A Global Mood Ring for Financial Markets

By Nicole Hemsoth

May 11, 2011

What if you could instantly scan all individual posts on Twitter for one day, cull those snippets together into a cogent whole, and use that information to paint a picture of the global mood?

If that idea alone isn’t enough, imagine making the snap decision to rush out and buy stocks because within three to four days stocks will rise due to the positive “vibe” in the air as foretold by the collective Twitter chatter. Conversely, if the world is having what amounts to a bad hair day, you accordingly sell your stock holdings, knowing that within three to four days, that dour zeitgeist will portend a drop in the Dow.

Does this sound to you like yet another flimsy system to sell traders on the idea that this might be the next big secret? Does it, like all other stock-related get-rich-quick schemes (and let’s face it, just because it comes out of academia doesn’t mask an unmistakble sense of self-interest) seem too good to be true?

For years scientists and speculators have tried to pin down the mysterious changing tides of the stock market. Proof? Search for “stock predictions” to find millions of options from informed analysis and offers of psychic or spiritual guidance. So far nothing has hit home for long enough to be a tried and true standard for evaluating buy or trade decisions.

That “too good to be true” paradigm for market predictions might be upended, however, thanks to our endless tweets and social media updates that indicate our mood, both through words and emoticons–not to mention an expensive array of compute-end tools to tackle massive unstructured data sets in a flash.

The provocative predictive analytics study in question proved a direct correlation between overall stock market performance and the general mood of many thousands of people as gauged from their brief posts on Twitter.  While the model for buying and selling described above only works around 86% of the time, this news caught the attention of traders and computer scientists with equal force.

As a recent article noted, “Online surveillance of social networking sites is emerging as a must-have tool for hedge funds, big banks, high-frequency traders and black box investment firms that run money via computer programs.” The author goes on to note that your feelings and general mood, captured and combined with the rest of the Tweeting, Facebooking world, could become the core of decision-making processes at major financial institutions.

Dr. Johan Bollen teaches informatics at Indiana University and is the lead behind the Twitter mood informatics project. He noted in a recent interview that this marks the beginning of a new era of mood collection to measure stock performance, noting that it is indeed like science fiction that we can now have “a large-scale emotional thermometer for society as a whole.”

In an interview this week Bollen told us that while he can’t share specific details about storage, application layers and the like since his team is in the process of further developing and licensing the research, the processing of tweets is happening in “real time” although it all depends on how one defines “real time.”

In Bollen’s words:

There is clearly a lower bound of the temporal granularity at which you can compute these signals. This limit is largely shaped by processing speeds and the amount of data to process. The amount of Twitter and social media data keeps growing very fast, however at some point you could expect all 7 billion people on earth to have a Twitter or Facebook account and since no one can tweet faster than their thumbs will move across a smart phone screen.

We may find some upper limit on the amount of social media data that can feasible be generated by humanity. From that you can work back to determine the temporal granularity at which you can operate the existing computational limits at a particular point in time.”

In Bollen’s experiences with the computational angle to arrival at global sentiment, he says that he remains optimistic that his team will be able to generate these signals at very small temporal granularity. He noted that as of now, they are “easily processing daily feeds meaning we have a daily signal which is suitable given that our research has shown that this signal is predictive of real-world changes 3 to 4 days in advance. From a preliminary analysis it seems we can take this down to hourly or even half-hourly signals without too much trouble.”

Bollen claims that while all of his work is quite CPU-intensive, much of it can be parallelized because they are analyze each tweet in isolation. With this in mind, however, he claims that they do run into some pretty hard computational limits with their social network analysis as some of the existing algorithms simply cannot run over social networks of such size.

As another element in the computational depth involved in such an undertaking, Bollen told us:

In terms of data intensiveness you do need large-scale data to counter-act noise and other distortions, but there is definitely a law of diminishing returns. Many of these data sets follow very skewed distributions. In general terms you will have very few people making very large and significant contributions, and very many making small and insignificant contributions. By capturing the right subset you can therefore arrive at a much smaller data set that still provides 90% of your signal, and thereby greatly boost your ability to perform your analysis at very short time intervals.

Outside of CPU and signals, there are other challenges that might stand in the way as this idea potentially takes off for financial companies.

This data, which comes in from across an array of global social networks creates a massive pool of unstructured data, could prove a stumbling block for the widespread viability of this kind of real-time data analysis.

Xenomorph is a data analytics and management firm with roots in financial services. According to its CEO, Brian Sentence, “Real time social media feeds give some insight into the human behavior that really drives the markets. However, in addition to the challenge of processing such a large amount of data, correct understanding of the data is the biggest challenge. For instance, seeing “Hathaway” mentioned on Twitter might mean some news on ‘Berkshire Hathaway’ or the actress “Anne Hathaway.”

However, this type of analytics goes far beyond general semantics and natural language processing—it looks at more discreet indicators of mood, including emoticons and other less word-bound cues.

Henry Newman, CEO and CTO of Instrumental, Inc., which is a consultancy firm for users and manufacturers of HPC, also weighed in on the data-level challenges of such analytics. He noted, “There are a number of challenges in this areas including the capture and indexing of the data and of course the development of algorithms to correlate the trends to specific market changes.  Additional challenges include the long term storage and the analysis model. I am aware of some sites MapReduce to be able to search this type of data but these are still problems.”

Instrumental Inc.’s Henry Newman also made a good point about the use of predictive analytics for financial markets in his speculation about the real value of this kind of technology. As he said, “I am not a sociologist and have not looked to see if this type of analysis will provide trending information for trading. What I am sure of is that if it does work just like every other method used it will not work all of the time and could cause large market swings just like other methods we have seen over the last few decades.”

The takeaway here if you’re not a stock market player: Be careful what you tweet, the world’s economy might just depend on it…well, at least 86% of the time. Allow me to do my part for the vitality of world economies and end this piece with a 🙂

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Arm Unveils Neoverse N1 Platform with up to 128-Cores

February 20, 2019

Following on its Neoverse roadmap announcement last October, Arm today revealed its next-gen Neoverse microarchitecture with compute and throughput-optimized silicon designs catered toward general-purpose cloud computing Read more…

By Tiffany Trader

The Internet of Criminal Things—Trust in the Gods but Verify!

February 20, 2019

“Are we under attack?” asked Professor Elmarie Biermann of the Cyber Security Institute during the recent South African Centre for High Performance Computing’s (CHPC) National Conference in Cape Town. A quick show Read more…

By Elizabeth Leake, STEM-Trek

Machine Learning Takes Heat for Science’s Reproducibility Crisis

February 19, 2019

Scientists are raising red flags about the accuracy and reproducibility of conclusions drawn by machine learning frameworks. Among the remedies are developing new ML systems that can question their own predictions, show Read more…

By George Leopold

HPE Extreme Performance Solutions

HPE and Intel® Omni-Path Architecture: How to Power a Cloud

Learn how HPE and Intel® Omni-Path Architecture provide critical infrastructure for leading Nordic HPC provider’s HPCFLOW cloud service.

powercloud_blog.jpgFor decades, HPE has been at the forefront of high-performance computing, and we’ve powered some of the fastest and most robust supercomputers in the world. Read more…

IBM Accelerated Insights

The Perils of Becoming Trapped in the Cloud

Terms like ‘open systems’ have been bandied about for decades. While modern computer systems are relatively open compared to their predecessors, there are still plenty of opportunities to become locked into proprietary interfaces. Read more…

What’s New in HPC Research: Wind Farms, Gravitational Lenses, Web Portals & More

February 19, 2019

In this bimonthly feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programming to exascale to quantum computing, the details are here. Read more…

By Oliver Peckham

Arm Unveils Neoverse N1 Platform with up to 128-Cores

February 20, 2019

Following on its Neoverse roadmap announcement last October, Arm today revealed its next-gen Neoverse microarchitecture with compute and throughput-optimized si Read more…

By Tiffany Trader

Insights from Optimized Codes on Cineca’s Marconi

February 15, 2019

What can you do with 381,392 CPU cores? For Cineca, it means enabling computational scientists to expand a large part of the world’s body of knowledge from th Read more…

By Ken Strandberg

ClusterVision in Bankruptcy, Fate Uncertain

February 13, 2019

ClusterVision, European HPC specialists that have built and installed over 20 Top500-ranked systems in their nearly 17-year history, appear to be in the midst o Read more…

By Tiffany Trader

UC Berkeley Paper Heralds Rise of Serverless Computing in the Cloud – Do You Agree?

February 13, 2019

Almost exactly ten years to the day from publishing of their widely-read, seminal paper on cloud computing, UC Berkeley researchers have issued another ambitious examination of cloud computing - Cloud Programming Simplified: A Berkeley View on Serverless Computing. The new work heralds the rise of ‘serverless computing’ as the next dominant phase of cloud computing. Read more…

By John Russell

Iowa ‘Grows Its Own’ to Fill the HPC Workforce Pipeline

February 13, 2019

The global workforce that supports advanced computing, scientific software and high-speed research networks is relatively small when you stop to consider the magnitude of the transformative discoveries it empowers. Technical conferences provide a forum where specialists convene to learn about the latest innovations and schedule face-time with colleagues from other institutions. Read more…

By Elizabeth Leake, STEM-Trek

Trump Signs Executive Order Launching U.S. AI Initiative

February 11, 2019

U.S. President Donald Trump issued an Executive Order (EO) today launching a U.S Artificial Intelligence Initiative. The new initiative - Maintaining American L Read more…

By John Russell

Celebrating Women in Science: Meet Four Women Leading the Way in HPC

February 11, 2019

One only needs to look around at virtually any CS/tech conference to realize that women are underrepresented, and that holds true of HPC. SC hosts over 13,000 H Read more…

By AJ Lauer

IBM Bets $2B Seeking 1000X AI Hardware Performance Boost

February 7, 2019

For now, AI systems are mostly machine learning-based and “narrow” – powerful as they are by today's standards, they're limited to performing a few, narro Read more…

By Doug Black

Quantum Computing Will Never Work

November 27, 2018

Amid the gush of money and enthusiastic predictions being thrown at quantum computing comes a proposed cold shower in the form of an essay by physicist Mikhail Read more…

By John Russell

Cray Unveils Shasta, Lands NERSC-9 Contract

October 30, 2018

Cray revealed today the details of its next-gen supercomputing architecture, Shasta, selected to be the next flagship system at NERSC. We've known of the code-name "Shasta" since the Argonne slice of the CORAL project was announced in 2015 and although the details of that plan have changed considerably, Cray didn't slow down its timeline for Shasta. Read more…

By Tiffany Trader

The Case Against ‘The Case Against Quantum Computing’

January 9, 2019

It’s not easy to be a physicist. Richard Feynman (basically the Jimi Hendrix of physicists) once said: “The first principle is that you must not fool yourse Read more…

By Ben Criger

AMD Sets Up for Epyc Epoch

November 16, 2018

It’s been a good two weeks, AMD’s Gary Silcott and Andy Parma told me on the last day of SC18 in Dallas at the restaurant where we met to discuss their show news and recent successes. Heck, it’s been a good year. Read more…

By Tiffany Trader

Intel Reportedly in $6B Bid for Mellanox

January 30, 2019

The latest rumors and reports around an acquisition of Mellanox focus on Intel, which has reportedly offered a $6 billion bid for the high performance interconn Read more…

By Doug Black

ClusterVision in Bankruptcy, Fate Uncertain

February 13, 2019

ClusterVision, European HPC specialists that have built and installed over 20 Top500-ranked systems in their nearly 17-year history, appear to be in the midst o Read more…

By Tiffany Trader

US Leads Supercomputing with #1, #2 Systems & Petascale Arm

November 12, 2018

The 31st Supercomputing Conference (SC) - commemorating 30 years since the first Supercomputing in 1988 - kicked off in Dallas yesterday, taking over the Kay Ba Read more…

By Tiffany Trader

Looking for Light Reading? NSF-backed ‘Comic Books’ Tackle Quantum Computing

January 28, 2019

Still baffled by quantum computing? How about turning to comic books (graphic novels for the well-read among you) for some clarity and a little humor on QC. The Read more…

By John Russell

Leading Solution Providers

SC 18 Virtual Booth Video Tour

Advania @ SC18 AMD @ SC18
ASRock Rack @ SC18
DDN Storage @ SC18
HPE @ SC18
IBM @ SC18
Lenovo @ SC18 Mellanox Technologies @ SC18
NVIDIA @ SC18
One Stop Systems @ SC18
Oracle @ SC18 Panasas @ SC18
Supermicro @ SC18 SUSE @ SC18 TYAN @ SC18
Verne Global @ SC18

Contract Signed for New Finnish Supercomputer

December 13, 2018

After the official contract signing yesterday, configuration details were made public for the new BullSequana system that the Finnish IT Center for Science (CSC Read more…

By Tiffany Trader

Deep500: ETH Researchers Introduce New Deep Learning Benchmark for HPC

February 5, 2019

ETH researchers have developed a new deep learning benchmarking environment – Deep500 – they say is “the first distributed and reproducible benchmarking s Read more…

By John Russell

IBM Quantum Update: Q System One Launch, New Collaborators, and QC Center Plans

January 10, 2019

IBM made three significant quantum computing announcements at CES this week. One was introduction of IBM Q System One; it’s really the integration of IBM’s Read more…

By John Russell

HPC Reflections and (Mostly Hopeful) Predictions

December 19, 2018

So much ‘spaghetti’ gets tossed on walls by the technology community (vendors and researchers) to see what sticks that it is often difficult to peer through Read more…

By John Russell

IBM Bets $2B Seeking 1000X AI Hardware Performance Boost

February 7, 2019

For now, AI systems are mostly machine learning-based and “narrow” – powerful as they are by today's standards, they're limited to performing a few, narro Read more…

By Doug Black

Nvidia’s Jensen Huang Delivers Vision for the New HPC

November 14, 2018

For nearly two hours on Monday at SC18, Jensen Huang, CEO of Nvidia, presented his expansive view of the future of HPC (and computing in general) as only he can do. Animated. Backstopped by a stream of data charts, product photos, and even a beautiful image of supernovae... Read more…

By John Russell

The Deep500 – Researchers Tackle an HPC Benchmark for Deep Learning

January 7, 2019

How do you know if an HPC system, particularly a larger-scale system, is well-suited for deep learning workloads? Today, that’s not an easy question to answer Read more…

By John Russell

Intel Confirms 48-Core Cascade Lake-AP for 2019

November 4, 2018

As part of the run-up to SC18, taking place in Dallas next week (Nov. 11-16), Intel is doling out info on its next-gen Cascade Lake family of Xeon processors, specifically the “Advanced Processor” version (Cascade Lake-AP), architected for high-performance computing, artificial intelligence and infrastructure-as-a-service workloads. Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This