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Insider Talk:NuWave founder Troy Buckner sheds light on the recent experience in the grains market by using behavioral finance.

Wednesday, August 18, 2010

Wheat Market Illustrates Behavioral Patterns

Troy Buckner, founder of NuWave, sheds light on the connection between recent experience in the grains market and behavioral finance. He argues that managed futures models can benefit from a greater recognition of psychological factors.

For a profile of Mr. Buckner, see our April 8th issue. NuWave currently manages around $800 million.


"Very significant moves get corrected almost 100% of the time, even if the overall drift in a time series continues."

After Russia announced its ban on grain exports, wheat prices rose to peaks not seen in two years. Yet economic fundamentals had only changed on the margin and expectations of supply and demand were not dramatically altered. The price nearly doubled in a few weeks, but supply will be down maybe 6% to 7% from the previously expected level.

This is a dramatic example demonstrating that fundamentals alone do not explain market moves. We have to look to behavioral finance theory to understand what's going on.

Individuals reacting to information drive prices. Ultimately, human emotion is responsible for repetitive scenarios in the marketplace. The key emotions are pretty much summarized by a short list: fear, greed euphoria and despair. It does not so much matter what the catalyst is, these emotions cause repetitive patterns that can be seen in basic scenarios.

Why would anyone buy wheat at over $8 a bushel when it was around $4 just a few weeks back? A casual observer would probably argue that the commodity is not fairly valued at the high price. But suppose you are afraid of losing your job if you don't have enough wheat to manufacture your product, or maybe worse, that you can't feed your population. Then fear takes over and makes you do something that is contrary to the fundamentals in the marketplace.

From the outside perspective it may seem like market participants are irrational, but your decision to buy at the extremely high price is not irrational to you. After all, you're petrified that you might lose your livelihood! Several months from now, we can look back and decide that the response was overly emotional. But in early August, it seemed to dominate the market.

Various factors create price moves that would not be predicted on rational grounds. Here is another example. Last year a farmer had to sell his wheat at a very low price. Another year like that and he might not be able to stay in business. He was desperate to get at least a reasonable price. Early this year this farmer had information suggesting prices should be substantially higher. If he held out, he would get more value.

And yet his personal situation and emotions made make him accept the current price, counter to what he believed will likely happen in the market. He had to hedge his bet and could not wait for a higher price.

Gaining an Edge

Human beings change very little over time. That is why there are repetitive patterns in time series. The environment changes and many factors are in constant flux, but the human emotional makeup is essentially constant.

You might reply that we all know there are emotional factors at play in markets. That may be, but there is a significant amount of contextual information that is ignored by many strategies. A systematic trader might trade simply on a breakout, but that movement is only a small piece of a bigger picture. There is more information in time series.

In modeling time series of prices, we can identify similarities and differences between today's scenarios and historical scenarios. Knowing the previous scenarios, you understand better the current time series movements. A given move in a time series should not be viewed in isolation but relative to other scenarios that are similar or different.

What are the previous moves that this might be best compared to? To put the current price action into context, we need to know the precedents. That way, we can get an idea of the big picture that reflects the reactions of the human beings who drive the market.

At NuWave we analyze time series for clues as to what's behind the price moves and whether they will persist. How probable is the continuation of the price based on the patterns discernible in the time series? Ultimately we want to know whether there is high enough probability for the price to persist in a given direction in order to warrant risking capital.

It is not enough from a risk/reward standpoint to simply buy the momentum as it goes higher or sell the momentum as it goes lower. If you understand what's behind the reaction and the odds for the price to persist or change, then you have an edge.

In the markets we trade there are hardly any examples of dramatic moves that do not correct. Very significant moves get corrected almost 100% of the time, even if the overall drift in a time series continues. With wheat, our models suggest that the more likely possibility is a downward correction.

You have the question of whether to participate on the long-term trend while dramatic short term corrections may be going on. Such corrections can take several months. At NuWave we may see these situations as an opportunity to be tactically short even if we forecast an upward long-term trend.

The impact of emotions is not the same across markets. I believe equity markets are typically more efficient than commodity markets, because there are so many different types of participants in equities with a great deal of information. While there are still emotional responses, equity markets are relatively efficient.

By comparison, in commodity markets there are fewer players and therefore more potential for volatility. Further, the near-term risk associated with underestimating something like the food supply is arguably different than the risk of underestimating GDP. That's why dramatic price moves in a short period are far more common in commodities than in stocks. A few days' move of 10% or 15% is extraordinary in equities but commonplace in commodities.

To exploit market inefficiencies, NuWave's strategies are designed to study time series data in order to understand moves that are rational in the context of history and those that seem irrational. Either scenario offers opportunity.



 
This article was published in Opalesque Futures Intelligence.
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