- September 2017
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- We empirically investigate the short-run impact of anticipated and unanticipated unemployment rates on stock prices. We particularly examine the nonlinearity in the stock market's reaction to the unemployment rate and study the effect at each individual point (quantile) of the stock return distribution. Using nonparametric Granger causality and quantile regression-based tests, we find that only anticipated unemployment rate has a strong impact on stock prices. Quantile regression analysis shows that the causal effects of anticipated unemployment rate on stock returns are usually heterogeneous across quantiles. For the quantile range 0.35, 0.80, an increase in the anticipated unemployment rate leads to an increase in stock market prices. For other quantiles, the impact is generally statistically insignificant. Thus, an increase in the anticipated unemployment rate is, in general, good news for stock prices. Finally, we offer a reasonable explanation for the reason, and manner in which, the unemployment rate affects stock market prices. Using the Fisher and Phillips curve equations, we show that a high unemployment rate is followed by monetary policy action of the Federal Reserve (Fed). When the unemployment rate is high, the Fed decreases the interest rate, which in turn increases the stock market prices.
- stock market returns; anticipated unemployment; unanticipated unemployment; nonparametric tests; conditional independence; granger causality in distribution; granger causality in quantile; local bootstrap; monetary policy; federal funds rate