Alternative Data News. 08, April 2020
Finding sources and uses for alternative data can be difficult. At CloudQuant we regularly read and search the internet for new sources of data that can be used in our mission to find alpha signals and build quantitative trading strategies. We recognize that we are technology and data junkies so we wrote our own crawler that specifically seeks out web pages, posts, and news articles that give us a snapshot of what is going on in the world of Alt Data. The following is a collection of articles that we think you will find interesting from the past week.
COVID-19 impact on US spending
Live view of consumer spending, based on credit and debit card usage across the United States, can help you keep a finger on the pulse of the economy. What is the magnitude of the current economic contraction? When is the economic turning point? At what speed and strength will the US economy recover?
How are the indices calculated? The combined spending shows the difference year-on-year (YoY) calculated daily (adjusted for day-of-week effects). The sector indices are aggregated per sector and show the difference year-on-year on a seven-day moving average window. The dotted vertical line indicates the onset for the change in consumer behaviour, observed to be around February 25th. Some sectors also include visitor data for businesses with physical locations, calculated in the same manner.
Why monitor consumer spending data? Live transaction data from credit and debit card usage is a way to get a very early indication of changes in consumer behaviour. Trends seen here will often be reflected in companies’ quarterly earnings reports, US census statistics and in GDP – but not until several weeks or months later.
2020-04-07 09:30:00+00:00 Read the full story…
CloudQuant Thoughts : There are some really great charts coming out from alternative data sources to help us get a handle on the effects of this outbreak.
Are Too Many Data Scientists Trying To Predict COVID-19 In Futility?
Data scientists have been creating a lot of tools that help explain significant questions around COVID-19. One example is dashboards based on COVID-19 cases around the globe. It has helped show active cases, those in the testing phase, information on patient history, etc that provide a window into the overall scenario of the pandemic.
There have also been many challenges and hackathons in response to COVID-19, and several data companies are providing free data resources. Kaggle has thousands of posts related to COVID-19.
The COVID-19 Open Research Dataset Challenge (CORD-19) dataset on Kaggle contains over 44,000 scholarly articles, and one Kaggle expert Daniel Wolffram has created several widgets that help navigate the current COVID-19 research literature. There are also geospatial trackers of multiple government initiatives built from the work of data scientists, which serve as valuable tools during the pandemic.
2020-04-07 09:30:00+00:00 Read the full story…
Weighted Interest Score: 4.1340, Raw Interest Score: 1.8728,
Positive Sentiment: 0.1960, Negative Sentiment 0.1307
CloudQuant Thoughts : Whilst there are experts in the field of analysis of pandemics and viral outbreaks I still think that the more eyes on a subject the better. Everyone has a unique point of view. The major issue is that their is no consistency in the data, Germany has very few dead and China is insisting that it has had around 30 deaths a day for a month and now no new infections. So alternative data such as those we have covered on this post over the duration of the outbreak (Tom Tom go traffic in major Chinese cities, Telemetry Traffic changes in Europe, TSA Daily numbers, Web enabled thermometers in the US) all give new and unique views of the ‘curve’ that everyone is talking about.
Rearchitecting Legacy Machine Learning Systems
TradeRev uses regression models for predicting the auction price of cars. The early years of ML/development focused entirely on time to market which lead to a successful product but we ended up with a code base that had huge tech debt (spaghetti code, monolithic architecture, manually created infrastructure etc.).
Increasing adoption rate of the product exposed the tech debt as scaling the product became a massive bottleneck. The speakers will discuss how they took the challenge of rearchitecting the entire ML product from both software engineering and data science perspectives.
They will share how they accomplished many milestones as a result of this endeavour
2020-04-07 18:29:08.973000+00:00 Read the full story…
Weighted Interest Score: 3.7298, Raw Interest Score: 2.5202,
Positive Sentiment: 0.4032, Negative Sentiment 0.3024
CloudQuant Thoughts : Yes, we are already here, re-architecting legacy machine learning systems!
Machine Learning: Making Sense of Unstructured Data and Automation in Alt Investments
Institutional investors are buckling under the operational constraint of processing hundreds of data streams from unstructured data sources such as email, PDF documents, and spreadsheets. These data formats bury employees in low-value ‘copy-paste’ workflows and block firms from capturing valuable data. Here, we explore how Machine Learning (ML) paired with a better operational workflow, can enable firms to more quickly extract insights for informed decision-making, and help govern the value of data.
According to McKinsey, the average professional spends 28% of the workday reading and answering an average of 120 emails – on top of the 19% spent on searching and processing data. The issue is even more pronounced in information-intensive industries such as financial services, as valuable employees are also required to spend needless hours every day processing and synthesizing unstructured data. Transformational change, however, is finally on the horizon. Gartner research estimates that by 2022, one in five workers engaged in mostly non-routine tasks will rely on artificial intelligence (AI) to do their jobs. And embracing ML will be a necessity for digital transformation demanded both by the market and the changing expectations of the workforce.
2020-04-08 01:29:51+00:00 Read the full story…
Weighted Interest Score: 3.5386, Raw Interest Score: 2.1870,
Positive Sentiment: 0.2604, Negative Sentiment 0.3541
CloudQuant Thoughts : At CloudQuant we understand Data Science, we have alternative data sets available where we pre-process the data for you, carrying out cleaning and sanity checks as well as testing the data set for efficacy. Head over to our Data Catalog to find out more!
BTON Financial And genesis Automate Buy-side Trading
BTON Financial, the independent outsourced dealing desk for asset managers and genesis, the Low Code Application Platform for Capital Markets, are pleased to announce their partnership to automate trading workflows, which in turn drives greater trading performance. The partnership helps drive front office transformation, bringing together genesis’ ability for agile software development and BTON Financial’s independent technology and data driven approach to outsourced dealing in the form of their award winning ‘Smart Broker Router’.
Following a competitive due diligence process, covering both vendors and consultancies, BTON Financial selected genesis as their technology partner because of their deep market expertise and Low Code Application Platform built specifically for capital markets. By using the genesis Low Code Application Platform, BTON are able to create solutions quickly without having to write substantial lines of code, making the development and deployment of these solutions much faster, simpler and much easier to support.
2020-04-08 09:44:10+00:00 Read the full story…
Weighted Interest Score: 3.9922, Raw Interest Score: 1.9140,
Positive Sentiment: 0.5270, Negative Sentiment 0.0832
Credit Hero gets a digital boost in lending with Salt Edge
Credit Hero, an online lender from Hong Kong, teamed up with Salt Edge, a leader in offering open banking solutions, to access borrowers’ bank data at digital speed and eliminate the traditional paper chase.
Hong Kong is a leading global financial hub. As recently the macroeconomic environment has changed, the lending market is experiencing a so-called digital seismic shift. Escalating uncertainties kickstart the demand for credit products which provide fast access to consumption-oriented liquidity.
Credit Hero uses artificial intelligence and data science to provide tech-savvy lending solutions. The company employs optical character and facial recognition for risk assessment and machine learning for automated underwriting. AI technologies run bank data aggregated from 9 major HK banks to reduce the lending process time from days to 6 minutes. Equipped with Salt Edge tools, Credit Hero improved the bad debt rate by enhancing credit risk analysis.
2020-04-08 11:15:00 Read the full story…
Weighted Interest Score: 3.8405, Raw Interest Score: 2.5148,
Positive Sentiment: 0.4438, Negative Sentiment 0.0986
Buy-Side AI Platform Gains Traction
Exabel, which provides a simple-to-use artificial intelligence and machine learning platform to active investment managers and financial analysts, has gained clients in the UK and aims to expand into the US.
Neil Chapman, chief executive of Exabel, told Markets Media: “We help the buy side to use more data and become more quantitative. We can provide artificial intelligence and machine learning as a platform to non-technical users to allow asset managers to squeeze more value from data.” Exabel announced that Chapman had joined as chief executive in January this year from ForgeRock, which develops develops commercial open source identity and access management products.
2020-04-06 17:27:13+00:00 Read the full story…
Weighted Interest Score: 3.8380, Raw Interest Score: 1.8031,
Positive Sentiment: 0.1061, Negative Sentiment 0.0424
nClouds Achieves AWS Data and Analytics Competency Status
A recent press release states, “nClouds (www.nclouds.com), a provider of Amazon Web Services (AWS) and DevOps consulting and implementation services and a managed service provider (MSP), announced today that it has achieved AWS Data and Analytics Competency status. The designation recognizes that nClouds has demonstrated technical proficiency and proven customer success in big data-related solutions. nClouds is a Premier Consulting Partner in the…
2020-04-07 07:10:55+00:00 Read the full story…
Weighted Interest Score: 3.6245, Raw Interest Score: 2.0274,
Positive Sentiment: 0.3578, Negative Sentiment 0.0596
Your Friendly Neighborhood AutoML-Empowered Data Scientist
Automation-focused machine learning (AutoML) has the power to dramatically upscale AI at your organization. With AutoML tools, organizations can unlock valuable new business insights, embed advanced AI capabilities in applications, and empower data scientists and nontechnical experts alike to build predictive models rapidly.
Faster than a speeding GPU, more powerful than a neural network, your AutoML-empowered data scientist can save the day.
AutoML automates repetitive, tedious, and time-intensive tasks that eat up a lot of data scientists’ time. Endowed with this technology, your super data scientists can iterate faster, try more features and algorithms, and tackle more priority projects. New superpowers, like the ability to build deep learning models for image recognition and natural language understanding, once the exclusive purview of a select few data scientists, will be in reach for the many.
2020-04-07 17:14:02-04:00 Read the full story…
Weighted Interest Score: 3.4633, Raw Interest Score: 1.9381,
Positive Sentiment: 0.3126, Negative Sentiment 0.1250
Predictive Analytics with Machine Learning & Data Mining (Course UT)
Evaluate data-driven business intelligence challenges and tools, such as data mining and machine learning techniques. Apply data-driven intelligence to improve decisions and estimate the expected impact on performance. Prepare to analyze unprecedented volumes of rich data to predict the consequences of alternative courses of action and guide decision-making. Discuss data-driven business intelligence challenges and tools like data mining and machine-learning techniques.
2020-05-13 00:00:00 Read the full story…
Weighted Interest Score: 3.1447, Raw Interest Score: 2.3772,
Positive Sentiment: 0.0792, Negative Sentiment 0.0792
SimCorp Launches Datacare Holistic Managed Data Service
SimCorp, a leading provider of investment management solutions and services to the global financial services industry, announces the launch of Datacare, a new managed data service for the global buy side. Developed in collaboration with Zurich Insurance Group (Zurich) and global buy-side institutions from the SimCorp Gain client community, Datacare* combines state-of-the-art technology and a managed service, providing a highly automated, multi-as…
2020-04-07 01:46:04+00:00 Read the full story…
2020-04-06 00:00:00 Read the full story…
Weighted Interest Score: 3.0614, Raw Interest Score: 1.9940,
Positive Sentiment: 0.6445, Negative Sentiment 0.1813
Big data in the water industry: How does it provide big value?
Water treatment is highly resource-intensive and typically relies on equipment that can be expensive or difficult to maintain due to the harsh conditions in water treatment plants. As a result, any opportunity to improve maintenance strategies or cut back on resource use can provide significant advantages.
At the same time, the rise of Industry 4.0 has enabled data collection at higher speeds and greater volumes than ever before. This is also known as “big data.” There is a wide range of applications for these massive data sets — like the ability to find new efficiencies, optimize processes and create more accurate forecasting and predictive models. All of these applications can be leveraged to provide big value for utilities and water treatment businesses.
Here are some of the most significant benefits that big data can offer the water industry.
2020-04-07 10:47:28+00:00 Read the full story…
Weighted Interest Score: 2.8197, Raw Interest Score: 1.5832,
Positive Sentiment: 0.4674, Negative Sentiment 0.4071
COVID-19 Is Going To Affect The Data Centre Market In Southeast Asia
A recent report stated that the data centre market in Southeast Asia is expected to grow at a CAGR of over 6% during the period 2019–2025. According to a report, COVID-19 is going to affect the data centre market in Southeast Asia, which is witnessing growth due to the increased interest from giant cloud providers such as Google, AWS, and Alibaba to open cloud regions. The report clarified that the increasing adoption of cloud-based services would be a key driver for the data centre market in the coming years. Alongside, the rising penetration of the internet is likely to aid the use of smart devices in this region.
Further, it stated that the impact of emerging technologies like big data, IoT, artificial intelligence, and virtual reality would also play a significant role in affecting data centre market growth in other southeast countries after 2020. In fact, the majority of colocation data centre providers are involved in the construction of hyperscale data centres to colocate space to cloud service providers. Case in point, in Southeast Asia, Singapore is a mature market and has been accounted for as the primary revenue generator of the APAC region. The list is then followed by Indonesia, Malaysia, Thailand, and Vietnam.
2020-04-08 07:59:38+00:00 Read the full story…
Weighted Interest Score: 2.6687, Raw Interest Score: 1.6792,
Positive Sentiment: 0.1199, Negative Sentiment 0.0600
UK Plc Profits Predicted To Crash 75% As The Coronavirus Crisis Bites
Stock market sentiment has improved significantly this week. The profit warnings and the dividend cuts have kept on coming, though. Even if covid-19 infection rates continue to cool all over the world, newsflow from across global share markets will remain extremely hairy for a long time. According to Link Group, the rot had set in for UK-listed stocks even before the coronavirus tragedy emerged. In a report released today it says that earnings were in “steep decline” before the outbreak and that the January-March period represented the third consecutive quarter of profits decline, even stripping out the covid-19 impact.
The financial data giant says that a mere 42% of British companies reported rising annual earnings in the first quarter, the lowest rate since all the way back in 2009. Link Group comments that “the UK stock market has lagged behind its peers in recent times, dogged by sluggish economic growth, political uncertainty, and an unfavourable sector mix.” It adds that “UK profits have been weak too.”
2020-04-07 00:00:00 Read the full story…
Weighted Interest Score: 2.5180, Raw Interest Score: 1.3407,
Positive Sentiment: 0.1635, Negative Sentiment 0.3597
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