The liquidity of energy stocks

This study investigates the dynamics of stock market liquidity in the energy industry in the US for 130 firms for the period 2006–2011. We use a (structural) vector autoregression approach to model the simultaneous relationships between three liquidity measures, namely turnover, price impact and spread. In addition, we account for oil prices in this model. The liquidity measures exhibit a persistent (highly autocorrelated) pattern. The intensity of trading appears to be relevant for the interrelationships of the liquidity measures. Stocks that are traded more often seem to be less sensitive to changes in liquidity. The main contribution of this study is that we introduce and test a specific causality pattern between trading activity, price impact, and spreads of energy stocks. This causality pattern is stronger during illiquid periods, which makes these periods much more risky.