Regression Analysis
Regression analysis is a way of measuring the relationship between two or more sets of data. An economist might want to know how the supply of wheat affects wheat prices, or the relationship among gold, inflation, and the value of the U.S. dollar. A hedger or arbitrageur could use the relationship between two related products. such as palm oil and soybean oil, to select the cheaper product or to profit from the difference. or you can find the pattern that binds the Producer Price Index to interest rates. Regression analysis involves statistical measurements that determine the type of relationship that exists between the data studied. Many of the concepts are important in technical analysis and should be understood by all technicians, even if they are not used frequently.
Regression analysis is often applied separately to the basic components of a time series, that is, the trend, seasonal (or secular trend), and cyclic elements- These three factors are present in all price data. The part of the data that cannot be explained by these three elements is considered random, or unaccountable.
Trends are the basis of many trading systems. Long-term trends can be related to economic factors, such as inflation or shifts in the value of the U.S. dollar due to the balance of trade or changing interest rates. The reasons for the existence of short-term trends are not always clear. A sharp decline in oil supply would quickly send prices soaring, and a Soviet wheat embargo would force grain prices into a decline; however, trends that exist over periods of a few days cannot always be related to economic factors but may be strictly behavioral.
Major fluctuations about the long-term trend are attributed to cycles. Both business and industrial cycles respond slowly to changes in supply and demand. The decision to close a factory or shift to a new crop cannot be made immediately, nor can the decision be easily changed once it is made. Stimulating economic growth by lowering interest rates is not a cure that works overnight. Opening a new mine, finding crude oil deposits. or building an additional soybean processing plant makes the response to increased demand slower than the act of cutting back on production. Moreover, once the investment has been made. business is not inclined to stop production, even at returns below production costs.
The random element of price movement is a composite of everything unexplainable. In later sections ARIMA, or Box-Jenkins methods, will be used to find shorter trends and cycles that may exist in these leftover data.