Changing as Markets Change

I had the chance to listen to a prominent MIT finance professor talk about how market participants make their decisions, and I came away thinking that his big-brain ideas validate the approach that we’ve been using for years.

Andrew Lo, the MIT professor, has developed what he calls the “adaptive markets hypothesis” (AMH) as a more sophisticated framework than the long-standing “efficient markets hypothesis” (EMH).

I won’t go into a lot of detail, but the EMH assumes that all market participants act rationally at all times, and that all available information is immediately reflected in market prices.

Lo’s AMH, market participants are not always perfectly rational, he says – they often make bad decisions. They learn from those bad decisions and, driven by competition, the survivors constantly innovate. Those who don’t adapt don’t last.

U.S. Global, we have long viewed markets as “complex adaptive systems”—they are made up of many moving parts that are interconnected across a global network, and they learn from experiences and change accordingly.

In our case, we use a matrix of top-down macro models and bottom-up micro stock selection models to determine weighting in countries, sectors and individual securities. We believe government policies are a precursor to change, and as a result, we keep tabs on the fiscal and monetary policies of the G-7 and what we call the “E-7” -- the world’s developing nations by population.

Also focus on historical and socioeconomic cycles, and we apply both statistical and fundamental models to identify companies with superior growth and value metrics. We overlay these explicit knowledge models with the tacit knowledge obtained by domestic and global travel for first-hand observation of local and geopolitical conditions, as well as specific companies and projects.

During his San Antonio visit, Lo contrasted “fear and greed” with “rational thinking” – the former being reactive and emotional, while the latter is measured and opportunistic. We use oscillators, like the one above showing gold and the dollar, to help us determine when fear or greed may be taking hold in a market.

As a big believer in globalization, urbanization and major technological breakthroughs as key drivers of change in the world. These factors have an enormous impact on infrastructure creation around the world, which in turn greatly affects commodities demand.

In the early 1970s, when gold resumed free-trading status in the U.S., China and India were both inward-looking and had very small economic footprints – now their economic engines are lifting tens of millions of people into middle-class prosperity each year.

I'd be a bum on the street with a tin cup if the markets were always efficient,” Warren Buffett once said. In other words, opportunities come to those (like us) who are able to navigate increasingly complex markets. Standard deviation is a measure of the dispersion of a set of data from its mean. The more spread apart the data, the higher the deviation. Standard deviation is also known as historical volatility.

This is a syndicated post. Read the original here.