FX Algos are Struggling to Keep Up with Brexit Headlines

by Celeste Skinner
  • Brexit headlines have increased dramatically, and news-reading algorithms can’t keep up with the mass of information.
FX Algos are Struggling to Keep Up with Brexit Headlines
Finance Magnates

The ongoing Brexit saga has dominated news headlines for more than two years now, and the future of the United Kingdom still remains uncertain. Although the situation continues to change, it never seems to get much clearer, and people who have been left scratching their heads confused about the whole issue are not alone - it’s even confounding the robots.

The global currency market has a trading volume of around $5.1 trillion a day. Since the referendum on Brexit in 2016, the British pound (GBP) has become a volatile currency and increasingly sensitive to Brexit-related headlines.

Not only has this made GBP trading harder for people, but also for news-reading robots, who, according to a report from Reuters are struggling to keep of with the mass of headlines around the UK’s efforts to leave the European Union. As a result, trading the sterling is more risky and expensive.

News-reading algorithms, or algos, are becoming an increasingly common feature of the trading floor of banks and asset managers, replacing humans and significantly increasing the rate at which deals can be executed, with some even able to reduce the time down to millionths of a second.

These algorithms were traditionally designed to process economic data or central bank policy statements, which are known to influence currency movements, before executing a buy or sell order. Now, however, some computer trading models can now analyze news headlines or Twitter storms in a split second.

But how many news-reading algos are there in the foreign exchange (Forex ) market? At present, there is no official data, but three currency traders at London-based banks told Reuters they estimated it to be less than 10 percent.

Robots Can’t Keep Up with the Brexit Saga

These robots are being inundated with news headlines regarding Brexit, and too many are being produced for the computers to keep up with. As highlighted by the news outlet, in one day, it has published up to 400 news headlines on Brexit in recent weeks. This is a dramatic uptick from the average of 15 it used to publish on British politics before Brexit was an issue.

Its competitor Bloomberg has increased its Brexit coverage even more dramatically, with a spokesperson stating that Brexit-related content is up by fourfold since last autumn, and on some days has exceeded more than 1,000 headlines.

We here at Finance Magnates have also noticed a surge in Brexit-related content. With reports from financial regulators and financial firms such as brokers, increasingly releasing announcements in regards to contingency planning.

Speaking to Reuters, Neil Jones, head of hedge fund currency sales at Mizuho in London said: “The model signals are more quantitative driven and rely on historical data feeds. Brexit headlines have thrown a spanner in their works for the sheer number of characters moving the currency on a daily basis.”

GBP Volatility is Incredibly Sensitive

Volatility in the GBP has become so sensitive, that even a hand signal can cause the currency to move. Last year, on November 6, Dominic Raab who was Britain’s Brexit Minister at the time, caused the sterling to surge after he simply gave a “thumbs up” after a cabinet meeting.

Taking this into consideration, it’s no wonder that trading robots are finding the Brexit issue overwhelming. Because of the increasing complexities of trading the sterling, the proportion of these robots trading the GBP are likely to be lower than the estimated 10 percent, with the news outlet stating that some hedge funds have even opted out of trading the currency altogether.

“If it was your job and given the complexity of the Brexit story, do you really want to precode something to automatically infer and put material risk on the back of that. Probably not,” David Leigh, global head of FX spot and electronic trading at Deutsche Bank told the news outlet.

The ongoing Brexit saga has dominated news headlines for more than two years now, and the future of the United Kingdom still remains uncertain. Although the situation continues to change, it never seems to get much clearer, and people who have been left scratching their heads confused about the whole issue are not alone - it’s even confounding the robots.

The global currency market has a trading volume of around $5.1 trillion a day. Since the referendum on Brexit in 2016, the British pound (GBP) has become a volatile currency and increasingly sensitive to Brexit-related headlines.

Not only has this made GBP trading harder for people, but also for news-reading robots, who, according to a report from Reuters are struggling to keep of with the mass of headlines around the UK’s efforts to leave the European Union. As a result, trading the sterling is more risky and expensive.

News-reading algorithms, or algos, are becoming an increasingly common feature of the trading floor of banks and asset managers, replacing humans and significantly increasing the rate at which deals can be executed, with some even able to reduce the time down to millionths of a second.

These algorithms were traditionally designed to process economic data or central bank policy statements, which are known to influence currency movements, before executing a buy or sell order. Now, however, some computer trading models can now analyze news headlines or Twitter storms in a split second.

But how many news-reading algos are there in the foreign exchange (Forex ) market? At present, there is no official data, but three currency traders at London-based banks told Reuters they estimated it to be less than 10 percent.

Robots Can’t Keep Up with the Brexit Saga

These robots are being inundated with news headlines regarding Brexit, and too many are being produced for the computers to keep up with. As highlighted by the news outlet, in one day, it has published up to 400 news headlines on Brexit in recent weeks. This is a dramatic uptick from the average of 15 it used to publish on British politics before Brexit was an issue.

Its competitor Bloomberg has increased its Brexit coverage even more dramatically, with a spokesperson stating that Brexit-related content is up by fourfold since last autumn, and on some days has exceeded more than 1,000 headlines.

We here at Finance Magnates have also noticed a surge in Brexit-related content. With reports from financial regulators and financial firms such as brokers, increasingly releasing announcements in regards to contingency planning.

Speaking to Reuters, Neil Jones, head of hedge fund currency sales at Mizuho in London said: “The model signals are more quantitative driven and rely on historical data feeds. Brexit headlines have thrown a spanner in their works for the sheer number of characters moving the currency on a daily basis.”

GBP Volatility is Incredibly Sensitive

Volatility in the GBP has become so sensitive, that even a hand signal can cause the currency to move. Last year, on November 6, Dominic Raab who was Britain’s Brexit Minister at the time, caused the sterling to surge after he simply gave a “thumbs up” after a cabinet meeting.

Taking this into consideration, it’s no wonder that trading robots are finding the Brexit issue overwhelming. Because of the increasing complexities of trading the sterling, the proportion of these robots trading the GBP are likely to be lower than the estimated 10 percent, with the news outlet stating that some hedge funds have even opted out of trading the currency altogether.

“If it was your job and given the complexity of the Brexit story, do you really want to precode something to automatically infer and put material risk on the back of that. Probably not,” David Leigh, global head of FX spot and electronic trading at Deutsche Bank told the news outlet.

About the Author: Celeste Skinner
Celeste Skinner
  • 2872 Articles
  • 25 Followers
About the Author: Celeste Skinner
  • 2872 Articles
  • 25 Followers

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