Wavelet-based evidence of the impact of oil prices on stock returns

Abstract

We examine the relationship between oil and stock markets in Europe and the USA at the aggregate and sectoral levels using wavelet multi-resolution analysis. Wavelet decomposition of the original time series is useful in characterizing the oil–stock price relationship at different time scales, in revealing contagion and interdependence between oil and stock prices (as in the recent global financial crisis) and in analysing oil lead and lag effects on stock prices through wavelet cross-correlation. Empirical evidence for the period June 2000 to July 2011 indicates that oil price changes had no effect on stock market returns in the pre-crisis period at either the aggregate or sectoral level (with the exception of oil and gas company stock). At both levels, however, with the onset of the financial crisis we found evidence of contagion and positive interdependence between these markets. Additionally, we found no evidence of lead and lag effects in the pre-crisis period, and so reject the underreaction hypothesis. Since the onset of the financial crisis, oil price leads stock prices and vice versa for higher frequencies, whereas for lower frequencies oil and stock prices lead each other in a complex way.