Algorithmic and high-frequency trading in Borsa Istanbul

Abstract

AbstractThis paper investigates the levels of algorithmic trading (AT) and high-frequency trading (HFT) in an emerging market, Borsa Istanbul (BIST), utilizing a dataset of 354 trading days between January 2013 and May 2014. We find an upward trend in AT by using common proxies: number of messages per minute and algo_trad of Hendershott et al. (2011). Mean algo_trad for BIST 100 index constituents varies between −18 and −13 which is parallel to 2003–2005 levels of NASDAQ large cap stocks. Initially, we measure HFT involvement by detecting linked messages as in the way proposed in Hasbrouck and Saar (2013). Next, we propose an extended HFT measure which captures various HFT strategies. This measure attributes approximately 6% of the orders to HFT. HFT involvement is higher in large orders (11.96%), in orders submitted by portfolio/fund management firms (10.40%), after improvement of BIST's order submission platform and tick size reduction for certain stocks.