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Algorithmic trading and liquidity: Long term evidence from Austria

Roland Mestel (), Michael Murg and Erik Theissen ()

Finance Research Letters, 2018, vol. 26, issue C, 198-203

Abstract: We analyze the relation between algorithmic trading and liquidity using a novel data set from the Austrian equity market. Our sample covers almost 4.5 years, it identifies the market share of algorithmic trading at the stock-day level, and it comes from a market that has hitherto not been analyzed. We address the endogeneity problem using an instrumental variables approach. Our results indicate that an increase in the market share of algorithmic trading causes a reduction in quoted and effective spreads while quoted depth and price impacts are unaffected. They are consistent with algorithmic traders on average acting as market makers.

Keywords: Algorithmic trading; Austrian stock market; Market liquidity (search for similar items in EconPapers)
JEL-codes: G10 C58 (search for similar items in EconPapers)
Date: 2018
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