Alternative Data News. 26, February 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.
A Scalable Prediction Engine for Automating Structured Data Prep | Ihab Ilyas
Ihab Ilyas is a professor of Computer Science at the University of Waterloo and co-founder of Tamr.
“Data scientists spend big chunk of their time preparing, cleaning, and transforming raw data before getting the chance to feed this data to their well-crafted models. Despite the efforts to build robust predication and classification models, data errors still the main reason for having low quality results. This massive labor-intensive exercises to clean data remain the main impediment to automatic end-to-end AI pipeline for data science. In this talk, I focus on data prep and cleaning as an inference problem, which can be automated by leveraging modern abstractions in ML. I will describe the HoloClean framework, a scalable prediction engine for structured data.”
Markets finally reacting to Corona Virus and Google search auto-complete can’t help but reveal how its users are reacting!!
CloudQuant Thoughts : Markets have their largest two day drop in years and the reaction of ordinary investors is totally expected but still very, very interesting. If you are not a broker with access to retail flow then how do you know what the small trader is thinking and when? Is it Stocktwits, is it by crawling CNBC’s subtitles? If you come up with your own unique way of finding the signal then you have unique Alpha.
Leaked Document Shows How Big Companies Buy Credit Card Data on Millions of Americans
Yodlee, the largest financial data broker in the U.S., sells data pulled from the bank and credit card transactions of tens of millions of Americans to investment and research firms, detailing where and when people shopped and how much they spent. The company claims that the data is anonymous, but a confidential Yodlee document obtained by Motherboard indicates individual users could be unmasked.
2020-02-19 15:56:01+00:00 Read the full story…
Weighted Interest Score: 2.6141, Raw Interest Score: 1.2432,
Positive Sentiment: 0.0950, Negative Sentiment 0.1209
CloudQuant Thoughts : “Let me be blunt. This is bullshit anonymization” Nicholas Weaver, a senior researcher at the International Computer Science Institute at UC Berkeley. This comes as no surprise to most Data Scientists!
ESG – Environmental, Social and Governance
CloudQuant Thoughts : Today the WSJ have an article titled “Investors Cast Off Coal Stakes, Miners Rely on a Few Big Funds”. ESG is the hot Alternative Data right now. CloudQuant provide services to review and test Alternative Data sets. We produce white papers where we investigate whether or not the data has demonstrable Alpha, we give access to the code and the data used to produce the white paper (I know! – Crazy!). Head over to our Data Catalog for more information.
Recent Moves in Sell-Side ESG Research: Credit Suisse & JPMorgan • Integrity Research
Two major investment banks, Credit Suisse and JPMorgan, have recently experienced senior personnel changes in their research teams overseeing environmental, social and governance (ESG) research.
Recent ESG Research Personnel Moves
Last month, US investment bank JPMorgan recently named Jean-Xavier Hecker and Hugo Dubourg as its new co-heads of ESG equity research for its Europe, Middle East and Africa (EMEA) region. Hecker joins JPMorgan following more than 2 ½ years as an SRI analyst at Exane BNP Paribas and close to 4 years as a corporate governance and SRI analyst at …
2020-02-24 02:30:01+00:00 Read the full story…
Weighted Interest Score: 3.1308, Raw Interest Score: 1.9521,
Positive Sentiment: 0.0368, Negative Sentiment 0.0368
ESG Research Set For Significant Growth
Environmental, social and governance research remains one of the few growth areas in the research market according to consultancy Integrity Research.
Michael Mayhew, founder of Integrity Research, said in a blog that ESG has been one of the fastest growing segments of sell-side equity research in the past few years and he expects this to continue to grow for the foreseeable future.
“We would not be surprised to see significant ESG…
2020-02-24 14:37:28+00:00 Read the full story…
Weighted Interest Score: 3.6182, Raw Interest Score: 2.2139,
Positive Sentiment: 0.1862, Negative Sentiment 0.1655
Australian investors warm to sustainable themes
Australia’s mutual fund assets in sustainable investments surged 23.0 per cent year-on-year (y-o-y) to AUD66.8 billion (USD46.7 billion) in 2019, and gathered AUD1.2 billion in inflows over the same period, Cerulli Associates’ estimates show.
This could be attributed to Australian investors’ increased awareness of climate change. According to the Lowy Institute Poll 2019, for the first time in its 15-year history, climate change topped the list …
2020-02-26 00:00:00 Read the full story…
Weighted Interest Score: 2.8713, Raw Interest Score: 1.5692,
Positive Sentiment: 0.1538, Negative Sentiment 0.2462
Defining ESG Investing and Understanding Its Uses
Photo: ESB Professional/Shutterstock
Advisors embracing or considering environmental, social and governance focused investing should understand the different definitions used by asset managers, index providers, stock and bond issuers as well as their clients.
“ESG is not just about values but includes the underlying financial material risks within an industry,” said Mona Naqvi, senior director, ESG, at S&P Dow Jones Indices, a panelists at the …
2020-02-24 00:00:00 Read the full story…
Weighted Interest Score: 2.5574, Raw Interest Score: 1.5155,
Positive Sentiment: 0.1184, Negative Sentiment 0.0710
ESG proposals at Amazon signal ongoing concerns
New slate of ESG proposals at Amazon signal ongoing shareholder concerns
Investors say proposals citing health and safety risks to workers, liabilities related to third-party sellers, and due diligence around the sale of surveillance tech, among other issues, indicate the company is failing to adequately manage risks.
Get Our Activist Investing Case Study! Get the entire 10-part series on our in-depth study on activist investing in PDF. Save it…
2020-02-25 17:41:48+00:00 Read the full story…
Weighted Interest Score: 2.1791, Raw Interest Score: 1.2938,
Positive Sentiment: 0.2043, Negative Sentiment 0.3064
Data Architecture and Data Science: What is the Intersection?
Data Science, in practice, should ultimately combine the best practices of information technology, analytics, and business. On the other hand, Data Architecture enables data scientists to analyze and share data throughout the enterprise for strategic decision-making. Thus, without a sound Data Architecture in place, data scientists will remain severely handicapped in their abilities to develop and productionize data models. This is the primary point of intersection between Data Architecture and Data Science.
However, both Data Science and Data Architecture specialists need to have a sound understanding of business issues before they can design a model-development and testing environment for business use. An IBM developer explores the architectural thinking embedded in Data Science.
According to Science Direct, Data Architecture accomplishes the two following goals for the enterprise Data Science teams:
- It allows “strategic development” of data models by “insulating the data from the business as well as the technology process.”
- It provisions an “environmental foundation” for ensuing model-development activities with approval from the data owner.
Thus, it is logical to assume that the data architect and the data scientist play complementary roles in an enterprise Data Science team.
2020-02-26 08:35:54+00:00 Read the full story…
Weighted Interest Score: 4.9917, Raw Interest Score: 2.4966,
Positive Sentiment: 0.1379, Negative Sentiment 0.0552
“Obviously AI” Rolls Out First Natural Language-Powered Machine Learning Platform for Predicting Outcomes from Any Data
Data at organizations can be incredibly siloed, difficult to access, and overwhelming for thousands of business users across the globe. From finding a list of items in a haystack of data, to running complex predictive analytics, business users often have to wait for weeks for data engineers to get a single question answered. Today, with the public launch of Obviously AI, a no-code platform designed to put the power of machine learning and analytics in the hands of non-technical business users, this solution can enable anyone to access crucial information and data predictions, simply by asking questions in natural language.
Obviously AI’s no-code tool is extremely easy to use with results on any query returned in under a minute. Users simply upload their dataset from CSV, databases or CRMs and then get a Google-like search bar to ask a question in natural language. For predictive questions, such as “Which customers are likely to cancel their subscriptions?” the platform will understand what the user is asking, find the right data, and build a machine learning algorithm on the fly. It also shows you exactly what factors drove your results, so you don’t have to guess how it got them. Similarly, the platform can answer analytical questions that look for existing patterns in data, such as “What is the average daily foot traffic for my retail stores?” Users do not need any familiarity with writing complex SQL queries or working with programming languages to code regressions, neural networks and other ML algorithms.
2020-02-25 08:05:32+00:00 Read the full story…
Weighted Interest Score: 4.5292, Raw Interest Score: 2.1505,
Positive Sentiment: 0.1792, Negative Sentiment 0.4779
SambaNova Systems raises $250 million for software-defined AI hardware
The infrastructure required to handle AI workloads is often as complex as it is sprawling, but a cottage industry of startups has emerged whose focus is developing solutions for end customers. SambaNova Systems is one such startup — the Palo Alto, California-based firm, which was founded in 2017 by Rodrigo Liang and Stanford professors Kunle Olukotun and Chris Ré, provides systems that run AI and data-intensive apps from the datacenter to the edge. In a reflection of investors’ voracious appetite for the market, it today announced that it’s raised $250 million in series C funding.
“Raising $250 million in this funding round with support from new and existing investors puts us in a unique category of capitalization,” said CEO Liang, a veteran of Sun Microsystems and Oracle. “This enables us to further extend our market leadership in enterprise computing.”
2020-02-25 00:00:00 Read the full story…
Weighted Interest Score: 3.9004, Raw Interest Score: 2.0033,
Positive Sentiment: 0.2956, Negative Sentiment 0.0657
StreamSets Expands Databricks Partnership With New Connector for Delta Lake
“StreamSets®, provider of the industry’s first DataOps platform, today announced an expansion of its partnership with Databricks by participating in Databricks’ newly launched Data Ingestion Network. As part of the expanded partnership, StreamSets is offering additional functionality with a new connector for Delta Lake, an open source project that provides reliable data lakes at scale. With it, users can configure their pipelines to write data from any source moving in batch or streaming mode directly into Delta Lake. Now, data teams can deliver all of their data in a shorter time frame, driving BI, analytics and ML. Today, companies require systems for diverse data applications like real-time monitoring, machine learning and data science — and that can process unstructured data like text, images, video and audio. A decade ago, data lakes replaced data warehouses as the best repositories for this raw data; however, they neither support transactions nor enforce data quality. In addition, they lack consistency, making it almost impossible to mix batch and streaming jobs and appends and reads.”
2020-02-25 08:10:00+00:00 Read the full story…
Weighted Interest Score: 3.6474, Raw Interest Score: 1.8763,
Positive Sentiment: 0.2535, Negative Sentiment 0.1521
The Rising Value of Data in Financial Markets
‘New oil’ or ‘new gold’ are just some of the phrases used to describe the value of data in financial markets. And rightly so. Data fuels every aspect of the trading process. From the very beginning, trading has always been about information. Whoever has the best and the fastest information gains the edge.
Today, traders are also challenged with managing the sheer amount of data in financial markets. The edge that traders gain now is all about who can consume and make sense of the data the fastest by leveraging technologies such as artificial intelligence. In the second of three reports on the trading desk of the future, Refinitiv partners with Greenwich Associates to explore data’s impact on financial markets over the next three to five years, including which types of data will be most valuable, who will provide that data, and how traders expect to use it.
2020-02-13 00:00:00+00:00 Read the full story…
SimCorp launches new machine learning initiative with start-up, Alkymi, targeting institutional investment challenges
SimCorp, a leading provider of investment management solutions and services to the global financial services industry, today announces a partnership with New York based start-up, Alkymi, to launch a new Machine Learning (ML) initiative. It’s arrival comes as institutional investors raise a number of data concerns, including the ability to quickly extract insights from unstructured data, for faster, more informed decision-making.
2020-02-26 00:00:00 Read the full story…
Weighted Interest Score: 3.4483, Raw Interest Score: 2.2040,
Positive Sentiment: 0.4271, Negative Sentiment 0.1367
Business – Integrating data is getting harder, but also more important
GEEKS ARE not known for being poets. But sometimes even they have a way with words, for example when trying to describe the main challenge of dealing with data. It is the search, they say, for “a single version of the truth”.
This also nicely describes what has been the goal of corporate information technology since it emerged 60 years ago. And the adage encapsulates the main tension for businesses in the data economy: finding digital truth—tha…
2020-02-20 00:00:00 Read the full story…
Weighted Interest Score: 3.0650, Raw Interest Score: 1.4636,
Positive Sentiment: 0.1591, Negative Sentiment 0.1803
Is artificial intelligence Sexist? The answer is Yes And No
With advanced research happening in the realm of artificial intelligence (AI), the technology is poised to become smarter than its human creators. But until that day, it is like to harbour sexist, racist and even homophobic tendencies – all inherited from its makers’ social and cultural biases.
This was discussed at some length last year at Rising, one of the country’s biggest gatherings of women trailblazers in the fields of data science and AI. Held on March 8 to commemorate Women’s Day, the one-day event hosted more than 250 participants and featured more than 15 sessions led by industry leaders, mostly women.
One of the speakers on the occasion, Director of Citi Saraswathi Ramachandra, provoked a discussion around a hotly debated topic – Is AI sexist. According to her, this cannot be firmly answered in the affirmative since AI models can only respond to what it has learned. This means that the real culprit is essentially the training dataset we feed it, and not the technology by itself.
2020-02-25 14:30:00+00:00 Read the full story…
Weighted Interest Score: 3.0166, Raw Interest Score: 0.9555,
Positive Sentiment: 0.1257, Negative Sentiment 0.2012
Buy Apple and Amazon? Now May Be Just the Time — ICYMI (In Case you Missed It)
The U.S. stock market is in a tizzy as the coronavirus could become a pandemic. That means the economic shock may last longer than most of us expected. And that in turn hurts in the shorter term but could create favorable revenue and earnings comparisons for 2021. This would be especially true for big tech. Institutional funds have been buying up big tech stocks, which is one piece of evidence that the sector has significant upside.
U.S. stocks broadly are closer to a correction – a 10% drop from record highs. The S&P 500 is 8% lower than its all-time high, reached last week.
The coronavirus is threatening global supply chains, many of which originate in China and have been mostly shut down. The spread of the virus to Italy and other Asian countries is worsening the problem. This may bleed into the U.S. if and when American importers can’t access goods from abroad to meet demand at home.
2020-02-25 21:18:46+00:00 Read the full story…
Weighted Interest Score: 2.9284, Raw Interest Score: 1.3498,
Positive Sentiment: 0.1373, Negative Sentiment 0.2745
Interested in Data Science? Here’s a Breakdown of Data, ML Platforms
Data science is a rapidly growing area of focus for many companies, and for good reason: The right kind of data, analyzed correctly, can yield insights that translate into better and more profitable strategies. That’s why “data scientist” has become a much sought-after role for companies to fill, with high salaries and generous benefits to match.
Once you begin your data-scientist journey, you very quickly d…
2020-02-24 00:00:00 Read the full story…
Weighted Interest Score: 2.9257, Raw Interest Score: 1.8256,
Positive Sentiment: 0.3363, Negative Sentiment 0.1681
Lesser-Known AI-Based Research Labs In India
In order to accomplish breakthroughs in the space of artificial intelligence, it is crucial for researchers to mitigate a plethora of existing challenges. Due to this reason, researchers must have access to a state-of-the-art laboratory to have a free hand in terms of researching. Consequently, companies are rigorously developing AI research labs to facilitate exceptional infrastructure across the country.
In India, the artificial intelligence space has buzz primarily by big giants like Google, Bosch, Mercedes, Microsoft, Accenture and PayPal, to name a few. However, there are a number of lesser-known players who are providing a great contribution to artificial intelligence (AI) with the help of their AI labs. In this article, we will have a look at a few of the lesser-known companies with AI labs.
2020-02-25 10:30:00+00:00 Read the full story…
Weighted Interest Score: 2.7714, Raw Interest Score: 1.5430,
Positive Sentiment: 0.2919, Negative Sentiment 0.0626
INSOFE Launches PGP (Honours) in Data Science, in Collaboration with IIT Ropar and CICE, Canada
INSOFE teamed up with IIT Ropar and CICE, Carleton University to offer – “PGP (Honours) in Data Science”, a specialization program that will prepare students with data science, application architecture, and engineering skills.
There is a great demand for engineers who can not only build models but actually scale and deploy complex AI applications. The salaries of such engineers are roughly twice that of data scientists who build offline models which itself is 50-70% higher than software engineers….
2020-02-26 13:00:00+00:00 Read the full story…
Weighted Interest Score: 2.6932, Raw Interest Score: 1.4052,
Positive Sentiment: 0.3123, Negative Sentiment 0.0781
How To Start A Career In Data Science
A data scientist is someone who helps an organisation to make critical decisions through data analysis, modelling, visualisation, among others. According to the survey reports, Data Science and analytics ecosystem has been witnessing an overall growth in the number of jobs with India contributing to 6% of open job openings worldwide.
Currently, the total number of analytics and data science job positions available are more than 90,000 and compar…
2020-02-26 05:30:00+00:00 Read the full story…
Weighted Interest Score: 2.5253, Raw Interest Score: 1.6456,
Positive Sentiment: 0.2161, Negative Sentiment 0.1828
How To Learn A Programming Language As Fast As Possible
Whether it is for a newly emerging language like Dart, Swift or some of the most established ones like Python, R, etc., the process of learning a new programming language is daunting. People learn programming languages for various reasons like getting a certification for a job hunt, building a project, among others. People want to learn a programming language as fast as possible. However, learning a programming language quickly doesn’t mean that …
2020-02-25 13:30:00+00:00 Read the full story…
Weighted Interest Score: 2.2623, Raw Interest Score: 1.4632,
Positive Sentiment: 0.1829, Negative Sentiment 0.0914
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