CalPERS Calls The Top: Largest Public Pension Fund Mulls Dumping $50 Billion Of Stocks

Is the largest public pension fund in the United States getting ready to dump about $50 billion worth of stocks?  According to a new note from Bloomberg, CalPERS" board is meeting for a workshop today in Sacramento to discuss asset allocations for the upcoming year which could include a doubling of the fund"s bond allocation from 19% to 44% which would be funded with a massive $50 billion sell down of equities.

Calpers is looking at a menu of options for its fixed-income target ranging from the current 19 percent to as much as 44 percent, according to a presentation for a board workshop in Sacramento coming up Monday. Equities could be cut to as little as 34 percent from 50 percent. Stocks were the best-performing asset class in fiscal 2017, returning almost 20 percent.

 

“The markets have had a pretty good run and it’s possible Calpers staff is thinking this might be a good time to lock in some of the gains,” Keith Brainard, research director for the National Association of State Retirement Administrators, said in a phone interview.

Unfortunately, as we"ve noted before (see: CalPERS Board Votes To Maintain Ponzi Scheme With Only 50bps Reduction Of Discount Rate), a shift toward higher fixed income allocations may require a simultaneous decrease in the fund"s discount rate assumptions which could drastically increase contribution requirements from various public employers all around the Golden State.

“We’ve cut the return expectation to the point that employers are screaming, ‘We can’t afford it. We can’t afford it,’ ” Jelincic said. “I personally would be willing to take on a little more risk.”

 

The average allocation for public pensions is about 23 percent to fixed income and 49 percent to stocks, according to Nasra data.

 

The Calpers board is scheduled to vote on the allocation in December. Almost all of the fixed-income and stock holdings are managed in-house while more complex assets, such as private equity and real estate, are overseen by outside consultants. Allocations to private equity and real assets would stay at 8 percent and 13 percent, respectively, under all scenarios under consideration.

 

The allocation revisions occur every four years. Calpers is working to provide for a growing wave of longer-living retirees.

Of course, while a more conservative asset allocation may be warranted in the current bubbly equity environment, often logic is quickly dismissed by politicians when it"s implementation could expose a massive ponzi scheme that has been hiding in plain sight for decades and risks the financial solvency of local and/or statewide government entities. 

This battle between math/logic and politicians has played out numerous times in states all across the country and somehow we suspect that "math/logic" will continue to lose...better to bury your head in the sand for a couple of more years and pretend there is no problem.

"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 World"s Largest Sovereign Wealth Fund Is Investing With No Valuation Model"

There are several quotable observations in Eric Peters" latest Weekend Notes, in which the One River Asset Management CIO looks at last week"s melt-up euphoria in markets...

Hope all goes well… Abe wins landslide, Nikkei soars to 21yr high. Xi Jinping is named in China’s constitution, cementing his place alongside Mao, equities jump. House Republicans pass $4trln budget resolution, lifting hopes for a $1.5tlrn tax cut/reform. Despite devastating hurricanes, US Q3 GDP expands 3%, S&P 500 hits record high. VIX 9.80. Biggest Nasdaq 100 daily gain in 2yrs. Bezos becomes world’s richest man, +$10bln on Friday to a $93bln net worth. Such a stunning rise, a synchronized global triumph, unrecognizable from the 2008 cataclysm that produced so many waves.

.... muses on Albert Einstein"s philosophy of happiness, observes the dilemma facing Elon Musk when it comes to auto sales in China, but most notable is his take on modern capital allocation and investing by the $14 trillion pool of 401(k)s and IRAs, which he calls "the world"s largest sovereign wealth fund", and which finds itself forced to invest in such assets as Tajikistan and Iraqi bonds because the traditional framework preached by the MPT is no longer applicable, and as a result "the largest SWF on earth is investing with no valuation model but for the rear-view mirror."

Here is the full excerpt:

Fallujah

 

“It’s a monolith,” he said. “It essentially operates as a single investor, like a sovereign wealth fund,” he continued.

 

“In fact, the US 401k and IRA savings is collectively the world’s largest SWF.” From the 1978 creation of the 401k, that pool has grown to $14trln. The early adopters were baby boomers, and their holdings dwarf all others; a combination of decades of contributions and capital gains.

 

“The firms that help Americans invest their retirement savings use the same models. They all utilize the same inputs, and produce the same outputs.”

 

“Walk into Schwab, or any competitor, and ask for your target asset allocation,” he said. “You’ll discover that the dominant input is your age. It’s a robo-advisor style of investing.”

 

The older you become the more bonds you should own relative to stocks. “They boast thousands of portfolio simulations, stress tests.” They explain how the methodology is scientifically proven and based on Modern Portfolio Theory.

 

“But MPT requires that you build a robust framework for estimating future asset class returns and correlations. And they have no such framework.”

 

“Without a robust framework for estimating future returns, these 401 advisors turn to the past to estimate future returns,” he explained.

 

“Do you want to know why money is flowing into emerging market bond funds?” And I nodded. “Because the machine tells retirees that they return 13% a year.”

 

Grandpa tucked a little Tajikistan into his portfolio last month (10yr bonds auctioned at 7.12%).

 

Grandma loaded up on Fallujah (Iraq auction yielded 6.75%).

 

“The largest SWF on earth is investing with no valuation model but for the rear-view mirror.”

NYU"s "Dean Of Valuation": Bitcoin"s Not A Fraud, It"s A Currency

Aswath Damodaran, a professor of finance at the NYU"s Stern School of Business, disagrees with JPMorgan Chase CEO Jamie Dimon that bitcoin is a "fraud," and explains that, in his view, the cryptocurrency is a currency rather than an asset in a new blog post.

Often referred to as Wall Street"s "Dean of Valuation," Damodaran concludes:

"I don"t believe cryptocurrencies are now or ever will be an asset class," or that they will change the "fundamental truths of risk, investing and management."

Via Musings on Markets blog,

As I have noted with my earlier posts on crypto currencies, in general, and bitcoin, in particular, I find myself disagreeing with both its most virulent critics and its strongest proponents.  Unlike Jamie Dimon, I don"t believe that bitcoin is a fraud and that people who are "stupid enough to buy it" will pay a price for that stupidity. Unlike its biggest cheerleaders, I don"t believe that crypto currencies are now or ever will be an asset class or that these currencies can change fundamental truths about risk, investing and management. The reason for the divide, though, is that the two sides seem to disagree fundamentally on what bitcoin is, and at  the risk of raising hackles all the way around, I will argue that bitcoin is not an asset, but a currency, and as such, you cannot value it or invest in it. You can only price it and trade it.

Assets, Commodities, Currencies and Collectibles

Not everything can be valued, but almost everything can be priced. To understand the distinction between value and price, let me start by positing that every investment that I will look at has to fall into one of the following four groupings:

1. Cash Generating Asset: An asset generates or is expected to generate cash flows in the future. A business that you own is definitely an asset, as is a claim on the cash flows on that business. Those claims can be either contractually set (bonds or debt), residual (equity or stock) or even contingent (options). What assets share in common is that these cash flows can be valued, and assets with high cash flows and less risk should be valued more than assets with lower cash flows and more risk. At the same time, assets can also be priced, relative to each other, by scaling the price that you pay to a common metric. With stocks, this takes the form of comparing pricing multiples (PE ratio, EV/EBITDA, Price to Book or Value/Sales) across similar companies to form pricing judgments of which stocks are cheap and which ones are expensive.

 

2. Commodity: A commodity derives its value from its use as raw material to meet a fundamental need, whether it be energy, food or shelter. While that value can be estimated by looking at the demand for and supply of the commodity, there are long lag and lead times in both that make that valuation process much more difficult than for an asset. Consequently, commodities tend to be priced, often relative to their own history, with normalized oil, coal wheat or iron ore prices being computed by averaging prices across long cycles.

 

3. Currency: A currency is a medium of exchange that you use to denominate cash flows and is a store of purchasing power, if you choose to not invest. Standing alone, currencies have no cash flows and  cannot be valued, but they can be priced against other currencies. In the long term, currencies that are accepted more widely as a medium of exchange and that hold their purchasing power better over time should see their prices rise, relative to currencies that don"t have those characteristics. In the short term, though, other forces including governments trying to manipulate exchange rates can dominate. Using a more conventional currency example, you can see this in a graph of the US $ against seven fiat currencies, where over the long term (1995-2017), you can see the Swiss Franc and the Chinese Yuan increasing in price, relative to the $, and the Mexican Peso, Brazilian Real, Indian Rupee and British Pound, dropping in price, again relative to the $.

 

 

4. Collectible: A collectible has no cash flows and is not a medium of exchange but it can sometimes have aesthetic value (as is the case with a master painting or a sculpture) or an emotional attachment (a baseball card or team jersey). A collectible cannot be valued since it too generates no cash flows but it can be priced, based upon how other people perceive its desirability and the scarcity of the collectible. 

Viewed through this prism, Gold is clearly not a cash flow generating asset, but is it a commodity? Since gold"s value has little to do with its utilitarian functions and more to do with its longstanding function as a store of value, especially during crises or when you lose faith in paper currencies, it is more currency than commodity. Real estate is an asset, even if it takes the form of a personal home, because you would have had to pay rental expenses (a cash flow), in its absence. Private equity and hedge funds are forms of investing in assets, currencies, commodities or collectibles, and are not separate asset classes. 

Investing versus Trading

The key is that cash generating assets can be both valued and priced, commodities can be priced much more easily than valued, and currencies and collectibles can only be priced. So what? I have written before about the divide between investing and trading and it is worth revisiting that contrast. To invest in something, you need to assess its value, compare to the price, and then act on that comparison, buying if the price is less than value and selling if it is greater. Trading is a much simpler exercise, where you price something, make a judgment on whether that price will go up or down in the next time period and then make a pricing bet. While you can be successful at either, the skill sets and tool kits that you use are different for investing and trading, and what makes for a good investor is different from the ingredients needed for good trading. The table below captures the difference between trading (the pricing game) and investing (the value game).

As I see it, you can play either the value or pricing game well, but being delusional about the game you are playing, and using the wrong tools or bringing the wrong skill set to that game, is a recipe for disaster.

What is Bitcoin?

The first step towards a serious debate on bitcoin then has to be deciding whether it is an asset, a currency, a commodity or collectible. Bitcoin is not an asset, since it does not generate cash flows standing alone for those who hold it (until you sell it).  It is not a commodity, because it is not raw material that can be used in the production of something useful. The only exception that I can think off is that if it becomes a necessary component of smart contracts, it could take on the role of a commodity; that may be ethereum"s saving grace, since it has been marketed less as a currency and more as a smart contracting lubricant.  The choice then becomes whether it is a currency or a collectible, with its supporters tilting towards the former and its detractors the latter. I argued in my last post that Bitcoin is a currency, but it is not a good one yet, insofar as it has only limited acceptance as a medium of exchange and it is too volatile to be a store of value. Looking forward, there are three possible paths that I see for Bitcoin as a currency, from best case to worst case.

1. The Global Digital Currency: In the best case scenario, Bitcoin gains wide acceptance in transactions across the world, becoming a widely used global digital currency. For this to happen, it has to become more stable (relative to other currencies), central banks and governments around the world have to accept its use (or at least not actively try to impede it) and the aura of mystery around it has to fade. If that happens, it could compete with fiat currencies and given the algorithm set limits on its creation, its high price could be justified.

 

2. Gold for Millennials: In this scenario, Bitcoin becomes a haven for those who do not trust central banks, governments and fiat currencies. In short, it takes on the role that gold has, historically, for those who have lost trust in or fear centralized authority. It is interesting that the language of Bitcoin is filled with mining terminology, since it suggests that intentionally or otherwise, the creators of Bitcoin shared this vision. In fact, the hard cap on Bitcoin of 21 million is more compatible with this scenario than the first one. If this scenario unfolds, and Bitcoin shows the same staying power as gold, it will behave like gold does, rising during crises and dropping in more sanguine time periods. 

 

3. The 21st Century Tulip Bulb: In this, the worst case scenario, Bitcoin is like a shooting star, attracting more money as it soars, from those who see it as a source of easy profits, but just as quickly flares out as these traders move on to something new and different (which could be a different and better designed digital currency), leaving Bitcoin holders with memories of what might have been. If this happens, Bitcoin could very well become the equivalent of Tulip Bulbs, a speculative asset that saw its prices soar in the sixteen hundreds in Holland, before collapsing in the aftermath.

I would be lying if I said that I knew which of these scenarios will unfold, but they are all still plausible scenarios. If you are trading in Bitcoin, you may very well not care, since your time horizon may be in minutes and hours, not weeks, months or years. If you have a longer term interest in Bitcoin, though, your focus should be less on the noise of day-to-day price movements and more on advancements on its use as a currency. Note also that you could be a pessimist on Bitcoin and other crypto currencies but be an optimist about the underlying technology, especially block chain, and its potential for disruption.

Reality Checks

Combining the section where I classified investments into assets, commodities, currencies and collectibles with the one where I argued that Bitcoin is a "young" currency allows me to draw the following conclusions:

1. Bitcoin is not an asset class: To those who are carving out a portion of their portfolios for Bitcoin, be clear about why you are doing it. It is not because you want to a diversified portfolio and hold all asset classes, it is because you want to use your trading skills on Bitcoin to supercharge your portfolio returns. Lest you view this as a swipe at cryptocurrencies, I would hasten to add that fiat currencies (like the US dollar, Euro or Yen) are not asset classes either.

 

2. You cannot value Bitcoin, you can only price it: This follows from the acceptance that Bitcoin is a currency, not an asset or a commodity. Any one who claims to value Bitcoin either has a very different definition of value than I do or is just making up stuff as he or she goes along.

 

3. It will be judged as a currency: In the long term, the price that you attach to Bitcoin will depend on how well it will performs as a currency. If it is accepted widely as a medium of exchange and is stable enough to be a store of value, it should command a high price. If it becomes gold-like, a fringe currency that investors flee to during crises, its price will be lower. Worse, if it is a transient currency that loses all purchasing power, as it is replaced by something new and different, it will crash and burn.

 

4. You don"t invest in Bitcoin, you trade it: Since you cannot value Bitcoin, you don"t have a critical ingredient that you need to be an investor. You can trade Bitcoin and become wealthy doing so, but it is because you are a good trader.

 

5. Good trader ingredients: To be a successful trader in Bitcoin, you need to recognize that moves in its price will have little do with fundamentals, everything to do with mood and momentum and big price shifts can happen on incremental information.

Would I buy Bitcoin at $6,100? No, but not for the reasons that you think. It is not because I believe that it is over valued, since I cannot make that judgment without valuing it and as I noted before, it cannot be valued. It is because I am not and never have been a good trader and, as a consequence, my pricing judgments are suspect.

If you have good trading instincts, you should play the pricing game, as long as you recognize that it is a game, where you can win millions or lose millions, based upon your calls on momentum. If you win millions, I wish you the best! If you lose millions, please don"t let paranoia lead you to blame the establishment, banks and governments for why you lost. Come easy, go easy!

*  *  *

As a reminder, CoinDesk reports that back in July, Damodaran also argued that cryptocurrencies were quickly becoming a preferred alternative to gold for people who don"t trust traditional fiat currencies.

SocGen: "Now Entering Dangerous Volatility Regimes"

With the VIX back to a 10-handle and eagerly eyeing single-digits once again, commentary on market complacency and the low VIX, which was blissfully gone for the past month when the VIX surged valiantly if briefly only to be smacked right back down, has returned. In a note from SocGen"s Praveen Singh, the French bank analyst boldly goes where so many prognosticators have gone before, and looking at the evolving cross-asset volatility trends, warns that the market is "now entering dangerous volatility regimes."

Hardly stating the unknown, Singh writes that "expected volatility has been falling consistently. Over the last year, expected volatility has been falling on a consistent basis. When we look at equity and  government bonds, the current  level of volatility is well below long-term average volatility. Falling volatility normally means stable environment for risk assets."

So time for some (familiar) numbers: the current low level of volatility happens less than 2% of the time for equities. In the following chart, SocGen plots the distribution of equity volatility based on data since 1994. The bank"s analysis suggests that average equity volatility has been above the current level 98% of the time. This means that volatility is more likely to go up than fall further from current levels... at least in theory, of course. In practice, what it means these days is that some central banks unload a few thousand VIX contracts to prevent any vol spike at just the right time.

Undeterred, SocGen presses on and warns that - central banks aside - in the past, equity volatility has bottomed at around current levels and rose subsequently. Volatility has a strong mean-reverting tendency.

"Hence, we observe that periods of particularly low volatility are often followed by periods of relatively higher volatility."

Of course, It"s not just equities: The low level of volatility is pervasive across asset classes and as Singh shows in the chart below, "we compare the current level of volatility with the historical range. We find that for most asset classes the current level of volatility is near the lower end of its long-term range."

Again, none of the above is new, and it goes to one fundamental theme involving vol: mean-reversion, a phenomenon which always happens, yet which has been sorely lacking in the space for a long, long time. As such, all SocGen is saying is that "it"s time"... but is it? Many traders have been crushed betting on an imminent vol surge, which never materialized. Why will this time be any different? Here"s SocGen"s rationalization:

How long can volatility stay this low? In the past, when equity market volatility was around the current level, it went on to rise by 3 points in the subsequent 12 months. In the below charts, we show evolution of equity volatility between 2007 and 2009. We note that:

• Equity volatility troughed in February 2007, around eight months ahead of the US equity market peak. The current level of equity volatility is very similar to what we saw in February 2007. Equity market volatility started to rise in the subsequent months.


• We note that the dislocation in equity market volatility is much greater than the dislocation in government bonds.

Finally, does SocGen"s concern mean investors should get out of stocks? Well... not really. As Singh concludes, the current low level of volatility makes equities our preferred asset class as risk-adjusted return is higher. However, a subsequent rise in volatility means: i) Balanced asset allocation, i.e. 50% equity and 50% fixed income, is better than a more dynamic (higher equity) allocation. ii) Equity re-allocation i.e. avoid areas where risk-adjusted return is deteriorating (US equity allocation has been reduced in our latest Q-MAP balanced portfolio). iii)  Increase cash allocation (our cash allocation has been increased from 5% to 10%).

So after predicting that a 2007 vol episode may be imminent (as a reminder, back then the VIX briefly tagged 80 in the process destroying all vol sellers), SocGen"s brave reco is to increase cash from 5% to 10%. One may just buy bitcoin instead.

The 3 Reasons Why Goldman Just Turned Bullish On Gold

Following this morning"s flash crash in gold, in which a "fat finger" - usually a euphemism for any trade that can not be logically explained yet one which reprices a given asset class substantially lower as happened with gold - suddenly sold $2.2 billion worth of gold in under a minute, taking out the entire bidside stack, we were expecting banks to immediately come out with bearish reports on gold, piggybacking on the latest central bank-facilitiated smackdown, and allegedly allowing their prop desks to load up on the yellow metal on the cheap.

We were surprised, however, when moments ago Goldman came out with a report explaining why the bank is now bullish on gold, Further, in the note from Goldman"s x-asset strategist, the bank laid out three specific reasons why gold may trade well above the bank"s commodity team year-end target of $1,250.

This is what Goldman said moments ago:

Across asset classes last week copper was the best performing asset (+2.5%), while oil was the worst performing asset (-4.3%, Exhibit 3). Gold"s performance was flat (+0.1%) over the same period, but had an intraday min at 1.6% today. Much of the focus has obviously been on oil where concerns are that expanding supply in the US and Libya will counter OPEC cuts. Gold has received less focus, although its cross-asset correlations have quietly been rising to new extremes (Exhibit 1).

Our commodity team"s view is gold at $1250/oz over 12 months as higher real rates from Fed tightening could put further pressure on gold, but this may be offset by 3 things:

1. lower returns in US equity (as we expect) should support a more defensive investor allocation,


2. EM $GDP acceleration would add purchasing power to EM economies with high propensity to consume gold, and


3. GS expects gold mine supply to peak in 2017.

Gold has been increasingly trading as a "risk off" asset, with its correlation with global bonds at the 100th percentile since 2002...

... and should thus be sensitive to our expectation of rising rates from here. However, with global growth momentum likely having peaked, gold could represent a good hedge for equity, in particular in currencies with low and anchored real yields.

Gold implied vol remains attractive for investors" of either view: it trades at its 0th percentile relative to the past 10 years (Exhibit 28).

While Goldman"s arguments are sound, the fact that the bank is urging its clients to buy gold, ideally from Goldman, suggests that the selloff is most likely nowhere near done.

Axel Merk: "There's More To Investing Than Chasing Companies That Want To Make Mars Inhabitable"

Authored by Axel Merk via MerkInvestments.com,

How does one construct a portfolio in an era of seemingly ever rising and highly correlated asset prices? Years of asset prices moving higher has changed both retail and institutional investors; it has changed the industry; and, in my humble opinion, those changes spell trouble. The prudent investor might want to take note to be prepared.

I allege that for many, investing is no longer about prudent asset allocation, but about expressing themes. If you like green technology, you tilt your portfolio towards green energy. If you are socially conscious, there’s an ETF for that. I have no problem with anyone allocating money to any specific theme. However, has anyone else noticed that it doesn’t matter what theme you allocate money to? Investors are all playing the lottery and guess what: everyone’s a winner!

Now, clearly, that’s an over simplification, as not every industry does well all the time - just ask those who invested in MLPs (master limited partnerships) in pursuit of income from fracking. Let me rephrase: the more of a monkey you have been, i.e. the less you have been thinking, the better you’ve likely performed over the past nine years. “Buying the dips” has been a consistently profitable strategy.

That has created numerous oddities:

• Take the investor who diversifies, rebalancing part of a portfolio to near zero-income generating fixed income. Advisors pursing such strategies have seen their clients take money away, as they are not willing to pay a management fee for essentially holding cash.

The problem: cash is discarded even if it may be a prudent investment choice.

• Take the investor who diversifies, rebalancing part of a portfolio to alternative income streams.

The problem: Anything that generates an income in a zero-income environment is, almost by definition, risky. That is, both stock and fixed income securities in such a portfolio are so-called risk assets, i.e. I believe they are likely to move in tandem, not providing desirable diversification in a downturn.

• Take the prudent investment advisor who has allocated part of a portfolio to true alternatives, such as long/short equities or long/short currencies. While providing diversification, such portfolios have likely underperformed during the relentless rise of equities. Worse, when the markets have had a hiccup, such as in early 2016, many of those portfolios still lost money, as the volatility of risk assets overwhelmed the cushion provided by the alternatives. Read: clients have been abandoning advisors, lured by competitors showing how great their performance has been, investing 100% in equities since the spring of 2009.

The problem: Those solicitations conveniently skip the inconvenient fact that their clients lost huge in 2008.

• Take the investor who wants to participate in the upside, but be protected on the downside.

The problem: they spend a small fortune buying insurance, even when they might be better off just holding a cash buffer (again, advisors don’t hold cash, as clients would withdraw that cash at some point).

• If many want to buy insurance, someone needs to write insurance. The one thing more profitable than buying stocks may well have been to write insurance. Funds that “sell volatility”, amongst others, have been amongst the best performers in the first quarter. Mind you, we do not recommend you touch any such product with a broomstick unless you know exactly what you are doing and able to stomach some serious losses. The theory behind many of these funds is that you collect what amounts to an insurance premium when volatility is low; the periods when you have to pay up are short and intense, but those setbacks are ultimately temporary.

The problem: Earlier this year, one such fund was in the news for substantial losses, not because volatility spiked, but because portfolio management got cornered when they tried to roll derivative contracts. Let’s just say: something that looks too good to be true, may well be. Interesting things may well happen (read “contagion”) if and when these positions unwind.

• Active management is dead. Long live passive investing. Never mind that anything but an index fund on the broad market is an active investment choice. The point being that you don’t want to pay some smart cookie to try to beat the market. That’s because those so-called experts were wrong in 2008 (and many times since). What can they possibly know? Besides, your favorite green tech investment fund is doing just fine, thank you very much.

The problem: Cautions provided by active managers help one frame possible risk scenarios. Managing risk is important, even if many risks never materialize.

• Active managers are leaving the industry. Who needs anyone skilled in navigating rough waters when you have robots providing liquidity?

The problem: it may be helpful to have a captain on board when the auto-pilot fails.

• Brokers are increasingly hand-holding relationship people, with portfolio allocation decisions being made by a small group creating model portfolios. After all, why risk your job trying to go out on a limb for your client?

The problem: there’s nothing wrong per se with this trend, except that it increasingly concentrates investment decisions for huge amounts of money into very few people. We hope they are smart. Importantly, we hope investors understand who makes the investment decisions and what the conflicts are. Let’s just say: when something goes wrong, class action lawyers will have their day in court.

• An increasing number of investors are skipping advisers altogether. After all, why not cut out the middle man if they don’t know any better than you do?

The problem: there’s no problem with do-it-yourself investing except, just as professionals, investors owe it to themselves to make prudent investment decisions. We think that many individual investors do a better job than some professional investors these days in allocating their money. That said, that’s a very low bar.

• If you have enough money, you allocate some money to venture capital. At least you have something to talk about at cocktail parties. It might help if you knew what your venture capital fund invested in, but let’s not get distracted by details.

The problem: no problem if you can afford it. May I make the suggestion, though, that you first try to understand your overall portfolio, before you dabble in illiquid investments?

What could possibly go wrong?

Quite simply, markets do go down, not just up. In my view there is an increased risk of a flash crash in an environment where we are ever more dependent on automated liquidity providers that might withdraw liquidity the instant there’s an anomaly in the market (read: if you place a market order to sell a security, don’t complain if the market price is dramatically below the most recent trade on an exchange).

While regulators may be all over flash crashes and possibly bail you out by canceling your order, a more pronounced decline is something you might want to prepare for as well. We hear pundits proclaim that we cannot have a bear market unless there’s a recession. There are couple of problems with that:

• First, it’s not true. There was no recession during the October 1987 crash.


• Second, we often don’t know whether there’s a recession until we are well into it; there have been instances when we didn’t know there was a recession until it was over.


• Third, we’ll only know we are in a “bear market” when the market is down 20%. That’s kind of late to prepare for a bear market. Except, of course, if the market tumbles much more than that, such as the Nasdaq after 2000; or the S&P 500 in 2008.

Is there a better way?

The other day, we met with an investor who has 40% of his portfolio in cash. He doesn’t like market valuations and has decided, he’ll put money to work if the market declines by 10%; then more money to work if it declines another 10%. We think this investment philosophy beats that of many. At least, he has taken chips off the table during the good times and has money to deploy. Before readers cry out: “There’s so much cash on the sidelines, this market must go up!”, I would like to caution that this investor is a rare exception of many investors I talk to - and I talk to retail investors, advisors, family offices, to name a few. The same person, by the way, told me he is at a loss on what to advise his friends, as he doesn’t want to encourage them to get into the markets given current valuations.

Indeed, this appears to be a market where just about every pessimist is fully invested. Because folks have been wrong so many times calling the market top, we believe many market bears are fully invested.

I think there’s a better way. The better way of investing is to take the long view. Sure it’s great to have one’s stock portfolio surge, but investing, in the opinion of yours truly, isn’t about gambling, but about asset allocation with humility. Passive investing is all right for certain things, but should not replace common sense. When the likely successor to Janet Yellen (we put our chips on Kevin Warsh) has complained that asset holders have disproportionally benefited from monetary policy, and that the focus has to shift, I think it’s but one indication to do a reality check on one’s portfolio, as headwinds to asset prices may well increase.

The short answer is that investors may well look at their portfolios more like pension funds or college endowments do. Except, well, many pension funds and college endowments have fallen into the same traps individual investors and advisors have. Let me rephrase: investors might want to invest according to a philosophy a well-run endowment might have. Let me just mention a few principles here. Here’s the investment allocation of an endowment of a private college - I’m not suggesting this specific allocation is the right one for any specific person or institution, but want to provide it as food for thought:

• 31% hedged strategies


• 27% equities


• 21% private equity


• 8% real assets


• 6% cash


• 5% fixed income


• 2% equity-like credit

Note that the equity holdings are less than 30%, not the 60% often touted in a “60/40” portfolio (with 40% referring to bonds). The number can be larger or smaller for any one investor, but I believe we should get away from the notion that one needs to have a large portion invested in equities. Endowments are long-term investors, yet don’t go to 100% equities; so why should a young investor be all in equities? By allocating a far smaller portion, you don’t need to lose sleep over asset bubbles. Instead, you can indeed rebalance or make gradual shifts.

Note the biggest bucket is “hedged strategies.” We have long advocated that investors need to look for uncorrelated returns. A long/short equity strategy or long/short currency strategy might generate such returns. Importantly, this bucket of alternatives is far higher than what many advisors choose. In an era of very expensive assets, we think this may be rather prudent. This doesn’t solve the issue of how to find the right hedged strategy - remember that those strategies will have under-performed the overall market. Important here is the investment process of the underlying ETF, mutual fund or whatever product one might want to consider.

Private equity is obviously not accessible to many investors. Relevant though is that there’s a big bucket allocated to investments where one expects a long-term return without seeing the daily price moves. Sometimes it’s good not to have tick-by-tick data. An individual investor might be able to replicate this by opening another account, selecting a few long-term ideas, then throwing away the key to the account for a few years. Well, one should still review the investments periodically, but the point being: it is okay to invest different portions of a portfolio according to different philosophies. Say, be a day trader for a small portion, but do hold strategic positions. Some of this can be achieved by intentionally mixing up the styles of different investment products. If not all of them perform well at the same time, that’s a good thing!

This particular portfolio has a small allocation to “equity-like credit”; we are not making a judgment whether this is too high or too low; the point again is that there’s a very broad allocation to different asset classes. Note, by the way, that ‘equity-like credit’ is likely to perform, well, like equities. Even with those assets added, the equity portion is still modest.

Not mentioned in this particular portfolio, as least not in the headline numbers, is an allocation to precious metals or commodities. Those who have followed us for some time know that we encourage investors to consider gold as a diversifier. We have often referred to gold as the “easiest” diversifier because it’s easier to understand than some exotic long/short strategy. In our analysis, the price of gold has had a near zero correlation to the S&P 500 since 1970; however, over shorter periods, correlations can be elevated. In our analysis, gold has done well in every bear market since 1971, with the notable exception of the bear market in the early 1980s when then Fed Chair Volcker raised interest rates rather substantially.

The point of all of this is not to suggest that investors need to add equity-linked credit or private equity to their portfolio. No, the point is that there’s more to investing than chasing high flying companies that promise to make Mars habitable.

You might have also noticed that I squeezed in the word “humility” in asset allocation above. Have some respect that things that go up can also go down. Having respect means that one doesn’t adjust one’s lifestyle (expenditures) as a reaction to rising asset prices. Investors can control expenses more so than income. So maybe we should be spending far more time talking about how we spend our money rather than how we invest it. But I digress...

BofA: The Market Is No Longer Efficient

Almost exactly 8 years ago, in April of 2009 we wrote for the first time that as a result of the confluence of unprecedented central bank intervention meant to prop up risk prices which distort markets in the long run, and the rising dominance of HFT and algo trading strategies, which distort price formation in the ultra-short term, the market is no longer a (somewhat) efficient, discounting mechanism, but has in fact been "broken."

Now, in a note released overnight by BofA"s Savita Subramanian, the equity analyst comes to the same conclusion: the market is no longer efficient, primarily as a result of a wholesale scramble for short-term, data-driven trading gains, which have made a mockery of fundamental analysis and a focus on long-term investing profits.

Here are some of her observations:

Stocks for the long-term is an all but forgotten concept today. The rise of short-term investment strategies, which tend to rely on access to better, faster and larger stores of data and information, has attracted trillions of dollars of capital, compressing equity holding periods and likely exacerbating spikes in short-term volatility.

Managed futures funds (also known as CTAs), which tend to trade based on quantitative algorithms, have grown rapidly over the past several decades. According to BarclayHedge, their assets have grown to over 250bn, making up close to 10% of the total hedge fund universe.

Similarly, low volatility computer-driven strategies have also seen significant growth in recent years.

Quantitatively oriented clients have 3x the number of factors today than they did twenty years ago (Chart 5). Quant/factor investing popularity has increased sharply, at the expense of interest in fundamental investing (Chart 6). One of today’s greatest market inefficiencies may stem from the scarcity of capital devoted toward long-term, fundamental investing.

And yet, long-term market inefficiencies have increased: Given the abundance and improvement in data, analysis and tools, oddly enough, what should be an increasingly efficient market shows some signs of becoming less efficient. In tandem with asset growth in “fast money”, the opportunity set, as measured by the range of market prices, has shrunk on a short-term basis, but has risen on a long term basis.  

The number of analysts covering stocks has structurally
decreased – suggesting that the human element of fundamental analysis
(assessing body language of management, physical channel checks, etc)
have been supplanted by processes.

* * *

So are human traders destined for extinction as robots take over all jobs with only ETF trading soon remaining? Well, since BofA"s paying clients tend to be human, Savita had to put an optimistic spin on her findings. This is what she said:

Fundamentals win over long time horizons. The declining interest, assets and resources devoted to fundamental analysis suggests a significant opportunity in our view. Fundamental investing is not dead, far from it, but seems to require patience. Our analysis shows that fundamental signals see amplified performance as time periods are extended, but technical and positioning-based signals do reasonably well in the short term, but see marked alpha decay over the long term.

 

Over the long term, valuation is almost all that matters. Valuations have historically explained 60-90% of subsequent returns over a 10-year time horizon, with the price to normalized earnings ratio (our preferred valuation metric) explaining 80-90% of returns over the subsequent 10 years (Chart 13). Most other valuation measures have a reasonably strong level of efficacy over long time horizons (Table 1). We have yet to find any factor with such strong   predictive power over the short term.

 

Time really is money…At least for stocks. As investment time horizons lengthen, the probability of losing money in stocks generally decreases. While trading stocks over a one-day period can be
considered to be only marginally better than a coin-flip, the probability of losing money plummets to 0% over a 20-year time horizon. Moreover, time horizon arbitrage is unique to equities: other asset classes (for example, commodities, as shown below) do not exhibit such characteristics (Chart 14).

 

Over the past 80 years, only two decades have produced negative total returns: the 1930s (only -1% despite the Great Depression) and the 2000s (-9%, the worst decade for investors which started with high valuations and the “tech bubble” bursting and ended just after the financial crisis). Other decades also had numerous crises: 1940s (WWII); 1950s (Korean War); 1960s (social unrest, Vietnam war, JFK assassination); 1970s (hyperinflation, oil embargo); 1980s (mortgage rates near 20%, LatAm debt crisis, crash of 1987, S&L crisis); 1990s (Asia/Mexico/Russia crises, LTCM) yet produced solid returns for those who remained invested.

While we applaud the finding that "valuations matter" - as otherwise thousands of universities around the world would have to give their econ and finance professors the pink slip - there"s just one problem with the above: LPs and other asset allocators no longer have "patience."As another BofA analysis also released overnight showed, according to which a great rotation from active to passive management is taking place.  And while fundamental investing may "not be dead", those who practice it will soon have no cash left to manage, which is essentially the same thing.

The Number 1 Reason Why Trump Is Good For Stocks

Via ConvergEx"s Nicholas Colas,

 The US equity market is very different than before Election Day 2016, and that’s not just because we are at fresh all-time highs.  There were plenty of new highs from 2013-2016, after all.  What’s different is the lack of sector and asset class correlation now versus 2009 – 2016.

Simply put, they are finally back to normal.  The drop in correlations among the 11 sectors of the S&P 500 has been profound, from 75-80% pre-Election to 57-62% afterwards.  This month’s reading of 57% points to the lasting nature of the change; this is a not blip.

The ramifications of this shift are: 1) lower S&P volatility (because, math) 2) getting sector bets right is now even more critical to outperformance and 3) it applies not only to domestic US equities, but to global managers who must allocate to EAFE and Emerging Market assets (correlations are structurally lower there as well).

It has been 94 days since the US Presidential election and Donald Trump’s surprise win.  In some ways it feels like yesterday, if only because it was not the expected outcome.  And in other ways, it feels like it was years ago.  Especially if you follow US equity markets, which have been remarkably quiescent.  If a modern day Rip Van Winkle went to sleep on November 7th, woke up today, and looked at a chart of the S&P 500 he might think “Oh, Hillary Clinton won…  And everything is status quo.  I am a little surprised US stocks rallied so hard, but there’s no volatility.  Yep – Hillary won.”

To see the effect of the Trump victory, you have to look at something other than price levels; you have to examine asset and sector price correlations.  We have been doing this monthly since 2009, and the story has been largely the same.  Correlations among the 10 (now 11) sectors of the S&P 500 have averaged 80-90%, and Emerging Markets and EAFE (Europe, Asia, Far East) equity markets have similarly tracked US equities.  This was known as ‘Risk On, Risk Off” for much of the post 2009 period of market history.  Everything goes up on the same days, and down on the same days.

Well, the world is very different now, and by a magnitude I would have thought impossible 95 days ago. We have attached some tables and charts to this note (click at the top for the PDF), but here is the highlight reel:

• Average sector correlations to the S&P 500 were 57.1% last month. On the eve of the US elections, they were 66% and for the prior year they had ranged from 70-80%.  From 2009 – 2015, they were rarely below 80% and were +90% for 5 months straight in 2011. Since the election, sector correlations to the S&P 500 have been 56.8% (December), 61.2% (January) and that 57.1% reading we just mentioned.  Keep in mind that 50% is a good estimate for a pre-Crisis long run average, and we are basically there now after almost a decade of unusually high correlations.


• The same observation holds for international equity markets. They have been tied at the hip to US stocks since the Financial Crisis as well, but now correlations for the EAFE country stocks to the S&P 500 are 61.4% and for Emerging Market equities it is 34.6%. The ramp down post-US election was a little slower.  Correlations last month were 74.3% (EAFE) and 55.1% (Emerging Markets).


• The story in other asset classes is mixed. Precious metals (gold and silver) have been consistently in the low-correlation camp since 2009, and remain so today.  High yield corporate bonds are seeing higher correlations to US stocks in the past month (now 72.9%, but 62.5% last month and 54.7% the month before that).  High quality corporates and long dated Treasuries now sport (no surprise) a negative correlation to US stocks (-30.2% and -35.9%, respectively).

Since correlations were uniformly high before Election Day and now have reverted to much lower long term averages, we are going to chalk this up entirely to Donald Trump’s victory.  Nothing else is sufficiently different so as to explain it.  And as much as the recent spate of new highs is a welcomed development, we had new highs before the Election. The drop in correlations is really “New new”.

The big question is “OK, what does this mean?”  Three thoughts to wrap up this note:

Point #1: Lower correlations mean less price volatility in the S&P 500. That’s just math:  the lower the correlation between assets in a portfolio, the lower the overall volatility. That’s one reason why the CBOE VIX Index has been so low (along with realized volatility).  We’ll have to wait and see how much the sector correlations stay low when we get a systemic shock, but for now we can expect volatility to remain under pressure.

Point #2: Getting sector and stock bets right just got a whole lot more serious.  As correlations drift lower, different sectors will tend to show greater price and performance dispersion.  Use Health Care as an example.  Say you underweighted that group at the end of last year.  Big mistake: it is up 4.1% year to date, and only overweights in Tech (+5.9% YTD) and/or Consumer Discretionary (+4.8% YTD) would have saved you so far.  No other sector has better YTD performance than those three.

Point #3: The same goes for international equity portfolios.  Emerging markets are up 8.2% in dollar terms so far in 2017. EAFE is up 3.9% - more than the S&P 500’s 3.1% price return.

We will close with two reminders.

• Next week is St Valentine’s Day (Tuesday). Make sure whatever you might be getting your significant other arrives on Monday, not Tuesday.  If you leave it up to UPS or FedEx or the local florist, your gift will arrive at 5pm.  You don’t want to leave your special someone hanging, do you?


• The day after Valentine’s is the unofficial middle of the first quarter. The drop in correlations has put a lot of managers on the back foot. Just consider Financials – last quarter’s “It” sector has underperformed in Q1 (2.1% versus 3.1% for the S&P 500). Or Energy, last year’s big winner and with a lot of funds still overweight (down 3.3% YTD).

That’s the rough part about the sudden drop in correlation; being wrong just got a lot more expensive.  Underperforming groups like Energy and Financials are on a short leash as we transit the mid-quarter point. They both worked today, but they have a lot of ground to cover.  You might not see this turmoil on the market’s surface, but it is there.  And it will most likely get even choppier.