دانلود رایگان مقاله انگلیسی پیش برندگان الگوهای بازده فصلی در بورس آلمان - اشپرینگر 2018

Abstract

Using a data set of German stocks that includes the financial crisis, this paper identifies market liquidity as the main driver of return seasonality. In comparison, the economic significance of order flow imbalance is markedly weaker. Applying panel regressions and controlling for unobserved effects, we investigate the effects of both variables simultaneously, together with dummies for calendar effects. US macroeconomic news announcements, which have been identified as one driver of return seasonality in previous studies using non-US data, are of little importance for our data set of German stocks.

Conclusions and directions for further research

This paper sheds light on the drivers behind seasonality in German stock returns. Using a fixed-effects panel regression methodology, we analyzed liquidity and order imbalance simultaneously as potential explanatory factors. We found that market liquidity has the strongest influence on return patterns: Although we use daily data (as opposed to intra-day data), we find that the variation in bid-ask spreads and the Amihud (2002) ratio accounts for a sizeable proportion of return seasonality. Thus, liquidity seems to be a major driver behind calendar effects at the level of individual stocks. Future research should look more deeply into this relationship for intra-day data as the link may be even more pronounced there. Market liquidity considerations could also be the reason why the TOM effect recently has moved to earlier days, a finding from the recent literature that was confirmed in this paper. By contrast, a shift in return patterns cannot be explained by fixed-date macroeconomic news, which cluster in the first third of a month. Accordingly, we do not find evidence that US macroeconomic news announcements drive return patterns on a broader scale. Its relation to liquidity dynamics may also explain why order flow is considered a seasonality driver. While most previous studies have focused on flow considerations of select investor groups, this paper analyzes order flow imbalances in aggregate, taking into account orders from all investors active in the market.