Making sense of chaos? ‘Algos’ scour social media for clues to crypto moves

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Algorithms use so-called natural language processing — identifying key words and emotions that indicate changes in how social media users view certain digital currencies. (Reuters)
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Bin Ren, CEO of Elwood Asset Management
Updated 17 July 2019

Making sense of chaos? ‘Algos’ scour social media for clues to crypto moves

  • Hedge funds and asset managers develop code to scrape social media sites for market-changing news

LONDON: After months of relative calm in cryptocurrency markets, bitcoin exploded back into life in April with its sharpest price jump in over a year — but few people could convincingly explain why.

The 20 percent leap focused investors’ attention on one of the enduring mysteries of cryptocurrencies: What moves the price of an emerging asset in an opaque, largely unregulated market?

For some, the answer lies on social media. Hedge funds and asset managers seeking an edge are training computers to scrape social media sites for triggers that could move the price of digital currencies.

Their goal: Crafting algorithms capable of picking out price “signals” from the background noise of sites ranging from Reddit and WeChat to Twitter and Telegram.

Many investors already use computer models to identify, and trade, price differences across hundreds of cryptocurrency trading exchanges.

But with opportunities for arbitrage narrowing as the nascent sector develops, big players are increasingly looking to build or buy more sophisticated robots to find market-moving signals online, according to interviews with six hedge funds and asset managers and three software developers.

Yet while the use of algorithms, or algos, for parsing social media may be growing, some of those interviewed said major challenges and risks remain to their wider deployment, from cost to complexity.

“It’s an arms race for money managers,” said Bin Ren, CEO of Elwood Asset Management, which specialises in digital assets and is owned by Brevan Howard founder Alan Howard.

“Very few players are able to implement and deliver it, but I believe it is highly profitable.”

Such “sentiment analysis,” as computer-driven reading of the social media mood is known, is used as a tool in traditional markets such as equities and foreign exchange to trade on consumer feelings towards a company or asset.

But it could be of greater significance in cryptocurrency markets, where there are few authoritative sources of information, such as central banks, scarcely any reliable data to gauge asset value such as economic indicators and financial statements, and a high proportion of individual investors.

It is also early days for the technique in the crypto sector, with scant industry-wide data on performance and many questions over its effectiveness. None of the institutions Reuters spoke to would give details of the performance of their algorithms, citing commercial confidentiality.

To be sure, digital currencies do share some drivers with traditional markets such as comments by policymakers. Bitcoin can be sensitive to remarks by regulators in particular: It fell sharply last week after the US Federal Reserve chief called for a halt to Facebook’s planned Libra cryptocurrency project.

But given cryptocurrencies have been entwined with the Internet from their dawn a decade ago, when the word was spread in forums and chatrooms, it would seem to make sense to search for price triggers online.

Still, it is far from cheap or simple to design an algorithm that can find market-moving signals in the cacophonous world of social media, analysing huge numbers of posts in dozens of languages while sifting out unreliable information.

Andrea Leccese, president of Bluesky Capital, an investment firm in New York, said upfront costs for a robot capable of only reading Twitter in English were between $500,000 to $1 million, with most of the money spent on skilled developers. That has deterred Bluesky from using the technique, he said.

One daunting challenge is the sheer number of social media channels. Beyond Twitter, sites often used by cryptocurrency aficionados include Telegram, a messaging app with public channels and Reddit, a messaging board.

In Asia, home to many retail traders, apps such as Line in Japan and Kakao in South Korea are popular.

Tens of thousands of comments on cryptocurrencies are pumped out around the clock across both national and international channels.

Reddit’s main forum, or subreddit, for bitcoin alone has 1.1 million members. Twitter also sees tens of thousands of posts mentioning bitcoin every day, with between 14,000 and 32,000 daily for the last three months, according to the BitInfoCharts website.

In an attempt to extract meaning from this mayhem, algorithms use so-called natural language processing — identifying key words and emotions that indicate changes in how social media users view certain digital currencies.

Investors using algorithms say that they can also identify patterns for information that gains traction online. “The information propagates not randomly, but through a very well-defined structure — it’s like a tree,” said Elwood’s Ren, which has used sentiment analysis for nearly two years after developing its own software.

“It’s very similar to modelling the spreading of a virus.”

Other investors emphasised the challenges in teaching machines to spot biased or inaccurate information.

A Reuters report last November found that many social media users take money for positive reviews of digital coins.

BitSpread, a cryptocurrency asset manager based in London and Singapore, uses its own capital to trade using an algorithm it started developing about a year ago, its CEO Cedric Jeanson told Reuters.

It is a relatively narrowly targeted software. Aggregating Twitter feeds, it looks out for posts on the liquidation, or closing, of positions at exchanges.

“It’s a matter of gathering all the info, trying to understand who is trading where, what kind of liquidation can appear,” he said. “It’s a strategy that makes sense.”

However, he acknowledged the drawbacks.

“The sentiment itself, what we see on Twitter, can be really geared towards fake news. We are always very cautious about what we’re reading in the news because, most of the time, we’ve seen that there’s a bias.”

Many algorithms use machine learning, where they are supposed to improve through experience and better understand how social media posts translate into market movements.

Developers often identify key people with outsized voices and large numbers of followers to weight more heavily in their algorithm, said Bijan Farsijani of Augmento, a Berlin-based startup that launched an algo for sentiment analysis last month.

He said a number of hedge funds had bought the software from his company since the launch.

Background: Bitcoin’s wild ride

Bitcoin, the biggest cryptocurrency and a bellwether for the sector, has surged more than 180 percent this year, driving up the interest of bigger investors from trading firms to hedge funds.

Bitcoin’s most recent rally, last month, was seen by analysts as driven by expectations for a wider adoption of cryptocurrencies driven by Facebook’s Libra.

That move was mirrored by a surge in interest online. Google searches for cryptocurrencies hit their highest level in three months on June 18, when Facebook made the announcement.

It is, however, difficult to pinpoint the chicken and the egg: online chatter or price moves.

“There may be some value in sentiment analysis in crypto, but most of the time what people tweet may be a lagging indicator of the price move,” said Leccese of Bluesky Capital.

“But there is potential,” he added. “People will start looking at this more in the next five to 10 years because there will be diminishing returns because of increased competition in traditional strategies.”

While there is a lack of data specifically for this technique, “quantitative” cryptocurrency funds — which use methods from arbitrage to sentiment analysis — significantly outperformed funds that make longer-term bets in the first quarter of this year, a PwC report shows.

Coders say that they are in increasing demand.

Taiwan-based Marc Howard teamed up with more than 500 machine-learning experts to crowdsource sentiment analysis algorithms, bringing in data from sources including Google Trends, Reddit and development platform GitHub.

Howard said his bitcoin investments using an algorithm beat funds simply tracking the price of the cryptocurrency by 54 percent in the year to June 24, adding that funds in New York and Taipei had tapped him for help in developing their own analysis.

“It’s pretty hot right now,” he said. “Any fund that’s worth their salt, they are devoting some of their resources and allocation for sentiment analysis.”

After one year in office, Pakistan's economy remains government’s biggest challenge

Updated 20 August 2019

After one year in office, Pakistan's economy remains government’s biggest challenge

  • Pakistan’s stocks declined by 32 percent and its currency lost its value by 29 percent in a year
  • Economist say Pakistan has got major support from the Arab world due to its new political leadership

KARACHI: Pakistan’s ongoing economic turmoil has overshadowed the ruling Pakistan Tehreek-e-Insaf (PTI) party’s first anniversary celebrations, as analysts and traders point out that the country’s stock market has witnessed a decline of 32 percent, the national currency has lost its value by 29 percent and the bullion market price has escalated by 60 percent within the last one year.
Prime Minister Imran Khan assumed the country’s top political office on August 18, 2018, promising wide-ranging reforms and economic turnaround. However, his administration found itself struggling against tough economic challenges that included mounting current account and fiscal deficits.
The situation triggered tremendous uncertainty in the stock exchange, making it one of the worst performing markets in Asia. The bench mark KSE 100 index declined from 42,446 points on August 17, 2018, to 28,764 points on August 16, 2019, recording a staggering decline of 32 percent.
“The situation of the market became worse as it remained in the grip of negative sentiments in the backdrop of economic conditions fueled by current account deficit, interest rate hike, and currency devaluations,” Muhammad Faizan Munshey, head of foreign institutional sales at Next Capital, told Arab News.
The stock market on Monday rebounded and gained 798 points to close at 29,562. “The worst condition is almost over and the market is expected to rebound in the future as well,” he added.
Analyst believe that the country’s bourse has bottomed out and the prices are expected to rebound, provided that the growth drivers remain in place. “The government must focus on growth drivers, such as exports, job creation and tax collections, for economic recovery,” Samiullah Tariq, director research at Arif Habib Limited, told Arab News.
During the PTI’s first year in office, the country devalued its currency by almost 29 percent from Rs123.50 against a dollar to Rs159.10 in the interbank market.
Analyst believe the rupee devaluation was done to fulfil the conditions of the International Monetary Fund (IMF) before Islamabad could avail $6 billion bailout package. “There were two reasons cited for the rupee devaluation: the first was the IMF’s free-float requirement and the second was that the Pakistani rupee was overvalued and needed stabilization,” Zafar Paracha, general secretary of Exchange Companies Association of Pakistan, told Arab News.
Pakistan’s central bank governor in June this year tried to dispel the impression that the state bank was reluctant to intervene in the currency market due to the IMF conditions, saying that the country had “adopted a market-based exchange rate system.”
According to Paracha, however, the policy shift took place after the Pak rupee hit a high of 165 against the dollar, saying “it was only then that they [the State Bank and the IMF] realized that free float was not suitable for our market and decided to adopt the market-based exchange rate mechanism instead.”
He added that the lull in the currency market was due to Eid al-Adha related foreign currency inflows. “I don’t see any steps taken to stabilize the economy. Pakistan’s economy does not need ad hoc measures. The change of finance ministers also resulted in a complete shift in policies earlier this year. What the country requires at the moment, however, are carefully crafted stabilization policies that are kept in place for five to ten years.”
Much like the stock and currency markets, the bullion market also experienced volatility as the rate of gold hit Rs89,000 per tola – or approximately 12 grams – on Saturday before cooling down to Rs88,000 on Monday. This rate stood at Rs54,750 a year earlier.
Bullion traders expect the volatility to continue in the market, saying that there has also been a decline in the purchasing power of consumers. “We expect that gold would hit Rs100,000 in the foreseeable future,” Haji Haroon Rasheed Chand, president of All Sindh Saraf Jewelers Association, told Arab News.
Under the circumstances, senior economist say that the country will have to take tough measures with harsh economic and political implications. “Last year, around one million people lost their jobs, poverty increased because the prices of goods jacked up and the growth rate of our economy slowed down,” Dr Hafeez Pasha, former finance minister, told Arab News, adding that “hard times are going to end.”
“Due to our new leader, we have got major support from the Arab world,” he said. “The good thing is that our Arab friends supported the country when it was in dire need and we must thank them for what they have done for us.”
“We received $3 billion from Saudi Arabia and they also extended us the deferred oil payment facility that began in July this year. The United Arab Emirates also deposited $2 billion and Qatar extended $500 million as well,” he added.