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The rise of the machines in commodities markets: new evidence obtained using Strongly Typed Genetic Programming
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| Journal | Annals of Operations Research |
|---|---|
| Date | E-pub ahead of print - 25 Aug 2016 |
| Date | Published (current) - 1 Jan 2018 |
| Issue number | 1-2 |
| Volume | 260 |
| Number of pages | 32 |
| Pages (from-to) | 321-352 |
| Early online date | 25/08/16 |
| Original language | English |
Abstract
Market regulators around the world are still debating whether or not high-frequency trading (HFT) is beneficial or harmful to market quality. We develop artificial commodities market populated with HFT scalpers and traditional commodities traders using Strongly Typed Genetic Programming (STGP) trading algorithm. We simulate real-life commodities trading at the millisecond timeframe by applying STGP to the S&P GSCI data stamped at the millisecond interval. We observe that HFT scalpers anticipate the order flow leading to severe damages to institutional traders. To mitigate the negative implications of HFT scalpers on commodities markets, we propose a minimum resting trading order period of more than 150 ms.
- Algorithmic trading, Commodities markets, Evolutionary algorithms, High frequency trading, Market efficiency, Market regulation
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