Evidence of the Distortive Effects of Government Policies on Financial Markets

Howard Simons at the Minyanville explains, (bold emphasis mine)

The Chicago Federal Reserve produces a personal consumption & housing (PCH) index dating back to March 1967; it has declined every month since January 2007. The duration and extent of this decline, 52 months and counting, is unprecedented in the series and most likely is the longest and deepest downturn since the Great Depression.

Note, however, what its relationship to the S&P 500’s year-over-year changes has been. It used to be the stock market led the PCH index by about three months. More important than the lead-time was the congruence of direction: If the stock market rose, so did the PCH and vice-versa.

What happened after QE1 began? Let’s run a simple in-sample regression model with the PCH index as a function of the S&P 500’s year-over-year changes lagged three months over the June 1967 – February 2009 period and save the coefficients. The fitted values of that model are shown in red below. If we then apply those coefficients to the March 2009-forward out-of-sample period, we see the fitted values in green. They are, starting one year after the 2009 rally began, much higher than the actual PCH index in blue. For example, the actual value of the PCH index at the end of April was -0.39; the out-of-sample fitted value was 0.04.

This is equivalent to saying the change in policy produced a change in financial markets without producing a change in the underlying real economy. There is your circus; you are on your own for the bread part of the deal.

This shows of the distortive effects of government policies on financial markets.

Also this represents additional evidence where markets today don’t accurately signal the actual balance of demand and supply.

Government policies have been major (if not the primary) factors in determining asset values.

It also shows that government can rig the game to benefit specific interests (banking sector over the real economy)

Finally, that the correlation-causation dynamics can change depending on the underlying forces, which in this case has been government interference.

So looking solely at correlation would signify as a dicey and tenuous way to analyze events unless one understands the likely (causal) drivers behind the market's actions.