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
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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.”


Egypt’s creative solutions to the plastic menace

Updated 24 August 2019
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Egypt’s creative solutions to the plastic menace

  • Egyptian social startups are taking alternative approaches to fostering awareness and reducing waste
  • While initiatives around the world are taking action to combat this problem, some Egyptian projects are doing it more creatively

CAIRO: Global plastics production reached 348 million tons in 2017, rising from 335 million tons in 2016, according to Plastics Europe. 

Critically, most plastic waste is not properly managed: Around 55 percent of it was landfilled or discarded in 2015. These numbers are extremely concerning because plastic products take anything from 450 to 1,000 years to decompose, and the effects on the environment, especially on marine and human life, are catastrophic.

While initiatives around the world are taking action to combat this problem, some Egyptian projects are doing it more creatively.

“We’re the first website in the Middle East and North Africa that trades waste,” said Alaa Afifi, founder and CEO of Bekia. “People can get rid of any waste at their disposal — plastic, paper and cooking oil — and exchange it for over 65 products on our website.”

Products for trading include rice, tea, pasta, cooking oil, subway tickets and school supplies.

Bekia was launched in Cairo in 2017. Initially, the business model did not prove successful.

“We used to rent a car and go to certain locations every 40 days to collect waste from people,” Afifi, 26, explained. “We then created a website and started encouraging people to use it.”

After the website was launched, people could wait at home for someone to collect the waste. “Instead of 40 days, we now could visit people within a week.”

To use Bekia’s services, people need to log onto the website and specify what they want to discard. They are assigned points based on the waste they are offering, and these points can be used in one of three ways: Donated to people in need, saved for later, or exchanged for products. As for the collected waste, it is given to specialized recycling companies for processing.

“We want to have 50,000 customers over the next two years who regularly use our service to get rid of their waste,” Afifi said.  

Trying to spread environmental awareness has not been easy. “We had a lot of trouble with initial investment at first, and we got through with an investment that was far from enough. The second problem we faced was spreading this culture among people — in the first couple of months, we received no orders,” Afifi said.

The team soldiered on and slowly built a client base, currently serving 7,000 customers. In terms of what lies ahead for Bekia, he said: “We’re expanding from 22 to 30 areas in Cairo this year. We’re launching an app very soon and a new website with better features.”

Go Clean, another Egyptian recycling startup dedicated to raising environmental awareness, works under the patronage of the Ministry of Environment. “We started in 2017 by recycling waste from factories, and then by February 2019 we started expanding,” said founder and CEO Mohammed Hamdy, 30.

The Cairo-based company collects recyclables from virtually all places, including households, schools, universities, restaurants, cafes, companies and embassies. The customers separate the items into categories and then fill out a registration form. Alternatively, they can make contact through WhatsApp or Facebook. A driver is then dispatched to collect the waste, carrying a scale to weigh it. 

“The client can be paid in cash for the weight of their recyclables, or they can make a donation to a special needs school in Cairo,” Hamdy explained. There is also the option of trading the waste for dishwashing soap, with more household products to be added in the future.

Trying to cover a country with 100 million people was never going to be easy, and Go Clean faced some logistical problems. It overcame them by hiring more drivers and getting more trucks. There was another challenge along the way: “We had to figure out a way to train the drivers, from showing them how to use GPS and deal with clients,” said Hamdy.

“We want to spread awareness about the environment everywhere. We go to schools, universities, companies and even factories to give sessions about the importance of recycling and how dangerous plastic is. We’re currently covering 20 locations across Cairo and all of Alexandria. We want to cover all of Egypt in the future,” he added.

With a new app on the way, Hamdy said things are looking positive for the social startup, and people are becoming invested in the initiative. “We started out with seven orders per day, and now we get over 100.”