Alternative Data News. 29, 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 deaths per 100,000 by US county. 2 March- 26 April
The scale is linear by deaths per 100,000. The bars are colored according to the number of reported cases. So tall dark bars may be outliers.
The tallest bar show is for 280 deaths per 100,000 in Randolph, Georgia.
The Outlier in the North West is Toole, Montana – they’ve had 6 deaths for just 4,736 total population.
You can explore the data, and make your own maps with the hosted tool: https://covid.everdb.net/map/?mapId=LMEe77ZGWxTH2K7qJ
For instance, here it is showing absolute, not per-capita figures: https://covid.everdb.net/map/?mapId=28bypPqWtNsCb6xmQ
And a very different style 2D map of reported cases: https://covid.everdb.net/map/?mapId=MZd32r4DZMEKcrprH
The scripts I used to produce the data shown are available at: https://github.com/gunn/covid-19-scripts
The source of the data was the New York Times dataset combined with Census data.
I’ve posted the full source of the app here: https://github.com/gunn/covid-19-map (typescript, react, kepler.gl, pure-store)
2020-04-29 00:00:00 Jump to the Interactive Map…
CloudQuant Thoughts : Not a lot of Alternative Data News this week so we go to our old favorite sub Reddit Data Is Beautiful for this very nice chart by Arthur Gunn.
Covid-19 downturn will not stop ESG’s momentum, says Man Group
The trend towards responsible investing and ESG is likely to maintain its momentum despite the potentially far-reaching impact of the coronavirus crisis, according to new research by Man Group.
With climate change among the top policy challenges globally, ESG (environmental, social and governance) investment themes have become key components among some of the most successful hedge funds in recent years, with Sir Chris Hohn’s TCI Fund, Caxton Associates, JP Morgan, and Man Group emerging as major advocates.
Man, the London-headquartered, publicly-listed global hedge fund group, suggested in a research note on Wednesday that structural drivers favour the trend’s momentum over the longer-term.
Man Numeric, the firm’s US quantitative investing unit, has developed a set of ESG alpha signals using a range of data providers, which indicated responsible investing factors have helped bolster risk-adjusted returns in recent years.
2020-04-29 00:00:00 Read the full story…
Weighted Interest Score: 4.3976, Raw Interest Score: 2.0783,
Positive Sentiment: 0.1807, Negative Sentiment 0.2108
Taneja Joins Deutsche Bank to Head New ESG Group
White glove brokerage Deutsche Bank has announced a new group and several new hires.
Given the increased focus on Environmental, Social & Governance (ESG) matters from the firm’s investment bank clients, a dedicated Sustainable Finance team has been formed within Capital Markets as part of Deutsche Bank’s broader strategy to offer ESG products and solutions to all client groups.
Operating within the existing Capital Solutions & Sustainable Financing (CS&SF) group led by Boris Kopp, the new team will partner closely with a network of regional and sectoral ‘ESG champions’ to be announced in due course, while aligning with other IB and bank-wide initiatives to ensure a consistent messaging and approach.
Trisha Taneja heads the new group and joined from Sustainalytics as Head of Sustainable Finance. The team mandate is be a valuable resource available to clients and global coverage teams to better understand the impact of ESG on market access and business development.
“Being able to offer global clients further ESG product expertise, regulatory guidance and investor perspectives will be key a differentiator, opening the door to broader strategic dialogue and ensuring Deutsche Bank is viewed as market leader on this important subject,” said Henrik Johnsson, Global Co-Head of Capital markets and Co-Head of Investment Bank, EMEA, and Frazer Ross, Head of DCM syndicate, EMEA.
2020-04-28 18:14:22+00:00 Read the full story…
Weighted Interest Score: 2.9622, Raw Interest Score: 1.5832,
Positive Sentiment: 0.1532, Negative Sentiment 0.0000
CloudQuant Thoughts : With many firms tightening their belts during the downturn, it is interesting to note the continued prevalence of ESG in trading decisions. We have long championed ESG and if you head over to our Data Catalog page you will find information on some ESG data offered by G&S Quotient, we have reviewed the data, produced a white paper demonstrating its effectiveness and can supply code and data access so you can re-run (yes, reproducible results!) or perform your own tests.
Satellites help track food supplies in coronavirus era
As the coronavirus pandemic leads to anxiety over the strength of the world’s food supply chains, everyone from governments to banks are turning to the skies for help.
Orbital Insight, a California-based Big Data company that uses satellites, drones, balloons and cell phone geolocation data to track what’s happening on Earth, has seen inquiries about monitoring food supplies double in the past two months, according to James Crawford, founder and chief executive officer of the company.
“We’re helping supply chain managers, financial institutions, and government agencies answer questions they never thought they would have to ask,” Crawford said in a phone interview.
Orbital has received funding in the past from Bloomberg Beta, a venture-capital unit of Bloomberg LP.
The coronavirus outbreak has triggered a fresh surge in demand for alternative data to shed light on how the pandemic is impacting industries and trade across the globe. That’s especially important as multiple government lockdowns and tighter restrictions on the movement of people and goods upend supply chains and logistics everywhere from Asia to Europe and the Americas.
2020-04-29 00:00:00 Read the full story…
CloudQuant Thoughts : The risks to food stocks as logistics and supply chains break down are of increasing concern. With 37 mile long Truck Traffic jams in Europe and a key Rice port in the Philippines becoming backed up, the world’s distribution system is at risk of seizing up. When you add in non-food logistics issues like the recent oil glut that has resulted in dozens of oil tankers parked off the coast of California you begin to see how difficult it may be to restart this world wide machine.
Top Machine Learning Books Made Free Due To COVID-19
Since e-learning is on the rise because of social distancing, the data science community earlier offered free online courses and now provides free e-books. While online data science courses are useful, books deliver structured as well as an in-depth understanding of the techniques. Reading books has its own advantages as it keeps you focused while eliminating distractions that your witness in online learning.
Springer Nature, popularly known for publishing books on science, business, and data science, has released numerous machine learning books for free. However, the below list only contains the most popular machine learning related books.
2020-04-29 10:30:00+00:00 Read the full story…
Weighted Interest Score: 3.6249, Raw Interest Score: 2.3462,
Positive Sentiment: 0.1731, Negative Sentiment 0.0962
NatWest Markets picks Dataiku machine learning platform
The markets business of UK bank NatWest is rolling out a data science and machine learning platform from AI specialist Dataiku, with the goal of deepening collaboration between technical staff and front office users.
NatWest Markets, which offers risk management, trading solutions and debt financing to the bank’s customers, has already developed a host of digital self-service applications.
With Dataiku it will now use its centralised data platform to drive collaboration between its technical and front office users, powering self-service analytics and ensuring that machine learning models are put into production as efficiently as possible.
2020-04-29 09:19:37+00:00 Read the full story (at Markets Media)…
2020-04-29 00:01:00 Read the full story (at FinExtra)…
Weighted Interest Score: 5.8784, Raw Interest Score: 3.0893,
Positive Sentiment: 0.4030, Negative Sentiment 0.0000
How Can Data Science-as-a-Service Help Your Organization?
If your business is struggling to reduce operational costs during the ongoing economic crisis or maintain the efficiency of services or the quality products, then Data Science as a Service (DSaaS) should be used to solve these issues.
DSaaS is an ideal choice for businesses to manage without a large team of data scientists and analysts in-house. It provides companies access to analytics resources for particular data science demands without much expense on building such teams from scratch.
Companies gain advantages based on their capability to cause data-driven decisions more efficiently and faster than their opponents. Data solely gives limited value to companies without the expertise, tools, and knowledge to comprehend what questions to ask, how to reveal the right patterns, and the skills to make forecasts that point to profitable action.
2020-04-28 06:30:43+00:00 Read the full story…
Weighted Interest Score: 3.6099, Raw Interest Score: 1.9382,
Positive Sentiment: 0.3155, Negative Sentiment 0.0902
A Machine Predicts My Next Sentence
Using Docker and TensorFlow for text generation with an RNN
- Text Generation
2020-04-29 01:31:03.880000+00:00 Read the full story…
Weighted Interest Score: 3.3309, Raw Interest Score: 1.4840,
Positive Sentiment: 0.1298, Negative Sentiment 0.0927
Time Series Forecasting with Graph Convolutional Neural Network
Store Item Demand Forecasting combining Graph and Recurrent Structures
Time Series forecasting tasks can be carried out following different approaches. The most classical is based on statistical and autoregressive methods. More tricky are the algorithms based on boosting and ensemble where we have to produce a good amount of useful handmade features with rolling periods. On the other side, we can find neural network models that enable more freedom in their development, providing customizable adoption of sequential m…
2020-04-29 01:26:44.426000+00:00 Read the full story…
Weighted Interest Score: 2.9175, Raw Interest Score: 1.5561,
Positive Sentiment: 0.1610, Negative Sentiment 0.1073
Machine Learning in Python: Main Developments and Technology Trends in Data Science, Machine Learning, and Artificial Intelligence
Smarter applications are making better use of the insights gleaned from data, having an impact on every industry and research discipline. At the core of this revolution lies the tools and the methods that are driving it, from processing the massive piles of data generated each day to learning from and taking useful action. Deep neural networks, along with advancements in classical machine learning and scalable general-purpose graphics processing unit (GPU) computing, have become critical components of artificial intelligence, enabling many of these astounding breakthroughs and lowering the barrier to adoption. Python continues to be the most preferred language for scientific computing, data science, and machine learning, boosting both performance and productivity by enabling the use of low-level libraries and clean high-level APIs. This survey offers insight into the field of machine learning with Python, taking a tour through important topics to identify some of the core hardware and software paradigms that have enabled it. We cover widely-used libraries and concepts, collected together for holistic comparison, with the goal of educating the reader and driving the field of Python machine learning forward.
2020-04-29 00:00:00 Read the full story…
Weighted Interest Score: 2.5641, Raw Interest Score: 2.1774,
Positive Sentiment: 0.4839, Negative Sentiment 0.1613
HCL To Set Up Data Analytics Center For Tamil Nadil (India) Govt To Fight COVID-19
Many global companies are making an effort to ease up the wrath that COVID-19 has brought to the world. In a recent development, the government of Tamil Nadu has partnered with HCL to set up a Data Analytics Center to strengthen the state’s disaster management efforts.
Tamil Nadu’s Disaster Management Center is responsible for the overall management of disasters across the entire state. With over 1000 coronavirus cases, the state is one of the worst affected in the country and the government is taking all the necessary measures to bring down the numbers.
2020-04-28 13:06:25+00:00 Read the full story…
Weighted Interest Score: 2.2401, Raw Interest Score: 1.6061,
Positive Sentiment: 0.0845, Negative Sentiment 0.2959
Data Analyst Interview Questions: Show Off Your Experience
Data analyst interview questions focus not only on your analytical skills (always useful in a data analyst job) but also your “soft skills” such as communication and empathy. Keep that in mind if you’re applying for data analyst positions.
Over the past several years, data analysts have become only more vital to companies’ long-term strategies. That means the typical data analyst job features a variety of tasks; depending on the firm and its mission, an analyst could find themselves writing algorithms in the morning and communicating with the C-suite in the afternoon. Analyzing data, and then translating the results into plain language that’s digestible by executives and other teams, is ultimately critical.
2020-04-28 00:00:00 Read the full story…
Weighted Interest Score: 2.1758, Raw Interest Score: 1.1098,
Positive Sentiment: 0.1606, Negative Sentiment 0.4089
JULIA: Differentiable Programming Helps In Complex Computational Models- Viral Shah, Julia Computing
One of the key highlights at the MLDS summit 2020 was Viral B Shah, Co-creator of Julia Computing, who talked about Julia language and how it will become the language of the future. With more than 1000 delegates, MLDS second edition was India’s first applied AI and machine learning conference focused on developers, data scientists and enthusiasts. It emerged as the best forum to learn, network and discover the latest in applied AI and deep learning tools and frameworks.
In a well-attended keynote, presented by Viral B. Shah, Shah explained how Julia will become the language of the future and how differentiable programming helps in accomplishing complex computational programs.
Julia is a powerful high-level language with high-performance, where the syntax is similar to Python and Matlab. The language is 10 times faster compared to some of the popular languages like R, Python, Matlab, among others. At the present scenario, various popular organisations such as Intel, Amazon, Nasa, Microsoft, Google, among others, have been using this language in some way or the other.
2020-04-29 08:30:00+00:00 Read the full story…
Weighted Interest Score: 2.1729, Raw Interest Score: 1.5969,
Positive Sentiment: 0.2662, Negative Sentiment 0.0242
This news clip post is produced algorithmically based upon CloudQuant’s list of sites and focus items we find interesting. We used natural language processing (NLP) to determine an interest score, and to calculate the sentiment of the linked article using the Loughran and McDonald Sentiment Word Lists.
If you would like to add your blog or website to our search crawler, please email email@example.com. We welcome all contributors.
This news clip and any CloudQuant comment is for information and illustrative purposes only. It is not, and should not be regarded as investment advice or as a recommendation regarding a course of action. This information is provided with the understanding that CloudQuant is not acting in a fiduciary or advisory capacity under any contract with you, or any applicable law or regulation. You are responsible to make your own independent decision with respect to any course of action based on the content of this post.