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V.8:4 (127-131): Playing copper by Eric L. Sharp
V.8:4 (127-131): Playing copper by Eric L. Sharp
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Playing copper by Eric L. Sharp
Perhaps the best way to succeed in futures trading is to pick up early on major trends and stay with them for all they're worth. Copper went into a major bull market in early 1987, almost tripling in value from the start to the high. Here are two techniques that helped in interpreting and staying with the copper trend. None of these methods is practical without a computer and adequate software, because too much data and number crunching are involved to do it by hand.
Statistical analysis is one method by which trends can be interpreted and predicted. Markets oscillate over time around values affected by changing conditions such as inflation, interest rates, supply levels and demand and exchange rates. Prices may be influenced by such factors. Typically, however, the most important influences are represented by a short list. Sorting out which are the key factors can be approached with a statistical method called correlation analysis, a method by which the strength and nature of a relationship between two variables can be quantitatively established. In correlation analysis, the first step is to decide which variables may be important in determining the price of a particular item and then obtain the relevant data over a suitable time period.
Data can be in daily, weekly, monthly or quarterly form, but in practice, monthly averages are usually best. They appear to be the most favorable trade-off between avoiding meaningless volatility and providing timely information.
Perhaps the best way to succeed in futures trading is to pick up early on major trends and stay with them for all they're worth. Copper went into a major bull market in early 1987, almost tripling in value from the start to the high. Here are two techniques that helped in interpreting and staying with the copper trend. None of these methods is practical without a computer and adequate software, because too much data and number crunching are involved to do it by hand.
Statistical analysis is one method by which trends can be interpreted and predicted. Markets oscillate over time around values affected by changing conditions such as inflation, interest rates, supply levels and demand and exchange rates. Prices may be influenced by such factors. Typically, however, the most important influences are represented by a short list. Sorting out which are the key factors can be approached with a statistical method called correlation analysis, a method by which the strength and nature of a relationship between two variables can be quantitatively established. In correlation analysis, the first step is to decide which variables may be important in determining the price of a particular item and then obtain the relevant data over a suitable time period.
Data can be in daily, weekly, monthly or quarterly form, but in practice, monthly averages are usually best. They appear to be the most favorable trade-off between avoiding meaningless volatility and providing timely information.
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