otherwise become highly correlated. Instead, it is important to allocate trading decisions (on paper in our case) to different individuals and ways of thinking.


• How long to hold on? I find it nearly impossible to hit the exact top to take profit on a winning trade and thus had to make a choice between exiting while still going up, or only after it is already going down. Most of the time I find myself selling on the way down, and have rationalized this by the observation that we are generally underestimate how far a market can go when we have the direction right.


• What is the right investment horizon for active positions? It is almost a truism that successful trades end up becoming longer lived than expected, while bad ones becomes shorter-lived. Beyond that, I find that asset classes with positive feedback with fundamentals, like equities and credit, have much higher longevity (quarter to years) than markets with negative feedback, such as bonds and currencies (weeks, maybe months). This is why our bond floor always feels so short-termist versus our equity floor. It took me a long time to recognize that this makes sense.


• How frequently to adjust your portfolio? In theory, every time new information arrives or asset prices move. This is not practical. I have been doing it monthly, but the beauty of our Lego approach and the usage of different brains in our paper portfolio with each managing a different trade is that we are effectively changing small parts here and there of the portfolio virtually on a weekly, if not daily basis.

Final thoughts

• Cherish your errors. I have learned ten times more from being wrong than being right. Once you make a mistake, go public with it, analyze it in detail, and learn from it.


• Be your own devil’s advocate, and spend most time with people who do not agree with you, or who have a different way of looking at things. Not always easy as being with like-minded people is more comforting.


• Regrets? None really. I have been extremely fortunate having come to JPMorgan at the right time, the right place, with the right mentors and the right great colleagues to learn every day from the right clients. And the journey, and the lessons are not over. Thank you so much! You made my 30 years, and counting.

"The Leaders Are Crashing" - It"s Not Just Junk Bonds That Have Given Up

We have been warning about significant divergences between equity prices and other asset classes for a few weeks (most notably the decoupling from equity risk and credit risk, junk bonds), but as BofA notes its not just these assets that are breaking away from soaring Nasdaq levels, in fact many of the rally"s leaders are crashing... in a way we have not seen recently.

High yield risk has suddenly decoupled from equity markets...

And Jeffrey Gundlach has been warning something"s got to give. Based on the past two days, looks like we have our answer.

Stocks fell around the world a second day and high-yield bonds headed for a fourth straight loss, resuming a historic correlation that the hedge fund manager on Wednesday had warned was alarmingly out of whack.

“JNK ETF down six days in a row, closing near its seven month low,” the DoubleLine Capital LP co-founder wrote on Twitter Wednesday. “SPX up five of last six days, closing at an all time high. Which is right?”

In fact the correlation between these two leaders has crashed...

In the past decade, there were only three other instances where the relationship between JNK and mega-cap tech broke down to this degree. Each time, the two assets began to resume their positive correlation within four to 12 days, data compiled by Bloomberg show.

But given the last few days in equities and credit... High Yield Bond prices (HYG) are at 8 month lows...

On record dollar volumes of trading...

Gundlach is calling a win...

“A material pullback would be something we need to watch for, as a deteriorating credit market has led each of the largest equity pullbacks since 2014,” said Frank Cappelleri, a senior equity trader and market technician at Instinet LLC.

 

“With divergences once again apparent now, the bulls face their latest test.”

It"s not just credit risk, but equity risk has decoupled from equity prices too...

VIX has started to creep higher but has further to go to fit with credit risk...

But it"s not just high yield bonds, price leadership has been stung in recent days: Oct 26th/27th ECB announced "tapering", Brent broke $60/b…concerns of "peak policy" stimulus & "peak profits"caused toppling of credit, bank, tech "leadership"; sell-off sequence past few weeks = 1st EMD, 2nd HYG, 3rd SX7E, 4th BKX, and #5 SOX...

As BofA"s Michael Hartnett notes, watch EMD & HYG in particular...needs to stabilize... but the recent pullback also follows insane gains...

FAANG+BAT market cap up $1.5tn YTD, a sum larger than entire market cap of DAX ($1.4tn); and Aug saw all-time low yields in US HY tech bonds (4.3% H0TY) & EU HY corp bond yields hit low in Oct (2.1% HE00, i.e. lower than yield on US Treasuries).

Finally, in case you think this is all much ado about nothing. The last time we saw such a divergence between credit and equities was in Aug 2015...

Just two weeks before the huge ETF  flash crash.

Mauldin: The Next Crisis Will Reveal How Little Liquidity There Is

Authored by John Mauldin via MauldinEconomics.com,

This is something I’ve been pondering for some time. I think the next crisis will reveal how little liquidity there is in the credit markets, especially in the high-yield, lower-rated space.

Dodd–Frank has greatly limited the ability of banks to provide market-making opportunities and credit markets, a function that has been in their wheelhouse for well over a century.

However, when the prices of massive amounts of high-yield bonds that have been stuffed into mutual funds and ETFs begin to fall, and the ETFs want to sell the underlying assets to generate liquidity, there will be no buyers except at extreme prices.

My friend Steve Blumenthal says we are coming up on one of the greatest buying opportunities in high-yield credit that he has ever seen. And he has 25 years of experience as a high-yield trader.

There have been three times when you had to shut your eyes, hold your breath, and buy because the high-yield prices had fallen to such extreme levels. That is going to happen again.

But it is going to unleash a great deal of volatility in every other market. As the saying goes, when you need money in a crisis, you sell what you can, not what you want to. And if you can’t sell your high-yield, you end up selling other assets (like equities), which puts strain on them.

But that is not just my view. Dr. Marko Kolanovic, a J.P. Morgan global quantitative and derivative strategy analyst, has written a short essay called “What Will the Next Crisis Look Like?” and it’s this week’s Outside the Box (subscribe to this free weekly publication here). He sees additional sources of weakness coming from other areas, too.

Frankly, the lack of volatility is beginning to scare me a bit. Minsky constantly reminded us that stability begets instability. Stability is a pretty good word to describe the current markets.

But such stability always ends in a "Minsky moment." We don’t know when; we don’t know where it starts; but we know it’s coming.

What Will the Next Crisis Look Like?

By Marko Kolanovic, PhD, and Bram Kaplan
October 3, 2017

Next year marks the 10^th anniversary of the Great Financial Crisis (GFC) of 2008 and also the 50^thanniversary of the 1968 global protests against political elites. Currently, there are financial and social parallels to both of these events.

Leading into the 2008 GFC, some financial institutions underwrote products with excessive leverage in real estate investments. The collapse of liquidity in these products impaired balance sheets, and governments backstopped the crisis. Soon enough governments themselves were propped by extraordinary monetary stimulus from central banks. Central banks purchased ~$15T of financial assets, mostly government obligations. This accommodation is now expected to reverse, starting meaningfully in 2018. Such outflows (or lack of new inflows) could lead to asset declines and liquidity disruptions, and potentially cause a financial crisis. We will call this hypothetical crisis the “Great Liquidity Crisis” (GLC). The timing will largely be determined by the pace of central bank normalization, business cycle dynamics and various idiosyncratic events, and hence cannot be known accurately. This is similar to the 2008 GFC, when those that accurately predicted the nature of the GFC started doing so around 2006. We think the main attribute of the next crisis will be severe liquidity disruptions resulting from market developments since the last crisis:

• Decreased AUM of strategies that buy Value Assets: The shift from active to passive assets, and specifically the decline of active value investors, reduces the ability of the market to prevent and recover from large drawdowns. The ~$2T rotation from active and value to passive and momentum strategies since the last crisis eliminated a large pool of assets that would be standing ready to buy cheap public securities and backstop a market disruption.

• Tail Risk of Private Assets: Outflows from active value investors may be related to an increase in Private Assets (Private Equity, Real Estate and Illiquid Credit holdings). Over the past two decades, pension fund allocations to public equity decreased by ~10%, and holdings of Private Assets increased by ~20%. Similar to public value assets, private assets draw performance from valuation discounts and liquidity risk premia. Private assets reduce day-to-day volatility of a portfolio, but add liquidity-driven tail risk. Unlike the market for public value assets, liquidity in private assets may be disrupted for much longer during a crisis.

• Increased AUM of strategies that sell on ‘Autopilot’: Over the past decade there was strong growth in Passive and Systematic strategies that rely on momentum and asset volatility to determine the level of risk taking (e.g., volatility targeting, risk parity, trend following, option hedging, etc.). A market shock would prompt these strategies to programmatically sell into weakness. For example, we estimate that futures-based strategies grew by ~$1T over the past decade, and options-based hedging strategies increased their potential selling impact from ~3 days of average futures volume to ~7 days of average volume.

• Trends in liquidity provision: The model of liquidity provision changed in a close analogy to the shift from active/value to passive/momentum. In market making, this has been a shift from human market makers that are slower and often rely on valuations (reversion), to programmatic liquidity that is faster and relies on volatility-based VAR to quickly adjust the amount of risk taking (liquidity provision). This trend strengthens momentum and reduces day-to-day volatility, but increases the risk of disruptions such as the ones we saw on a smaller scale in May 2010, October 2014 and August 2015.

• Miscalculation of portfolio risk: Over the past 2 decades, most risk models were (correctly) counting on bonds to offset equity risk. At the turning point of monetary accommodation, this assumption will most likely fail. This increases tail risk for multi-asset portfolios. An analogy is with the 2008 failure of endowment models that assumed Emerging Markets, Commodities, Real Estate, and other asset classes are not highly correlated to DM Equities. In the next crisis, Bonds likely will not be able to offset equity losses (due to low rates and already large CB balance sheets). Another risk miscalculation is related to the use of volatility as the only measure of portfolio risk. Very expensive assets often have very low volatility, and despite downside risk are deemed perfectly safe by these models.

• Valuation Excesses: Given the extended period of monetary accommodation, most of assets are at their high end of historical valuations. This is particularly true in sectors most directly comparable to bonds (e.g., credit, low volatility stocks), as well as technology- and internet-related stocks. Sign of excesses include multi-billion dollar valuations for smartphone apps or for ‘initial crypto- coin offerings’ that in many cases have very questionable value.

We believe that the next financial crisis (GLC) will involve many of the features above, and addressing them on a portfolio level may mitigate the impact of next financial crises. What will governments and central banks do in the scenario of a great liquidity crisis? If the standard rate cutting and bond purchases don’t suffice, central banks may more explicitly target asset prices (e.g., equities). This may be controversial in light of the potential impact of central bank actions in driving inequality between asset owners and labor (e.g., see here). Other ‘out of the box’ solutions could include a negative income tax (one can call this ‘QE for labor’), progressive corporate tax, universal income and others. To address growing pressure on labor from AI, new taxes or settlements may be levied on Technology companies (for instance, they may be required to pick up the social tab for labor destruction brought by artificial intelligence, in an analogy to industrial companies addressing environmental impacts). While we think unlikely, a tail risk could be a backlash against central banks that prompts significant changes in the monetary system. In many possible outcomes, inflation is likely to pick up.

The next crisis is also likely to result in social tensions similar to those witnessed 50 years ago in 1968. In 1968, TV and investigative journalism provided a generation of baby boomers access to unfiltered information on social developments such as Vietnam and other proxy wars, Civil rights movements, income inequality, etc. Similar to 1968, the internet today (social media, leaked documents, etc.) provides millennials with unrestricted access to information on a surprisingly similar range of issues. In addition to information, the internet provides a platform for various social groups to become more self-aware, united and organized. Groups span various social dimensions based on differences in income/wealth, race, generation, political party affiliations, and independent stripes ranging from alt-left to alt-right movements. In fact, many recent developments such as the US presidential election, Brexit, independence movements in Europe, etc., already illustrate social tensions that are likely to be amplified in the next financial crisis. How did markets evolve in the aftermath of 1968? Monetary systems were completely revamped (Bretton Woods), inflation rapidly increased, and equities produced zero returns for a decade. The decade ended with a famously wrong Businessweek article ‘the death of equities’ in 1979.

*  *  *

Every week, celebrated economic commentator John Mauldin highlights a well-researched, controversial essay from a fellow economic expert. Whether you find them inspiring, upsetting, or outrageous… they’ll all make you think Outside the Box. Get the newsletter free in your inbox every Wednesday.

WTI Spikes Over $57 For The First Time Since July 2015

Having legged higher at the opens of Asia, Europe, and US markets, WTI is extending gains overnight on middle-east tensions...

Brent is trading above $62 amid anti-corruption drive led by Saudi Crown Prince Mohammed bin Salman, which may consolidate his control in OPEC’s largest oil producer, and WTI has pushed above $57 as producers such as Nigeria, Saudi Arabia signal they support a potential extension of OPEC output cuts.

“We have political uncertainty, risk of political instability in this major oil producing country and also unforeseen implications for the entire region,” Commerzbank analyst Carsten Fritsch says by phone.

 

“It justifies a certain risk premium in the oil price...

 

At the moment you’d have to be brave to bet against Brent."

And everyone and their pet rabbit is record long the energy complex.

USDJPY Inches Higher As Japanese Stocks Set For Longest Winning Streak In History

Yen is weaker and Japanese equity futures notably higher following a landslide election victory for Japan Prime Minister Shinzo Abe which theoretically ushers in yet more easy monetary policy. USDJPY has jumped above 114.00 in early trading, sending NKY futures up almost 1% in the pre-market.

If this equity rise holds it will mark the 15th consecutive gain for the Japanese market - breaking the 1961 record of 14 straight days to become the longest winning streak in Japanese stock market history.

Nikkei 225 is at its highest since Dec 1996.

Meanwhile, much has been made recently of the decoupling between USDJPY and the Nikkei 225

However, this chart masks a closer relationship between USDJPY and the relative performance of Japanese and US equities.

So there really is no regime shift.

What are the drivers of this persistent negative correlation between the yen and Japanese equities and which flows supported this negative correlation this year?

On Friday, JPMorgan presented three fundamental explanations to justify the link between Japanese equities and the yen.

One typical explanation is that the yen, being a major funding currency for the world, should rise in a risk-off equity environment and vice versa. But this argument is not supported by the fact that there is much lower correlation between the yen and global equities. It is also not supported by the structural break in the correlation between Japanese equities and the yen shown in the chart above. The yen was the most prominent or sole funding currency before the financial crisisof 2007/08. After the financial crisis the yen was joined by the dollar and later by the euro as funding currencies. So if anything the negative correlation between equities and the yen should have been even more negative before the financial crisis. But the opposite happened. The negative correlation only intensified after the financial crisis.

 

A second explanation, with causality running from yen to Japanese equities, is that a weaker yen has a positive impact on corporate profits inducing equity investors to buyJapanese equities and vice versa.

 

A third explanation is that Abenomics was always thought of as a combined trade for overseas investors: buy Japanese equities and sell the yen. And reverse, i.e. sell Japanese equities and buythe yen, when Abenomics wanes.

But JPM notes both of these last two explanations have a problem: why does the yen not go up as foreign investors buyJapanese equities? In principle when foreign investors buy or sell Japanese equities currency-hedged there should be no currency impact. And when foreign investors buy or sell Japanese equities currency unhedged there should be in fact a positive correlation between the yen and Japanese equities. What are the circumstances then under which we have a negative correlation between Japanese equities and the yen?

We previously presented three flow circumstances:

 

1) If a foreign investor (buyer) purchases Japanese equities currency-hedged from another foreign investor (seller) who was long yen already (i.e. the seller owned these Japanese equities currency unhedged before), the net market impact would be an up movein Japanese equities and a down move in yen.

 

2) If a foreign investor (buyer) purchases Japanese equities currency-hedged from a Japanese investor (seller) and this Japanese investor uses the proceeds to purchase foreign equities currency-unhedged, the net impact would also be an up move in Japanese equities and a down move in yen. This flow appears to have taken place since mid-September. Foreign investors were buyers of Japanese equities, at the same time as Japanese investors sold domestic equities and as Japanese investors stepped up their purchases of foreign equities. But since September, the purchases of foreign equities by Japanese investors were smaller in magnitude relative to the purchases of Japanese equities by foreign investors. So the negative impact on theyen from the former flow was more muted relative to the positive impact on Japanese equities from the latter flow.

 

 

3) Another flow example is related to dynamic hedging by existing holders of Japanese equities, Existing foreign holders of Japanese equities could have unwound previous FX hedges in response to equity price declines in recent months, even if they did not sell any Japanese equities themselves. This is because equity investors tend to dynamically adjust their FX hedges to match the size of the hedges to the value of their equity holdings. So as the price of Japanese equities goes down in local currency terms, these foreign investors cut some of their previous FX hedges, pushing the yen up in the process. The opposite flow takes place in periods of Japanese equity appreciation: existing foreign holders of Japanese equities have to increase the size of their FX hedges to match the increased equity values, pushing the yen down in the process.

This dynamic hedging flow suggests that there should be an even stronger correlation between the performance of the yen and the absolute performance of Japanese equities in local currency terms, relative to the correlation between the yen and the relative performance of Japanese vs. US or global equities. But the two charts above show that the opposite happened this year. The correlation between the yen and the relative performance of Japanese vs. US equities has been stronger than the correlation between the performance of the yen and the absolute performance of Japanese equities. This suggests the above flow stemming from dynamic hedging by foreign investors of existing Japanese equity holdings, has likely weakened this year.

So from the above three flow circumstances, it is the second one that appears to offer the best explanation of what happened since September in the Japanese equity/yen space. 

So, following the recent buying, how overweight have foreign investors become in Japanese equities?

So in all, it appears that overweights in Japan have been focused mostly among leveraged overseas investors including CTAs, making Japanese equities vulnerable to an unwind of some of these positions in the near term. Non-leveraged institutional investors or retail investors are rather neutral.

To conclude, JPMorgan finds no reason to believe that the historical negative correlation between Japanese equities and the yen has broken down. The relationship between Japanese equities and the yen has been closely aligned this year if one looks at the relative rather than the absolute performance of Japanese equities.

More recently, since September, the purchases of foreign equities by Japanese investors were smaller in magnitude relative to the purchases of Japanese equities by foreign investors. So the negative impact on the yen from the former flow was more muted relative to the positive impact on Japanese equities from the latter flow. Going forward, overseas leveraged investors present the main vulnerability for Japanese equities, in our view.