V.18:7 (58-62):Commodities And The Inflation Rate by Alex Saitta
Product Description
Commodities
And The
Inflation Rate by Alex Saitta
Which individual commodities have the strongest coincidental relationship with the inflation rate?
Successful traders need to keep an eye on commodity price changes to gain insight into the latest changes in the inflation rate and anticipate the next bond market move. You cannot rely on the monthly Consumer Price Index (CPI) report, since there is a considerable lag between the period when the data is collected and the date the report is released to the public. By the time you get it, it's too late.
Here’s a technique to identify the commodities that display the strongest coincidental relationship with the inflation rate. This eliminates the need to watch all commodities markets and allows you to focus on those that are significant.
STUDY
I used correlation analysis to study the strength of the relationship between commodities and inflation. I selected 16 widely traded commodity futures markets that update in real time and are widely available to traders. Correlation analysis measures how well two variables move together over time, and it results in the formation of a statistic referred to as the correlation coefficient. The coefficient ranges from -1.0 to +1.0 and identifies the direction as well as the strength of a relationship between the two variables.
A coefficient of +1.0 marks a perfect positive relationship. This means that when one variable rises, the other rises in lockstep. When one falls, the other falls in lockstep. A coefficient between zero and +1.0 is a nonperfect positive relationship. When one variable rises, usually the other rises. When one falls, typically the other falls. When the coefficient is less than zero, a negative or inverse relationship exists. A coefficient of zero indicates there is no relationship at all between the two variables, so when one variable changes, it is equally likely the other variable will rise or fall. (For a detailed discussion of the calculation of the correlation coefficient, see sidebar, "Correlation coefficient calculation.")
Which individual commodities have the strongest coincidental relationship with the inflation rate?
Successful traders need to keep an eye on commodity price changes to gain insight into the latest changes in the inflation rate and anticipate the next bond market move. You cannot rely on the monthly Consumer Price Index (CPI) report, since there is a considerable lag between the period when the data is collected and the date the report is released to the public. By the time you get it, it's too late.
Here’s a technique to identify the commodities that display the strongest coincidental relationship with the inflation rate. This eliminates the need to watch all commodities markets and allows you to focus on those that are significant.
STUDY
I used correlation analysis to study the strength of the relationship between commodities and inflation. I selected 16 widely traded commodity futures markets that update in real time and are widely available to traders. Correlation analysis measures how well two variables move together over time, and it results in the formation of a statistic referred to as the correlation coefficient. The coefficient ranges from -1.0 to +1.0 and identifies the direction as well as the strength of a relationship between the two variables.
A coefficient of +1.0 marks a perfect positive relationship. This means that when one variable rises, the other rises in lockstep. When one falls, the other falls in lockstep. A coefficient between zero and +1.0 is a nonperfect positive relationship. When one variable rises, usually the other rises. When one falls, typically the other falls. When the coefficient is less than zero, a negative or inverse relationship exists. A coefficient of zero indicates there is no relationship at all between the two variables, so when one variable changes, it is equally likely the other variable will rise or fall. (For a detailed discussion of the calculation of the correlation coefficient, see sidebar, "Correlation coefficient calculation.")
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