Abstract
Regulators continue to debate whether high-frequency trading (HFT) is beneficial to market quality. Using Strongly Typed Genetic Programming (STGP) trading algorithm, we develop several artificial stock markets populated with HFT scalpers and strategic informed traders. We simulate real-life trading in the millisecond time frame by applying STGP to real-time and historical data from Apple, Exxon Mobil, and Google. We observe that HFT scalpers front-run the order flow, resulting in damage to market quality and long-term investors. To mitigate these negative implications, we propose batch auctions every 30 milliseconds of trading.
| Original language | English |
|---|---|
| Pages (from-to) | 363-402 |
| Number of pages | 40 |
| Journal | The Financial Review |
| Volume | 51 |
| Issue number | 3 |
| Early online date | 13 Jul 2016 |
| DOIs | |
| Publication status | Published - 1 Aug 2016 |
Keywords
- G10
- G12
- G14
- G15
- G18
- G19
- G20
- G23
- G28
- G29
- algorithmic trading
- evolutionary algorithms
- genetic programming
- high-frequency trading
- market efficiency
- market regulation
