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It is a risk-on world with global equities (EFA) and emerging markets (EEM) now posting double digit gains for the year. A first round French election that was pointed less in the direction of Le Pen and a Trump presidency that does not seem as extreme as some pundits suggested has been coupled with global economic growth that is stronger than expected. The deflation trade may be further tempered in the US, but the threat of trade wars has diminished and the world economy is more focused on reality than dire economic scenarios.

There are many narratives for why equities or bonds will move higher, but a recurring theme is the financial conditions faced by investors. Financial conditions provide the tailwinds or headwinds to push asset class returns. These conditions tell us something about whether we will be transitioning between a risk-on and risk-off environment or whether we will be a crisis mode.

How do you know whether a model is broken? Or, how do you conduct a model review? There are many specific steps for any review but there are four major questions that have to be addressed that are separate from risk management. The key question of model efficacy should focus on forecasting skill and action. Does the model forecast correctly and is the model employed properly to make good decisions.

Globalization is a critical part of macro investing. There can be talk of separation politics, but for investors, you have to focus on the global economic cycle because the world is highly integrated. What is very interesting is that globalization has been fairly stable between the current environment and the Bretton Woods period as discussed by the recent work of Eric Monnet and Damien Puy who studied long horizon data available from the IMF. They find that there were two common shock periods which caused a highly synchronous global behavior. The first was oil shock period of the 70’s and the second was the Great Financial Crisis. You could say that these were the two periods when “correlations went to one” across asset classes. There was no international diversification benefit.

A growing stream of thinking in microeconomics is the concept of “winner-take-all” dynamics. The idea seems simple. A combination of networking economics and classic economies of scale creates situations where there are just a few dominant firms or economic agents who are able to capture significant market share in a given industry. With the advances in technology over the last decade, many industries are seeing the impact of winner-take-all dynamics leading to the result of greater concentration.

March saw a significant rotation in return performance from US equities to global and emerging markets and from value to growth. Our indicators show prices are starting to break to the downside albeit trends are currently flat. March was a transition month from euphoria to reality concerning US government policies. Future price direction will be determined by the real economy and not policy expectations.

Any managed futures trader will tell you that trading metals on the LME is much more difficult than other “futures” contracts. Structural differences make for a more challenging environment from monitoring and capital usage to transaction costs. The continuous forward contracts of the LME are just more difficult to trade than the focused discrete delivery dates of futures because market liquidity is spread over a wider set of dates. Even if liquidity is centered at a three month prompt, the liquidity on exit before expiration may be more difficult to find.

The capital flows and returns for the month and quarter tell a risk-on story for global markets. This is not the case for the US where equity returns were at best flat and bonds showed negative returns in March. The dollar sold off for the month by slightly less than one percent as measured by the DXY dollar index. Even if we account for the dollar tailwind for international stocks, global equities did better than the US by well over 2% for March. Emerging markets have seen the best quarter in years with double-digit returns. Adjusting for the dollar would have placed international and emerging market bonds in-line with US bond returns.

For most managed futures managers, the modeling task is simple, look for trends or break-outs. Managers are not predictive but reactive to what market prices are doing. Looking at the current price data across the major sectors provide little evidence of strong trends or break-outs. Trends that seem to be currently developing are not strong enough to move beyond recent highs, so our trend sector matrix is showing sideways to a slight up moves across most sectors with the only strong trends in commodity markets.

One of the leading experts on forecasting is J Scott Armstrong, from the Wharton School. He has produced numerous papers and books on forecasting but has encapsulated all of his decades of thinking with his paper, The Golden Rule of Forecasting. There is a right and a wrong way to do forecasting and Armstrong walks through the key issues, whether it is through an econometric model or a judgmental forecast. His golden insight is that when in doubt be conservative. More deeply, his comment is that the forecaster must seek out and use all knowledge relevant to the problem, including knowledge of methods validated for the situation.


A recent FT article, “Rise in the new form of ‘portfolio insurance’ sparks fear – Popularity of trend-following funds – and their promises – carry echoes for some of 1987 crash” focused on the threat of trend-following to create selling pressure on equity markets. This speculative topic has been a recurring theme for decades and has been extensively researched. The empirical question is very straight forward. Do futures prices lead cash prices and are futures prices driven by systematic trend-followers? That is, is there a positive feedback loop whereby the selling of equity futures by some strategies will lead to more selling and a price crash? The research on the impact of speculators has generally shown that this is not an issue.

Approaches to modeling go through fads and fashions. What was learned yesterday by MBA’s will be the model of choice tomorrow. Certain approaches are employed because that is the approach the modeler wants or likes. The same applies to strategies. A value investor will not likely to turn into a growth investor. He likes that sort of thing. A quant will not become a discretionary storyteller. He likes the precision of the model.