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Futures and Options

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Elaine Kub, DTN grains analyst
Elaine Kub, DTN grains analyst
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Not Fundamental, but Not Technical Either

According to the commodity market fundamentals we were all accustomed to, traditional traders make buying and selling decisions based on what they figured to be a "fair" price for a given commodity.


According to the commodity market fundamentals we were all accustomed to, traditional traders make buying and selling decisions based on what they figured to be a "fair" price for a given commodity. For traders using arbitrage algorithms, a computerized system will calculate its idea of a fair price based on a number of predetermined input factors. Based on the algorithm's computed information, traders then set the computerized system to buy or sell futures depending on whether the market is over or under priced - according to the system's estimates. The important caveat is selecting the proper market inputs when creating these algorithms to ensure profitability. However, commodity markets today are no longer operating under the same market fundamentals. Traders still using technical algorithms with previously selected inputs based on traditional market fundamentals are now at risk.

Today, there is an exponentially larger amount of speculative traders with a different type of mentality buying and selling futures. These traders do not care about "fair" prices and will not take market fundamentals into account when deciding to buy or sell. Speculative traders are investing to capitalize on the shear profit potential that any given market might offer. Accounting for the majority of erratic swings in the daily commodity pricing, speculative traders are driving the continued bullish trends that are setting record-high commodity prices. In March alone, a staggering 12 commodity markets - including corn, soybeans, silver, crude oil, wheat and gold - each traded at all-time highs.

Because speculative traders are only concerned with making money on a trend, many of the traditional fundamentals no longer apply. One notable example is resistance points. Built into most algorithms, these resistance points (or target prices) act as logical barriers to keep the market in check. These are generally round numbers, for example $5 corn or $100 crude oil. With so many commodity markets trading at record highs, there has been little evidence to support that these resistance points have any affect on speculative investors' trading habits. Having no clear overhead resistance points creates a significant amount of risk for technical algorithms that take a short position (selling with hopes to buy back at a lower price) as easy as it might a long position (buying with hopes to sell at a higher price). It would be hard to justify taking a short position during a time when there seems to be limitless upward potential.

Traders that rely on algorithms designed to capitalize on inter-market arbitrage opportunities also are at risk. These algorithms will buy or sell a commodity based on the idea the market is over or under priced in comparison to a different market. Previously, the markets were in a position where certain commodities would move in correlation with each other. For example, in the past as the soybean markets rose in price the closely correlated Malaysian palm oil market also showed gains. Today, the large number of speculative traders is far more willing to allow these historic price ratios to fall out of line. In addition, these traders do not expect or care if prices revert back to their historic means. Although it might appear that some inter-market relationships remain intact, this illusion is created by the fact that all markets are moving in upward trends. It is not because the historic price ratios are being taken into account by traders. Relying too closely on an algorithm that does not understand this difference in the markets can prove to be costly.

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