The MLM Index™ (see www.mtlucas.com for a description of the MLM Index™) does not include an allocation to equities. Many of our trend follower competitors do include them, and as a result we get asked all the time the reasons behind excluding them. As we have written about in previous posts (Portfolio Symmetry and Commodities are not Stocks), we believe that commercial markets like commodities, currency and interest rates are fundamentally different than equity markets, and need to be accessed in a different way, matching the economic rationale for the markets existence. Equity markets exist to fund the growth of capitalism and transfer capital from savers to businesses to be invested profitably. That’s a long only rationale in our mind, as the market participants are overwhelmingly one way. We think this is borne out by the tendency of equity earnings and prices to generally rise over time as economies grow. It also means that there isn’t a natural investment pool short the equity markets – no one has a business model that relies upon falling equity prices. One way you can see the differing utility functions is in the options market – implied volatility on puts trade at a premium to calls, as the demand for protection of a long investment book is much greater than the demand for call protection on a big real money short portfolio. Continue reading
Obviousness alert! – getting the asset class betas right is the most important first step in building a portfolio. Once those decisions are made, adding alpha is an important secondary objective. We invest along the same lines we see businesses operating in the real world – raising capital to fund growth through equity and credit markets, while managing the operational price risks that impact the running of the business as best they can. Both of these create risk premiums; markets exist to transfer them to investors. We try to balance them. To us, these two premiums are complementary, but need to be accessed in different ways. The investment risk premium funds economic activity by investing in equity and credit securities from the long side, directing capital to those who seek to expand and transfer capital risk. The price risk premium takes on exogenous input and output cost risk in commodity prices, currency movements and interest rates, facilitating hedging that allows business more certainty in operations, allowing them to focus on the core expertise. Crucially, it does this from both sides of the market, trend following long and short. Combining these is very attractive, as one side thrives on stability and generally rising growth, whilst the other thrives in times of instability. Put very simply, the investment risk premium looks for cash flows, the price risk premium looks for crash flows. We think of trend following as a beta in its own right, an important distinction between us and other more traditional long only approaches. It is a beta that most portfolios are wildly underexposed to, if they have any exposure at all. We believe in equalizing the risk between them, viewing both as having long term positive expected returns while being uncorrelated most of the time, and often negatively correlated in times of stress. When it comes to adding alpha to these balanced betas, we do all the things the academic literature leads you to – buy value, momentum persists, diversify, equally weight. Over time, we expect all of these alpha decisions to contribute strongly to the static beta approach above.
The diversification of balancing these premiums has played out a number of times over the years, and we are seeing it again as we start the new year. The stability the investment risk premium prefers is rattled by fears of global growth. This is getting offset by the price risk premium is capturing the fear as it manifests itself through flows in other asset classes – falling commodity prices, a flight to safety in bonds and flows into safe haven currencies. It has been a great example of a concept we have seen for many years, and highlights how more traditional long only approaches to investing in commodities don’t make sense. Structurally, over time, human ingenuity lowers the real price of commodities, while cyclically they move on supply and demand. They are not static long only investments, one needs to be able to take both sides of the market, taking on risk from producers and users. We think of interest rates in a somewhat similar way – a factor outside the control of a business that needs to be managed. Developed market bonds offer very low or negative real returns. Investors that leverage bonds in order to equalize volatility or returns with equity markets are running real risks – having the flexibility to take exposure on both the long side and the short side will be crucial in the coming years.
The BLS Quarterly Census of Employment and Wages, collected from unemployment claims data, provides the Labor Department with a comprehensive view of the jobs and earnings market for the U.S. economy. The first quarter 2015 survey covered over 9 million establishments employing a total of over 135 million employees—around 98% of the total population of individuals on company payrolls. In contrast the non-farm payroll series surveys a small sample, 143,000, of the population of 9 million establishments.
When I started at Commodities Corporation in 1979, we managed $100MM dollars. We had computers that sat on raised floors in climate controlled rooms. We were state of the art….and we still had 100 employees. Alas, fees were higher, but my point is that advancing data availability and data processing has been a boon to the investment industry.
But there has been an unmistakable downside to all this power and information, what my partner Roger has christened “false precision”. Everyone has lots of data and the power to manipulate it with ease. All questions can be answered with “hard numbers”. Risks can be fully calibrated (see previous post, A Note on Risk). Nowhere has this thinking reached more heroic levels of absurdity than at your Federal Reserve. From a Chairman Yellen speech, circa 2012:
Although simple rules provide a useful starting point in determining appropriate policy, they by no means deserve the “last word”–especially in current circumstances. An alternative approach, also illustrated in figure 10, is to compute an “optimal control” path for the federal funds rate using an economic model–FRB/US, in this case. Such a path is chosen to minimize the value of a specific “loss function” conditional on a baseline forecast of economic conditions. The loss function attempts to quantify the social costs resulting from deviations of inflation from the Committee’s longer-run goal and from deviations of unemployment from its longer-run normal rate. The solid green line with dots in figure 10 shows the “optimal control” path for the federal funds rate, again conditioned on the illustrative baseline outlook. This policy involves keeping the federal funds rate close to zero until late 2015, four quarters longer than the balanced-approach rule prescription and several years longer than the Taylor rule. Importantly, optimal control calls for a later lift-off date even though this benchmark–unlike the simple policy rules–implicitly takes full account of the additional stimulus to real activity and inflation being provided over time by the Federal Reserve’s other policy tool, the past and projected changes to the size and maturity of its securities holdings.
Lord have mercy! Can she really think this can work? Is there any Fed model that caught 2008, 1998, 1987, or any other market moving event? This is the event horizon of the false precision black hole. But don’t worry, just throw a bunch of junk mortgages in a bucket, stir, and voila – AAA. It’s all right here in this spreadsheet.
The Bloomberg Commodity Index finished July down 12% YTD and 28% over the last 12 months. It is currently 60% off its highs in June 2008 (remember $150 oil?). Several large commodity funds closed in July. Does this asset class make sense? Our answer – absolutely YES – but commodities aren’t stocks so let’s stop benchmarking and investing in them the same way.
I just read a great book – The Simplicity Cycle by Dan Ward. It articulates wonderfully a philosophy that underpins everything we do here at Mount Lucas, something that we feel is incredibly important for investors to understand, and that investors in general are moving away from. The book isn’t finance based at all, a quick and easy read. The basic premise is summed up with the quote below:
“…humans gravitate towards complexity, in our technologies and religions, our laws and relationships, because simplicity is so often inadequate to our needs. We require a certain degree of complexity in our lives, just as we require a certain number of calories each day. Accordingly, we add layers, gizmos, features, functions, connections and rules to the things we create in an attempt to make them more exciting, more effective, or otherwise better. This preference, too, becomes a problem when it spirals out of control and produces industrial-strength concentrations of complexity that surpass our needs by multiple orders of magnitude….Simplicity is great and important, to be sure, but let me say it again: simplicity is not the point. What is the point? In a word, goodness…Simplicity matters because it affects goodness, but it turns out the relationship between simplicity and goodness does not follow a straight line. This means an increase in one does not always correspond with an increase in the other. Sometimes making things simpler is indeed an improvement. Sometimes not. Life is tricky that way”
Generally we aren’t ones to criticize the Fed – post crisis they have done an excellent job supporting a recovery through zero rates and unconventional measures, and have begun to step back without causing the panic and damage that was predicted. It’s an incredibly difficult job, with huge importance.
That said, our view is that the Fed has pretty much hit the mandate, the data supports that, and an end to zero rates is warranted soon. The drop in Q1 GDP looks increasingly like a quirk. In reading the dueling Fed blogs as to the cause of this drop (New York FED says winter and San Francisco FED says residual seasonality), we can’t help but think that either way, Q1 is not a true reflection of the economy now or going forward. Do you think productivity fell 3% in the first quarter? Although the Fed has consistently been too optimistic with GDP projections, it has also been too pessimistic on jobs. Only one of these is in their mandate. Put simply, the economy doesn’t feel like it needs the same rates as the depths of the crisis, particularly at a time when expansionary policies are starting to take hold elsewhere.
Regarding the price of retail products. Where are most of them made? China.
Import prices from China FELL 0.3% month over month and are down 1.3% YOY.
This speaks to the failure of the Philips curve framework to explain U.S. inflation swings. Inflation rose, 2010, with unemployment at 9%, as the China infrastructure boost lifted Chinese activity. Inflation is now quiescent with 5.5% unemployment, as China is in a bust.
I heard a quote from Howard Marks at Oaktree, who was explaining that managing risk should not be left to designated risk managers: “The bottom line for me is that risk management should be the responsibility of every participant in the investment process, applying experience, judgment and knowledge of the underlying investments.” We love our risk guy – he is a critical part of our team, but I like to think that this diverse approach applies to our firm as well. Everyone in the firm, and clients who want to, have access to our risk analytics. We are all thinking about the elements of the portfolio, how they interact and the relationships we may have overlooked. We also look for trends about how others think about risk. What follows are a few observations:
Since we have been in the business, and well before, sentiment measures have been used to gauge the popularity of trades –everyone of age remembers the MarketVane sheets. It is our sense that there is a more rapid convergence to consensus than ever before – that is, investors, in response to changing data, coalesce around a forward view very quickly. We hope to add some statistical meat to this idea over the next few months, but for the time being let’s begin with an anecdotal example. Continue reading