Algo Trading Debate Intensifies
Fueled by recent market snafus involving faulty execution and operations, the debate over the pros and cons of high-frequency trading has escalated in recent months.
“If there is one issue that I hear about from my advisors who are channeling clients, its concern about the extent to which the markets have become driven by high-speed computer trading systems and algorithmic trading,” said John Taft, CEO of RBC Wealth Management in the U.S.
Taft, a former chairman of Sifma, added that “it’s a very complicated subject.”
According to a Sifma white paper published late last year, high-frequency trading is a relatively new, catch-all term that’s used, often interchangeably, to refer to several related but distinct computer-based trading concepts.
These concepts include computer-based trading characterized by high portfolio turnover and high order-to-trade ratios, algorithmic trading, market making, and other forms of computer-based trading that employ sophisticated technological tools.
Regulators have sought to identify types of trading strategies or behaviors that are often used in HFT.
Hong Kong’s Securities and Futures Commission, in a consultation published last month, set out proposals on the regulatory requirements for intermediaries to manage and mitigate the risks that arise from trading in an automated environment.
The SFC defines algorithmic trading as computer-generated trading activities created by a pre-determined set of rules aimed at delivering specific execution outcomes.
The consultation proposes that a financial intermediary should ensure that the design and development of its algorithmic trading system and trading algorithms are supported by persons adequately qualified and trained to understand the compliance and regulatory issues which may arise from the use of algorithms, including its trading characteristics and execution behavior, and its potential market impact.
“Market participants need to debug their code thoroughly as well as test the system it on a demo account at great length before releasing it in the wild,” said Matthew Hors, managing director of Varick Capital. “I also feel regulators need tighten things up in regards to black box systems.”
In the United States, the Financial Industry Regulatory Authority (Finra) expects firms generating orders by the use of trading algorithms to have written policies and procedures in place that are reasonably designed to ensure that such trading complies with applications rules and regulations.
The Australia Securities and Investment Commission (ASIC) this week issued its latest market supervision report, which identified issues from high-frequency trading.
The report–ASIC’s fourth on the supervision of Australian financial markets and market participants– identified that during the first half of 2012, there were 22,225 trading alerts, with 36 matters referred for investigation, including potential insider trading (13), market manipulation (5), possible breaches of the market integrity rules (15) and of the continuous disclosure obligations (3).
ASIC proposes that market participants test algorithms to ensure that they would function in compliance with regulation requirements before using them for the first time or before a material change to the algorithm is implemented.
European Securities and Markets Authority (ESMA) guidelines state that investment firms should test trading algorithms prior to deployment and conduct periodic reviews after implementation, monitor trading algorithms in real time, and have policies and procedures in place to minimize the risk that their automated trading activity gives rise to market abuse.
The deal will expand QuantHouse's US coverage.
Broker-dealer algorithms are evaluated, normalized and eventually rewarded for their performance.
Are trades executed in line with the intent of the orders?
Cowen estimates at least 6 basis points saved per block trade, more for less liquid securities.
eFinancialCareers reports that low-vol markets favor man over machine.