Herif/Dude”: Personifying High-Frequency Trading in an Emerging Stock Market


Karakaya M. F.

Europe and Beyond: Boundaries, Barriers and Belonging, Manchester, Birleşik Krallık, 20 - 23 Ağustos 2019, ss.211

  • Yayın Türü: Bildiri / Özet Bildiri
  • Basıldığı Şehir: Manchester
  • Basıldığı Ülke: Birleşik Krallık
  • Sayfa Sayıları: ss.211
  • İstanbul Üniversitesi Adresli: Evet

Özet

In the Turkish stock market, Borsa Istanbul (BIST), from time to time since February 2016, a mysterious trader has beenmaking the market. As this mysterious trader acted like “a giant bull in the china shop” and doubled the daily volume ofthe market, it attracted the attention of all relevant parties in the BIST. The Turkish observers named this mysterious traderas “Herif (the guy)” while non-Turkish observers coined theterm “Dude.” After a growing “guess who game” on theidentity of this mysterious trader, the broker firm revealed that it was actually an automated computer-based high-speed trading technology (so-called high-frequency trader (HFT))acting in the market. Yet, the name “herif/dude” has prevailed.In an environment as the stock exchange that, in Simmelean sense, is supposed to be the most clear and emphatic expression of the flexibility and anonymity of money, an automated trading tool executing selling/buying orders according to certain algorithms was personified. In spite of the fact that the sociological enquiries on the transformation of stock markets from trading pits to click/screen trade (Baker, Abolafia, and Zaloom) and to the HFT (by MacKenzie, Knorr- Cetina, Preda, Lange, and Borch) provide an alternative track that diverge from a purely anonymous, de-personified andobjective stock market, “Herif/Dude” case provides a real story that points a sociological understanding of HFT in an emergentstock market. This study analyzes “Herif/Dude” case in termsof post-social relationship, (de)personification, anonymity, subjectivity, masculinity, mundane politics of emergent financial markets, and the (new) role of brokers and traders based on the data derived from in-depth interviews with the relevant parties of BIST.