Alternative Data News. 14, October 2020

Alternative Data Newsletter

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.

Animation of Coronavirus spread in the UK – 1st Feb to 9th Oct

This animation shows the number of positive COVID-19 cases confirmed across the UK (and Isle of Man) from the start of February until the 9th of October, in each lower tier local authority area, adjusted for the population of the area.

Tools used:

Custom Ruby scripts for processing the data
Leaflet.js for the visualisation itself
Google Chrome to generate screenshots
ffmpeg to convert the screenshots into an animation
Data sources:

2020-10-10 Read the Full Story…

CloudQuant Thoughts : Not a lot of great posts in Data Is Beautiful this week and I had to edit the one above to speed it up and pause on the last few days. No doubt about it, the virus is back with a vengeance in the UK/Europe and the US was a week or two behind them during the first outbreak…

Aqua Digital Rising Taps Gold-i for Listing Unique Indices

The prominent multi-asset liquidity management and fintech provider Gold-i has announced a partnership with start-up Aqua Digital Rising, a new alternative asset investment platform that allows investments in indices based on human beings, according to a press release.

The partnership will allow Aqua Digital’s Contracts for Difference (CFDs) to be integrated into Gold-i’s Matrix multi-asset liquidity management platform. The integration will add a new asset class to Gold-i’s offering, a company which has been known for pushing boundaries in the industry. The new CFDs are on track to launch in January 2021, essentially offering investors to trade on the success of individuals, from sports people and celebrities through to social media influencers and politicians, according to the companies.

Tom Higgins, CEO, Gold-i comments: “I have always been motivated by innovation – it is at the heart of all our developments at Gold-i – and when I heard about Aqua Indices, I was excited by such a revolutionary concept. Financial institutions are continually looking at ways to increase revenues by diversifying and Aqua Indices presents the ideal opportunity. We are thrilled to be at the forefront of this, enabling our clients to have access to a next generation alternative asset class.”

2020-10-07 14:16:07+00:00 Read the full story…
Weighted Interest Score: 3.9640, Raw Interest Score: 1.9820,
Positive Sentiment: 0.4805, Negative Sentiment 0.0601

CloudQuant Thoughts : Interesting idea but quite how are they going to execute? Is it going to be like, the Hollywood Stock Exchange?

Where Have All the Airplanes Gone?

My 4-year-old pointed to the sky one day and asked, why don’t we see airplanes flying over our house nowadays? (10 Little Airplanes (1) is his favorite counting rhyme). I showed him the below picture and explained that airplanes are grounded due to COVID19. He started counting the aircraft in the picture. Well, what’s your count?

As a Data Science practitioner, a problem statement surfaced – Can we count the number of airplanes parked across various locations globally. With help from my colleague(2), we set out to stitch a quick but efficient deep learning solution that can count airplanes from satellite images. The solution had to perform two operations – Object detection and classification.

  1. Getting the Data
  2. Preparing the Data
  3. Building the Model
  4. Result Time

2020-10-13 09:30:46+00:00 Read the full story…
Weighted Interest Score: 2.9199, Raw Interest Score: 1.1804,
Positive Sentiment: 0.1450, Negative Sentiment 0.1035

CloudQuant Thoughts : Always nice to see the process from ‘data idea’ to ‘execution’.

Microsoft partners with Team Gleason to build a computer vision dataset for ALS

Microsoft and Team Gleason, the nonprofit organization founded by NFL player Steve Gleason, today launched Project Insight to create an open dataset of facial imagery of people with amyotrophic lateral sclerosis (ALS). The organizations hope to foster innovation in computer vision and broaden the potential for connectivity and communication for people with accessibility challenges.

Microsoft and Team Gleason assert that existing machine learning datasets don’t represent the diversity of people with ALS, a condition that affects as many as 30,000 people in the U.S. This results in issues accurately identifying people, due to breathing masks, droopy eyelids, watery eyes, and dry eyes from medications that control excessive saliva.

Project Insight will investigate how to use data and AI with the front-facing camera already present in many assistive devices to predict where a person is looking on a screen. Team Gleason will work with Microsoft’s Health Next Enable team to gather images of people with ALS looking at their computer so it can train AI models more inclusively. (Microsoft’s Health Next team, which is within its Health AI division, focuses on AI and cloud-based services to improve health outcomes.) Participants will be given a brief medical history questionnaire and be prompted through an app to submit images of themselves using their computer.

2020-10-12 00:00:00 Read the full story…
Weighted Interest Score: 2.7801, Raw Interest Score: 1.1292,
Positive Sentiment: 0.2754, Negative Sentiment 0.2479

CloudQuant Thoughts : Before long we will be walking down the street observed by cameras galore, watching our gate, noting that we seem to be struggling to walk.. diagnosing the cause.. sending suggestions via personalized advertising boards (Minority Report) or just a buzz on your iWatch..   “Need New shoes? Need Yoga? Or are you showing the first signs of ALS?”

CloudQuant Increases Liberator’s Speed & Reach

CloudQuant today rolled out a major update to their industry leading Liberator/Rosetta APIs.

This technical release provides Improved Performance, Error Feedback, and Column Level Filtering to the increasing number of CloudQuant clients using our external API, as well as providing a boost to CloudQuant’s research tools – CQ AI, CQ Mariner, and CQ Explorer.

Our API enables external users to seamlessly integrate Liberator’s Power and Speed into their own environments. CloudQuant’s Liberator and suite of Technological Products dramatically cut the time from data acquisition to profit!

2020-10-04 00:00:00 Read the full story…

CloudQuant Thoughts : Our Liberator API is at the center of our Data Fabric, it provides data to all of our clients and all of our products. As such we are constantly improving it. Liberator’s ability to deliver precise Alternative Data into any user’s platform in a simple and clear manner is a major driver of our goal of dramatically cutting the time it takes to go from Raw Data to Profit. Liberator has also qualified for a Benzinga Award Nomination!

ESG Section

CloudQuant provide Alternative Data services to major players and provide marketing services for data vendors. One such vendor has an alternative data set for ESG data. As part of our service offering we can review the dataset using our backtesting system and produce results, code to reproduce the results and white papers on how we achieved the results. For more information head over to our Data Catalog.

BNP Paribas Asset Management Launches First Blue Economy ETF (Sustainable use of Ocean Resources)

  • BNP Paribas Asset Management (‘BNPP AM’) announces the launch of the first blue economy ETF (exchange-traded fund), BNP Paribas Easy ECPI Global ESG Blue Economy UCITS ETF. The ETF is listed on Xetra and Euronext and has a TER of 0.30%.
  • The fund aims to invest in companies from the global developed market which are the best placed to seize opportunities provided by the sustainable use of ocean resources.
  • It tracks the ECPI Global ESG Blue Economy index, an equally-weighted index providing exposure to 50 large caps selected for their sustainable participation in the blue economy. The index conforms to UN Sustainable Development Goal (‘SDG’) 14: ‘Life below water’.

Following the launch of the first circular economy ETF in May 2019, BNPP AM is expanding its range of sustainable thematic investments through the launch of the first ETF based on the blue economy theme. The blue economy is defined by the World Bank as the sustainable use of ocean resources for economic growth, improved incomes and jobs, and healthy ocean ecosystems.

This new ETF replicates an index from ECPI, an index supplier specialising in ESG for 20 years, whose methodology is primarily based on the environmental, social & governance (ESG) criteria of listed companies globally. Companies are selected for their participation in the blue economy and listed according to five categories: coastal livelihood (protection, eco-tourism), energy & resources (offshore wind, marine biotech, wave & tidal), fisheries & seafood, pollution reduction (recycling/waste management, environmental services) and maritime transport. The equally-weighted index consists of those 50 companies with a positive ESG rating and with the largest market capitalisation within their category; it excludes notably, companies involved in systematic violations of the UN Global Compact principle and arms production, and companies that derive more than 10% of their revenues from tobacco, thermal coal extraction or unconventional oil & gas[2].

2020-10-14 04:59:35+00:00 Read the full story…
Weighted Interest Score: 5.3117, Raw Interest Score: 2.1940,
Positive Sentiment: 0.2992, Negative Sentiment 0.1247

Envestnet Links With Federated Hermes For Impact Portfolios

Envestnet, Inc. announces that Envestnet | PMC (PMC) has joined forces with Federated Hermes, Inc. to launch the Federated Hermes PMC Impact Portfolios. This new suite of model portfolios offers access to environmental, social, and governance (ESG) integrated investment strategies which can be customized to fit different tolerances for risk.

The Federated Hermes PMC Impact Portfolios consist of diversified model portfolios that are aligned with target allocation strategies across a seven-point risk spectrum. PMC, Envestnet’s Portfolio Management Consultants group, utilizes its proprietary capital markets assumptions and multi-factor due diligence process to evaluate and identify high-conviction impact strategies, and build the Federated Hermes PMC Impact Portfolios.

Reflecting the ongoing uptick in interest by investors in ESG strategies and products, the number of advisors utilizing impact portfolios on the Envestnet platform grew by 12 percent during the first six months of 2020. Usage of PMC’s impact and tax overlay solutions increased by 16 percent during the same period.

2020-10-14 06:23:30+00:00 Read the full story…
Weighted Interest Score: 4.6108, Raw Interest Score: 2.4596,
Positive Sentiment: 0.0674, Negative Sentiment 0.0674

Bloomberg to Offer MSCI ESG Research Data

New York, October 13, 2020 – Bloomberg announced today that MSCI’s ESG Ratings are now available via the Bloomberg Terminal. Bloomberg Terminal users can access this MSCI data and use it alongside Bloomberg’s broader functionality across the Terminal, complementing Bloomberg’s existing ESG data sets.

With MSCI ESG Ratings, investors can measure a company’s resilience to long-term, financially relevant ESG risks. By using a rules-based methodology to identify industry leaders and laggards, MSCI rates companies on a ‘AAA to CCC’ scale according to their exposure to ESG risks and how well they manage those risks relative to peers.

The addition of MSCI ESG data on the Bloomberg Terminal provides subscribers with a holistic view of company and issuer ESG performance in order to streamline their research and investment processes. Additionally, investors can supplement their current research processes by incorporating MSCI’s ESG Ratings into their existing ecosystem of Bloomberg equity, fixed income and portfolio analysis tools.

2020-10-13 09:00:28+00:00 Read the full story…
Weighted Interest Score: 4.0518, Raw Interest Score: 2.2228,
Positive Sentiment: 0.2814, Negative Sentiment 0.0281

MSCI ESG Research Data Offered On Bloomberg Terminal

Bloomberg announced that MSCI ESG Ratings by MSCI ESG Research LLC is now available via the Bloomberg Terminal. Bloomberg Terminal users can access this MSCI data and use it alongside Bloomberg’s broader functionality across the Terminal, complementing Bloomberg’s existing ESG data sets.

With MSCI ESG Ratings, investors can measure a company’s resilience to long-term, financially relevant ESG risks. By using a rules-based methodology to identify industry leaders and laggards, MSCI rates companies on a ‘AAA to CCC’ scale according to their exposure to ESG risks and how well they manage those risks relative to peers.

The addition of MSCI ESG data on the Bloomberg Terminal provides subscribers with a holistic view of company and issuer ESG performance in order to streamline their research and investment processes. Additionally, investors can supplement their current research processes by incorporating MSCI’s ESG Ratings into their existing ecosystem of Bloomberg equity, fixed income and portfolio analysis tools.

2020-10-14 05:13:17+00:00 Read the full story…
Weighted Interest Score: 3.8751, Raw Interest Score: 2.1529,
Positive Sentiment: 0.1794, Negative Sentiment 0.0000

Wall Street’s biggest banks are increasingly expecting a Biden-led blue wave as the election looms. Here’s how they say you should position your portfolio.

As Joe Biden’s lead in polls widens, Wall Street is warming to the prospect of a Democratic sweep in November.

Goldman Sachs and UBS recently advised clients to prepare for a shift to cyclical and value stocks from growth favorites, as a Biden victory would increase the odds of additional fiscal stimulus.

The yield curve could steepen as investors prepare for rising inflation and stronger economic growth, UBS add…
2020-10-10 00:00:00 Read the full story…
Weighted Interest Score: 3.9138, Raw Interest Score: 2.0292,
Positive Sentiment: 0.3488, Negative Sentiment 0.1902

Complete Guide To Handling Categorical Data Using Scikit-Learn

Dealing with categorical features is a common thing to preprocess before building machine learning models. In real-life data science scenario, it means that the dataset has an attribute stored as text such as days of the week(Monday, Tuesday,.., Sunday), time, colour(Red, Blue, …), or place names, etc.

Categorical features have a lot to say about the dataset thus it should be converted to numerical to make it into a machine-readable format. Focusing only on numerical variables in the dataset isn’t enough to get good accuracy. Often categorical variables prove to be the most important factor and thus identify them for further analysis. Most of the machine learning algorithms do not support categorical data, only a few as ‘CatBoost’ do.

There are a variety of techniques to handle categorical data which I will be discussing in this article with their advantages and disadvantages.

Identifying the two major types of Categorical Variables :

  • Nominal – These are variables which are not related to each other in any order such as colour (black, blue, green).
  • Ordinal – These are variables where a certain order can be found between them such as student grades (A, B, C, D, Fail).

The dataset I’m going to work with is the Melbourne housing price dataset from Kaggle. Let’s Explore the Dataset…

2020-10-14 11:30:22+00:00 Read the full story…
Weighted Interest Score: 2.5914, Raw Interest Score: 1.1365,
Positive Sentiment: 0.0729, Negative Sentiment 0.0874

IIT-Jodhpur Launches Undergraduate Programme in AI & Data Science

The Indian Institute of Technology Jodhpur is launching a new BTech programme in artificial intelligence and data science from the academic session 2020-21. The new undergraduate programme will have courses in computer science, mathematics, artificial intelligence, machine learning, data science, and their applications in various domains.

According to the institute, students, once opted for the course, will be able to take a specialisation in various areas including visual computing, socio-digital realities, language technologies, robotics, and artificial intelligence and others. In IIT-Jodhpur’s official release, it has been mentioned that, with the course, enrolling students will also have the option to take up MBA (tech) in their fifth year as a dual-degree option in the School of Management and Entrepreneurship.

2020-10-12 06:48:32+00:00 Read the full story…
Weighted Interest Score: 2.8288, Raw Interest Score: 1.6562,
Positive Sentiment: 0.3681, Negative Sentiment 0.0736

Sharp Venture Capitalists Make Remarkable Inroads With Alternative Data

Alternative data is not utilized nearly enough in data capital management. It can help you increase your returns in powerful ways.

The University of Hawaii reports that big data is shaking up the venture capital industry in unbelievable ways. Venture capitalists are finding new ways to leverage alternative data effectively for much higher yields.

Big data plays a role in shifting the risk-reward calculus in the favor of venture capitalists. Venture capital is a high risk, high reward game. To put it into perspective, 90% of new startups fail, which means that investors can …
2020-10-08 08:34:08+00:00 Read the full story…
Weighted Interest Score: 5.9046, Raw Interest Score: 2.4377,
Positive Sentiment: 0.3750, Negative Sentiment 0.2625

IISc Launches Advanced Program In Computational Data Science

The Indian Institute of Science (IISc) in association with TalentSprint has announced the launch of a ten-month Advanced Program in Computational Data Science.

This program will equip current and aspiring data scientists, along with data engineers, data analysts and data architects, the latest expertise to lead the workforce of the future. The advanced program will be led by a team of leading faculty and experts from an interdisciplinary background who will teach live and interactive online classes and mentor participants to solve data science problems.

The program will further allow enrollees to build a personal portfolio of data stories to showcase on their career profiles and allow them to connect with TalentSprint’s network of deep-tech professionals from across the world. The first cohort of the program will start in January 2021 and will be accepting 50 professionals from India, APAC and the Middle East.

2020-10-08 11:27:35+00:00 Read the full story…
Weighted Interest Score: 2.5442, Raw Interest Score: 1.3926,
Positive Sentiment: 0.3214, Negative Sentiment 0.1339

6 Lessons Learned in 6 Months as a Data Scientist

When transitioning into a Data Science career, a new mindset toward collaboration, data, and reporting is required. Learn from these recommendations on approaches you should consider to successfully develop into your dream job.

Since my title flipped from consultant to data scientist six months ago, I’ve experienced a higher level of job satisfaction than I would have thought possible. To celebrate my first half year in this engaging field, here are six lessons I’ve collected along the way.

  1. Read the arXiv paper
  2. Listen to podcasts for tremendous situational awareness
  3. Read GitHub Issues
  4. Understand the algorithm-hardware link
  5. Learn from the Social Sciences
  6. Connect data to business outcomes

2020-10-06 00:00:00 Read the full story…
Weighted Interest Score: 2.2311, Raw Interest Score: 1.2363,
Positive Sentiment: 0.3643, Negative Sentiment 0.3422

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