High-frequency trading, HFH (high frequency trading, HFT, flash trading)
Buy and sell orders on the stock exchange triggered in milliseconds by appropriately programmed computers. The program used for this purpose is called an arbitrage trading program, APT; some people also call such computer programs robot traders. High-frequency trading can cause and amplify extreme price movements on the markets. On May 6, 2010, for example, a so-called flash crash occurred on the New York Stock Exchange, triggered by errors in APTs. Within minutes, individual stocks lost half or more of their value. Such price drops can cause great difficulties for companies that are dependent on capital injections. – A good ninety percent of the orders placed by high-frequency traders are quickly deleted again without being executed; this is known as quote stuffing tactics. The resulting very high cancellation rate leads to a large discrepancy between the indicated liquidity of the market and the actual trading volume. In order to hinder this rapid arbitrage, there are various proposals. For example, a high-frequency trader should be required to keep open for a certain period of time prices at which he wants to buy or sell, once they have been entered into the system. Limiting the turnover of flash trades on the respective exchange has also been considered. – However, until uniform supervisory rules are introduced worldwide and the migration of trades to platforms outside the stock exchanges is prohibited, it is unlikely that high-frequency trading can be tackled. It is important to know that in the spring of 2011, the share of turnover via HFH on the stock exchange in New York was around seventy percent and already over forty percent on the German stock exchanges. At the same time, HFH turnover on foreign exchange markets worldwide was close to fifty percent. – The basic criticism of the HFH is aimed at the fact that the market normally adjusts the price of an asset promptly to fundamental changes in its value. However, it is not clear how HFT algorithms, whose decisions are based only on order book entries (order books) in the last few seconds, can serve this goal of price adjustment. A block trade of 10,000 shares between two large investors certainly leads to real price discovery in the market. The lightning-fast back and forth trading of 100 shares between two HFT algorithms, on the other hand, does not contribute to price discovery and market efficiency according to the principles of economic reason, and thus to the social task of the market to allocate scarce resources to the best host. – See algorithm trading, bid-ask spread, foreign exchange trading, computerized, ghost hour, index arbitrage, quote-stuffing tactics, up-tick rule. – See BaFin Annual Report 2010, pp. 69 f. (regulation of HFT), Financial Stability Report 2011, pp. 76 f. (HFH is taking an increasingly significant share of exchanges; risk of liquidity drying up abruptly in unfavorable market conditions; plans to regulate HFH), BaFin Annual Report 2011, pp. 90 f. (report on high-frequency trading; ESMA guidelines), BaFin’s 2012 Annual Report, p. 64 (regulatory efforts at the global level), BaFin’s 2013 Annual Report, p. 35 f. (requirement to obtain a license under the High-Frequency Trading Act of May 2013), and the respective BaFin Annual Report, chapter “International Affairs.”
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University Professor Dr. Gerhard Merk, Dipl.rer.pol., Dipl.rer.oec.
Professor Dr. Eckehard Krah, Dipl.rer.pol.
E-mail address: info@ekrah.com
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