Alternative Data News. 11, November 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.
3D Map of COVID Cases by Population, March through Today
This vizualization uses county-level COVID-19 case data obtained from the US Covid Atlas from UChicago’s Center for Spatial Data Science, where I’m a software engineer. The data comes originally from 1Point3Acres, packaged as a Geojson (a few Python and R daily scripts) and displayed on the front end using Deck.gl. Original color scheme is based off of d3’s Yellow-Orange-Red color interpolation.
Here’s a non population-normalized version for reference — raw COVID-19 count numbers.
2020-11-10 Read The Full Story…
CloudQuant Thoughts : Another Fabulous Reddit DataIsBeautiful post by especiallySpatial. Momentary spikes are apparently down to backlogs in the data. This animation is of reported cases, the reported deaths normally trail the cases by a month or so, also our doctors and nurses have been getting better at treating this disease and so the outcomes are not AS BAD as at the outset, however Americans are still dying in the thousands. Here is especiallySpatial‘s same animation for deaths. This pandemic must not be allowed to spiral out of control just because we are in a political limbo.
CloudQuant CEO to speak on Panel at CRUX 3 day Virtual Summit – November 18th 2020
CloudQuant CEO Morgan Slade will be taking part in a Panel Discussion at the CRUX Summit 9:00am – 9:45am Eastern on November 18th 2020.
The Panel Discussion is title “What’s Missing in Data Preparation & Distribution”.
Why Should Biden Focus On Getting A National Chief Data Scientist
Data science for Joe Biden, the newly elected President of the US, is not a new field. To boost his presidential campaign and to broaden the appeal with younger voters and small donors, he had relied on a data analytics startup — Civis Analytics, which is backed by former Google chairman Eric Schmidt. In his campaigns, he has also been a strong advocate of making investments in technology.
With a strong dependency on data science for his election campaigns, it would not be unlikely for him to rely on the technology to drive his memos and future missions. The question now is, like his contemporary, Barack Obama who had for the first time appointed a Chief Data Scientist to bring about data-driven tasks, will Biden focus on getting a National Chief Data Scientist? Most popular views and experts believe that, in fact, he should get one — and here’s why.
2020-11-11 04:30:32+00:00 Read the full story…
Weighted Interest Score: 2.3947, Raw Interest Score: 1.3519,
Positive Sentiment: 0.4056, Negative Sentiment 0.2704
CloudQuant Thoughts : The last presidency ramped up AI, now Data Science and belief in a Scientific approach to data is the healthiest thing we can do for the American people. When discussing national talking points with my daughter, I spend the majority of my time referring to data as such I hope we can move to a more provable facts driven society.
How consumer data provider Yodlee can help bolster the buy-side portfolio-building process
Envestnet | Yodlee, a data aggregation and analytics platform specialising in consumer spending data analytics, says asset managers are increasingly seeking out such alternative data insights in their hunt for alpha. Nikhil Nadkarni, Vice President, Data Products, explains how the consumer spending data analytics can help provide asset managers a view into consumer interactions with brands and incorporating insights into the investment research processes.
“Equity Researchers and Investment Managers can use consumer spending data analytics in their fundamental research to understand and forecast revenues, customer retention, customers’ lifetime values, customer churn and competitive analysis. Learning consumer spending patterns around online versus offline provides visibility into how consumer discretionary spending is shaping consumer behaviour especially during Covid-19.”
Usage of alternate data, like consumer spending data analytics, is getting a lot of attention from institutional money managers as it delivers additional alpha in investment research. Such data analytics provide a lens for researchers and portfolio managers to validate an investment thesis and generate differentiated insights outside of just forecasting revenue.
2020-11-03 Read the Full Story…
CloudQuant Thoughts : Evestnet | Yodlee were the main sponsors of the excellent Benzinga Fintech Awards which took place yesterday. We were nominated for Best Data Analysis Tool (Unfortunately we didn’t win!). I believe you can still watch the recordings of the two live-streams. I would personally recommend the Boot Camp Track for variety!
CloudQuant is a major provider of Alternative Data Sets, including a quite excellent ESG data set. For many of the datasets we provide we have taken the claims of the vendors and tested them on our publicly available Mariner Backtesting system, we produce White Papers detailing our results and even make the Python code we used in the analysis so you can re-run it yourself on Mariner.
Moody’s Acquires Stake In Alternative Data Provider
Moody’s Corporation announced that it has acquired a minority stake in MioTech, a leading provider of alternative data and insights serving the environmental, social, and governance (ESG) and know your customer (KYC) markets in Greater China. The investment reflects Moody’s commitment to providing China’s evolving financial markets with innovative ESG and KYC solutions.
MioTech uses artificial intelligence (AI) to track and scan alternative data sources related to ESG and KYC factors, supply chains, and financial information for over 800,000 public and private companies in China. Its analytical tools are designed to turn unstructured datasets into insights for portfolio managers, research analysts, and risk managers, and its AI algorithms detect entities’ vulnerabilities by monitoring news, social media, disclosure, and other forms of alternative data in real-time.
2020-11-06 Read the Full Story…
Alternative fund managers demonstrated resilience in adapting to the new Covid-19 reality
Despite extreme levels of market volatility, increased trading volumes and disruptions to society due to Covid-19, alternative fund managers have persevered, and even exceeded, performance expectations from investors. Nonetheless, managers continue to face challenges in addressing important areas of focus, including environmental, social and governance (ESG) products, and diversity and inclusion (D&I), according to the 2020 EY Global Alternative Fund Survey.
In times of change, does accelerated adaptation present obstacles or opportunities? – the 14th annual survey (formerly the EY Global Hedge Fund Survey) – reveals that total allocations to alternative investments remain relatively unchanged; however, the competition between asset classes continues to intensify. Following a multiyear trend, allocations to hedge funds shrunk again to just 23 per cent in 2020, compared to 33 per cent in 2019 and 40 per cent in 2018. Investments in private equity and venture capital remained stable at 26 per cent, while investments in private credit increased from 5 per cent to 11 per cent as many market participants anticipate Covid-19 initiating a credit cycle that will create opportunities for these managers.
2020-11-11 00:00:00 Read the full story…
Weighted Interest Score: 3.1797, Raw Interest Score: 1.5793,
Positive Sentiment: 0.2154, Negative Sentiment 0.1292
Must-Have Elements of a Modern Data Approach
The current global situation has highlighted the importance of digitalization for organizations of every kind—from businesses to hospitals and schools. But data-driven organizations must be able to access all the relevant data, store it cost efficiently, ensure it is of the highest quality, and make its insights available in real time to all users. Now more than ever, a strong data strategy is essential to every enterprise’s success.
According to the “2017 Gartner Chief Data Officer” survey, 86% of data and analytics leaders said defining such a strategy was a top responsibility, up 64% from 2016. As many leaders have realized, a large part of this responsibility requires them to implement new strategies that empower citizen and specialist users with self-service capabilities. To make this possible and accelerate digital transformation, enterprises need to adopt a modern data platform and approach.
2020-11-04 Read the Full Story…
How alternative data is a research necessity in today’s dynamic market – PODCAST
Economist John Kenneth Galbraith once remarked: “One of the greatest pieces of economic wisdom is to know what you do not know.”
As global markets experience greater volatility in 2020, the opportunities for active fund managers to seek out alpha-generating positions have improved. However, with heightened volatility comes heightened risk. This webinar looks at how Covid-19 has accelerated the use of alternative data to aid global equities portfolio managers respond to dynamic markets. And whether accessing alternative data sets has helped them in this endeavour; both with respect to idea generation, and risk management.
In this webinar, the panelists discussed:
- How equity l/s managers are evolving their investment process using non-traditional data sets.
- How is data management improving/solidifying their approach to risk management?
- Why not all alternative data sets are created equal (GPS data on shopping density in supermarkets doesn’t necessarily mean people are spending money)
- Why accessing anonymous credit card data sets, as one example, can provide deeper insights into consumer retail activity (i.e. more tactical long/short positions for those trading consumer stocks)
- How should analysts/PMs best approach incorporating alternative data sets into their existing infrastructure?
- What are the risks and opportunities, in today’s market environment?
2020-11-06 00:00:00 Read the full story…
Weighted Interest Score: 6.9069, Raw Interest Score: 2.3725,
Positive Sentiment: 0.4152, Negative Sentiment 0.0000
Nasdaq Leads Europe for SME Listings
Bjørn Sibbern, president of European markets at Nasdaq, said the exchange has listed more than 50 small and medium-size enterprises in Europe this year despite the Covid-19 pandemic. Sibbern told Markets Media: “It was important to keep markets open and functionality normally during the volatility caused by Covid-19. We did not feel there was a need to shorten hours or ban short selling.”
He took on his European role in June last year after moving from New York where he had been Nasdaq’s head of the global information services business. Last year he said he wanted Nasdaq to become more visible in Europe outside the Nordics. “We are the leading European venue for SME listings with more than 50 so far this year despite Covid-19,” he added. “The success is due to a cluster of institutional and sophisticated retail investors in the Nordics and advisers who support these initial public offerings.”
2020-11-10 04:37:24+00:00 Read the full story (TradersMagazine)…
2020-11-06 13:07:02+00:00 Read the full story (MarketsMedia)…
Weighted Interest Score: 5.2300, Raw Interest Score: 2.0762,
Positive Sentiment: 0.2212, Negative Sentiment 0.0340
How Digital is Your Bond Desk?
Digital transformation is at the top of every bank’s strategic agenda as possibly the most important initiative necessary to remain competitive and drive future value. According to an Accenture Survey (1) of investment banks, 60% believe that in three years technology will have a significant impact on trading and that data analytics is the technology that will have the greatest impact. The opportunity is reflected in the continued growth in IT spending on new technologies and the talent required to develop it. Boston-based research and advisory company Celent, projects global bank IT spending to reach $309b in 2022 (2), and much of that spending is going to new and disruptive technologies. But there are many questions that management must address about what a digital transformation strategy means and how to ensure the results generate real value.
2020-11-11 08:10:34+00:00 Read the full story…
Weighted Interest Score: 3.5156, Raw Interest Score: 1.7196,
Positive Sentiment: 0.2707, Negative Sentiment 0.1194
How to create stunning visualizations using python from scratch
A step-by-step guide using Matplotlib and Seaborn libraries
Visualization is an important skill set for a data scientist. A good visualization can help in clearly communicating insights identified in the analysis also it is a good technique to better understand the dataset. Our brain is wired in a way that makes it easy for us to extract patterns or trends from visual data as compared to extracting details based on reading or other means.
In this article, I will be covering the visualization concept from the basics using python. Below are the steps to learn visualization from basic,
- Importing data
- Basic visualization using Matplotlib
- More advanced visualizations, still using Matplotlib
- Building quick visualizations for data analysis using Seaborn
- Building interactive charts
2020-11-09 16:37:44.772000+00:00 Read the full story…
Weighted Interest Score: 3.4597, Raw Interest Score: 1.3460,
Positive Sentiment: 0.1706, Negative Sentiment 0.0379
Data science at scale with PySpark on Amazon EMR cluster
Have you ever run into a situation where your computer simply fails to process the kind of data you trying to work with? Hmmm, so you are probably dealing with a big data that is most likely too large and complex to be processed by a single machine on CPU. Well, what do we mean by big data? How much data is considered as big data? Well, we can argue endlessly about that — so let’s not do that here. Instead, let’s just say that you have a large enough data and your computer is struggling to process it. Hopefully, there is no any flames or smoke coming out of your machine. Joke aside, this is a very common problem and the most common approach to solve it is to process such large datasets on a distributed computing platform. Apache Spark is an open-source parallel computing framework and is designed to enable the processing of such large datasets on a cluster of computers.
There are a few different providers for distributed computing platform you can choose from and some popular choices include Cloudera, Hortonworks, Databricks, Amazon AWS and Microsoft Azure. In this article, I will show you how to set up a distributed computing platform for your needs on AWS cloud, in particular Amazon EMR. We will be using PySpark which is the Python API to Apache Spark.
2020-11-11 13:21:28.119000+00:00 Read the full story…
Weighted Interest Score: 3.3743, Raw Interest Score: 1.2304,
Positive Sentiment: 0.0932, Negative Sentiment 0.1491
US Treasury Could Issue Inaugural Green Bond Under Biden
The US could issue its first sovereign green bond market under the Biden administration which could spark significant growth in the market.
Bram Bos, lead porfolio manager green bond at NN Investment Partners, the Dutch fund manager, said in an email that President-elect Joe Biden’s commitment to rejoining the Paris agreement when he is inaugurated symbolises a broader transformative shift in climate policy. “The Biden administration will invest heavily in sustainable infrastructure and clean energy, which could lead to an inaugural green US Treasury issue and further boost the global green bond market,” he added.
2020-11-10 06:09:49+00:00 Read the full story…
Weighted Interest Score: 3.1717, Raw Interest Score: 1.6781,
Positive Sentiment: 0.1831, Negative Sentiment 0.1831
What Is The Hiring Process For Data Scientists At ZS
With a focus on building scalable capabilities for generating, operationalising, and measuring data-driven insights for their clients, ZS has a strong advanced data science group within their Business Consulting function. The team focuses on integrating transformative AI-enabled solutions and data products across multiple industries such as healthcare, life sciences, telecommunication, high tech, and retail. As the company leverages deep industry expertise and leading-edge analytics to create solutions that work in real life, the data science team plays a vital role in driving these functions.
What Do ZS Look For In A For Data Scientist? From foundational research in deep learning, natural language processing (NLP), optimisation, and operational research — the advanced data science team at ZS works across various solutions. They are involved in developing solutions to full-scale productisation. In other words, the team works on completing the entire life cycle from innovation to industrialisation. To fit into these roles, ZS look for AI technocrats who can effectively lead a hybrid team of scientists and engineers. This requires mastery in either advanced data science or engineering and working proficiency.
2020-11-11 07:30:23+00:00 Read the full story…
Weighted Interest Score: 3.1582, Raw Interest Score: 1.6029,
Positive Sentiment: 0.4654, Negative Sentiment 0.0259
3 Types of Data Science Engineer Interview Questions
Nail the data science engineer interview with confidence
My background is primarily in software engineering and data science. As I began looking for a job in data science, interviewers noticed my experience in software. Many interviewing individuals did not have software backgrounds but were from mathematics, physics, or signal processing. During my interviews, I commonly saw questions in three main areas: data ingestion and cleaning, scalability, and research and development.
- Data Ingestion and Cleaning
- Research and Development
2020-11-11 04:08:54.068000+00:00 Read the full story…
Weighted Interest Score: 3.0885, Raw Interest Score: 1.0225,
Positive Sentiment: 0.0417, Negative Sentiment 0.2504
How one bank’s tech team is teaching ‘on-the-fly’ data
Following her virtual session, ‘Democratising data-driven decisions with self-service tools’ at the Apidays conference, Yojas Samarth, senior data engineer, tech speaker and tech trainer at DBS Bank, speaks to Finextra Research regarding the nuance of training teams to effectively utilise data platforms.
Scenario based workshops and animated tools are some of the favoured methods Samarth employs in her efforts to teach the DBS workforce how to make use of the data assets at their fingertips – a resource that is quickly becoming a necessary competitive differentiator rather than a luxury.
Data democratisation is a force for good in financial services, however training is needed not only to interact with data legally and securely, but in order to distil relevant and valuable insights in a manner that works to promote the business goal.
2020-11-10 15:15:00 Read the full story…
Weighted Interest Score: 2.7633, Raw Interest Score: 1.5595,
Positive Sentiment: 0.1915, Negative Sentiment 0.1915
A Development Environment for Data with CI/CD
Data engineering is the science and art of producing good and timely data. Its goal is to deliver data to users even more than to deliver applications. There are great methods and tools that help deliver applications with consistently high quality. What are the methods and tools that help us deliver high-quality data? In this article, I will take the three following concepts: development environments, continuous integration, and continuous deployment, and demonstrate what they should look like in the world of data delivery. I will also provide examples of tools that can help you build this foundation for your data application.
What Is a Development Environment for Data? When developing data-intensive applications, we need to experiment with new code, new data sets, changes to the code, or data changes to data analysis tools — for example, new ETL, format or schema changes, a new compression algorithm, accuracy, a Spark/Presto version upgrade, and so on. While the type of experiment varies, the need remains the same: We should be able to run isolated experiments of data pipelines in an environment that is similar to our production environments without the fear of compromising it.
2020-11-11 08:35:03+00:00 Read the full story…
Weighted Interest Score: 2.5238, Raw Interest Score: 1.3874,
Positive Sentiment: 0.2643, Negative Sentiment 0.1321
India’s New AWS Data Center, Intel’s AI Acquisitions & More: Top News
As the world watched American election drama unfold, the stock market was rallying in favor of big tech. The internet companies which were under fire from both sides will benefit from a divided Congress as it makes it harder to pass legislation against tech giants. However, Twitter and Facebook continue to stumbled into more goof ups. Twitter even blocked President Trump’s tweets on election night. Looks like the gatekeepers of the internet and their semi-algorithmic content moderation will be looked at more closely in the coming months given the recent events. As we write this article, the results are still not yet declared and the big tech continues to influence one of the biggest events. But, it looks like Californians are not at all happy with so much of big tech and they voted in favor of a privacy law that can give one full control of their own data. Read more about this new law in this week’s top news brought to you by Analytics India Magazine.
2020-11-07 12:30:54+00:00 Read the full story…
Weighted Interest Score: 2.5181, Raw Interest Score: 1.3183,
Positive Sentiment: 0.1809, Negative Sentiment 0.1422
Top Tips and Tools for a Data Science Career in Finance
We caught up with Graham Giller, the former head of data science research at JPMorgan and ex-head of primary research at Deutsche. These days, Giller is CEO of his own firm, Giller Investments, and has written a book, Adventures in Financial Data Science, out later this month.
If you’re looking for develop a career in financial data, these are Giller’s tips.
2020-11-10 00:00:00 Read the full story…
Weighted Interest Score: 2.4685, Raw Interest Score: 1.3773,
Positive Sentiment: 0.2850, Negative Sentiment 0.1662
What Does a Data Engineer’s Career Path Look Like?
Big data is changing the future of almost every industry. The market for big data is expected to reach $23.5 billion by 2025.
Data science is an increasingly attractive career path for many people. However, the outlook is hazy for people that are not as familiar with the career path.
If you want to become a data scientist, then you should start by looking at the career options available. Northwestern University has a great list of ways that people can pursue a career in data science. You should also learn the career path that you need to follow to get started, which includes learning the right programming languages.
2020-11-08 19:38:27+00:00 Read the full story…
Weighted Interest Score: 3.3677, Raw Interest Score: 2.0106,
Positive Sentiment: 0.2011, Negative Sentiment 0.1005
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