Key High Frequency Algorithmic Trading Controls

Posted by

Lynne Callister

on 18 Oct 2017

Disruptive trends like High-Frequency Algorithmic Trading (HFAT) are transforming financial services. So it's important to know what controls you need.

Key High Frequency Algorithmic Trading Controls

Benefits of HFAT

Many firms, including Goldman Sachs, have expanded their own algorithmic trading programmes to take advantage of the numerous benefits.

  • Creating greater liquidity
  • Increased volumes,
  • Reduced short-term volatility
  • Narrower spreads
  • Lower costs for investors
  • Better price formation
  • Faster execution of orders

But there are also considerable risks that can potentially cause widespread and significant market distortion and create a disorderly market.

Algorithmic trading will continue to face more scrutiny as new obligations appear like within MiFID II. This isn't anything new - Germany's High-Frequency Trading Act was introduced in 2013 - but critics are sceptical about whether the measures will do anything to combat market abuse and question whether the time invested in data collection could be better spent.

Five essential HFAT controls

1. Check the HFAT definition

Until recently, there was no clear definition of HFAT, and still, there's some dispute about whether the MiFID II definition is too broad.

Check whether you fall under the definition of HFT:

"trading in financial instruments where a computer algorithm automatically determines individual parameters of orders, such as whether to initiate the order, the timing, price or quantity of the order, or how to manage the order after its submission, with limited or no human intervention."

2. Registration

Firms engaging in HFT must be formally registered and meet Regulatory Technical Standard 6 (RTS 6) requirements, demonstrating where software is purchased from, how it is developed, audited and stress-tested, how trades are monitored, and the mechanisms for triggering alerts.

3. Clarify terminology

Get broad consensus across the firm about what constitutes an algorithm, algo-trader and algo-trading. For example, would you class a simulated stop order as algorithmic trading? This will ensure consistent application of the rules.

4. Clock synchronisation

(RTS 25) - is this technically possible? How can you overcome practical challenges? What management oversight is there over the time distribution chain? Are there systems in place to ensure a rapid response if problems are experienced? What checks can be carried out to ensure that everything is set up correctly? What sorts of events might cause time lags - e.g. maintenance or failed network switches - and how can you mitigate this? How can errors be detected? How can you ensure accuracy between data centres and servers running trading platforms?

5. Check capability for record-keeping

Are you currently able to keep detailed time-sequenced records of all algorithms? What capability will you need in future?

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