For the 20-year period ending in 2007, the Los Angeles Lakers’ N.B.A. championship record did a surprisingly good job of reflecting the stock market. When the Lakers won, the market usually fell; the market rose when they lost. Between 1987 and 2007, this “indicator” was wrong only three times. As Ed Carson writes: “An investor who put down $1,000 into the Nasdaq at the start of 1987 and stayed fully invested through 2007 would have ended up with $7,604. But an investor who bought the Nasdaq in years the Lakers lost and stayed in cash when the Lakers won would have finished with $21,189.” Thankfully, Carson points out that the “Laker Indicator” is a perfect illustration of the dangers of assuming causality where only correlation exists: “But what if instead of the Lakers, we substituted put-call ratio or a bulls-vs.-bears indicator. A 20-year stellar track investing record like the Laker indicator would sound like a sure thing.” [%comments]
Are the Lakers a Sure Thing?
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End the recession: Shut Down the Lakers
I’m pretty excited to see the impact of the disastrous financial crisis on the efficient market hypothesis of Fama’s theory and its assumptions.
While the outperformance is actually somewhat larger, with a calendar year.
forget indirect speculation- the lakers are killing against the spread this year- so kobe really is money- a word of caution tho- the celtics are getting abjectly hosed this year against the spread
That’s like the fact that the Yankees only win the world series with democrats in the white house:
41,43: Roosevelt
47,49-53: Truman
61,62: Kennedy
77,78: Carter
96-00: Clinton
09: Obama
Coincidence is a part of correlation
Correlation just an measurement of “When ‘A’ happened, how often did ‘B’ happen”. It is based on past event only, there is no relationship suggested between A and B, and it has no predictive value by itself
When statisticians speak of “correlation vs. causation,” the idea is that two variables are proven to be associated, but only in the latter case can one variable be seen as causative to the other.
In the former there is a definite relationship established.
In the case of coincidence – or perhaps a better word is ‘happenstance’ – the fact that two variables share a pattern is a random set of events and no proof exists of any clear relationship.
This article is a good “correlation vs. causation” example, but it could be embedded with a cautionary “data mining is stupid” lesson as well. What’s a story of a franchise with such a history that turned dramatically the other way after some period of time?
Since the championship is mid year, its equally true that bull markets cause the Lakers to win, and bear markets cause them to lose.