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The Yale International Center for Finance conducts monthly surveys of individual and institutional investor’s confidence in the stock market. While there are other surveys available, the Yale Center provides a long term view of what investors may think about the markets.

The month began with some very promising trending opportunities, but with some choppy moves in both bonds and commodities, returns were generated by those who were nimble at position-sizing and getting out of losing trends before profits were completely given back to the market. This was a month where trend timing length mattered. Long-term trends ride through short-term choppiness. Short-term trend following is often able to profit and exit on reversals. A difficult problem is matching model to trend length and is often the reason for a diversity of timing models.

The equity markets again continued to march higher with strong gains in international and emerging markets. However, it should be noted that non-dollar equities were given a nice tailwind from the decline in the dollar, (take off 2-3+ percent). After the currency adjustments, there is less reason for large celebrations. What should be a concern is that the biggest moves were in large cap stocks with more modest returns for small cap and value indices. This should be expected on a dollar decline given the international nature of large-cap earnings, but lower breath is not a positive sign for follow-through with the trend.

The drumbeat of over-valuation continued in July, but investors do not seem to be listening to any negative stories as stocks around the world continued to move higher. The view that economic growth will pick-up in the second half of the year coupled with rosier earning forecasts have pushed equities higher. Any worry about valuation will be for tomorrow. Today, the focus is on buying risky assets around the world.

Here is a simple question that should have an easy answer. Name a universal set of asset classes that can be employed to categorize the investments for a large university endowment. The answer to this question may astound you. There is no agreement on the number of asset classes an endowment should have in order to make asset allocation decisions. That’s right, the largest university endowments cannot agree on this basic number for how to categorize investments. See the paper, “The evolution of asset classes: Lessons from university endowments”, Journal of Investment Consulting Vol 17, no 2, 2016.

Investors have had an aversion to using models, but that may be changing rapidly. More money is being managed by systematic managers or focused on some form of smart beta or a set of rules to investing. Nevertheless, there has been documented fear from letting go and having a model make decisions.

There is a well know cognitive bias called the Dunning-Kruger effect whereby individuals who perceive themselves as experts will have the illusion of superiority concerning their cognitive abilities. They believe their own talk. They are experts, right?

When I hear about diversification across funds or strategies, I, like most investors, will immediately focus on the correlation matrix versus other alternatives and asset classes. However, investors should be thinking beyond the simple historical numbers and focus on forward expectations for correlations. There should be views of how diversification may change through time or behave under different scenarios. To form diversification or correlation forecasts, investors should have a classification scheme for diversification. All diversification is not alike and a classification scheme may help with determining how correlation may move.

Investors are looking closely at the fees being charged, but the hidden fee of liquidity may be the most significant cost that is often not talked about. Large firms that are charging less may have higher costs associated with liquidity than small firms. As the size of the firm grows, the cost of entering and exiting may be higher. Additionally, some markets that may offer opportunities are avoided because the cost of trading when liquidity is lower is higher.

Automated execution is taking over futures markets. Actually, the battle is over. Voice (non-electronic) and manual execution are reserved for illiquid products, old school firms, smaller traders, those who may be undertaking spreads, complex legged or option strategies, roll strategies, and some block trade. However, the use of electronic trading can vary by market and sector. Technically, we are referring to manual (MAN) versus automated (ATS) trade execution where automated is generated and/or routed without human intervention. Non-electronic would be a separate category. By far, automated to automated trades dominate most markets even in many commodities. The high frequency automated traders are the new market scalpers. Financials have a higher percentage of automated trading over commodity markets.

What kind of month was June for CTA’s? Well, you can look at the distribution plot of returns for the month to get an idea of the extremes. We created the QQ plot for the 377 firms that reported to the IASG database for June as of last week. This can be done for smaller more specialized samples, but we took the maximum set of data reported to IASG.