is a way of determining any relationship between two seperate entities
(e.g a price and a particular indicator. The result of this analysis
shows if changes in the first entity coincide with changes in the
second entity. The first item is known as the 'independent' entity,
and the trick is to see whether changes in it affect the 'dependent'
(second) entity (usually price). The results are usually called
a 'correlation coefficient' and vary between plus one and minus
one. A coefficient of +1.0, is a 'perfect positive correlation'
- changes in the independent entity result in an exact change in
the dependent entity. A coefficient of -1.0, is a "perfect negative
correlation," and mean that changes in the independent entity cause
an identical change in the dependent entity, but in the opposite
direction. A coefficient of zero implies no relationship between
the two entities. Low correlation coefficients (less than 0.1) suggests
the relationship is weak or non-existent. High correlation coefficients
(over 0.9) indicates that the dependent entity is likely to react
predicably to changes in the independent entity. In day trading
schools, this technique is often used to try and limit the risk
by making simultaneous 'bets' on two strongly correllated entities
that have an inverse relationship. A common use for this technique
is to coompare 2 securites or indices (e.g. the DOW and the FTSE)
to see if any useful reliable relationship exists that can be exploited.
This forms the basis of 'pairs trading'.