Alternative Data News. 02, December 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.


Why did renewables become so cheap so fast? And what can we do to use this global opportunity for green growth?Price of electricity new renewables vs new fossil

For the world to transition to low-carbon electricity, energy from these sources needs to be cheaper than electricity from fossil fuels.

Fossil fuels dominate the global power supply because until very recently electricity from fossil fuels was far cheaper than electricity from renewables. This has dramatically changed within the last decade. In most places in the world power from new renewables is now cheaper than power from new fossil fuels.

The fundamental driver of this change is that renewable energy technologies follow learning curves, which means that with each doubling of the cumulative installed capacity their price declines by the same fraction. The price of electricity from fossil fuel sources however does not follow learning curves so that we should expect that the price difference between expensive fossil fuels and cheap renewables will become even larger in the future.

2020-12-01 Read the Full Story…

CloudQuant Thoughts : The future for Energy looks very rosy indeed!


S&P Global And IHS Markit To Merge

All-Stock Transaction Valuing IHS Markit at $44 Billion, Powering the Markets of the Future

Joins Two World-Class Organizations with Unique, Highly Complementary Assets to Enhance Customer Value Proposition

Combined Company to Benefit from Increased Scale and Mix Across Core Markets with Attractive Growth Adjacencies

Expected to be Accretive to Earnings by the End of the Second Full Year Post-Closing with ~$480 Million of Annual Run-Rate Cost …
2020-11-30 07:07:33+00:00 Read the full story…
Weighted Interest Score: 2.9668, Raw Interest Score: 1.6110,
Positive Sentiment: 0.4658, Negative Sentiment 0.1359

S&P Global Gobbles Up IHS Markit In $44 Bn Deal

Credit ratings giant S&P Global reached an all-stock deal to buy IHS Markit for $44 billion, the companies announced Monday.

The merger will create a $126 billion financial services behemoth that will be headquartered in New York.

The firms said joining forces will bolster offerings to investor clients and provide complementary information streams in growth areas, such as in the shifts towards renewable energy and environmental, social and governance (ESG) investing.

2020-12-01 12:11:27+11:00 Read the full story…
Weighted Interest Score: 2.5915, Raw Interest Score: 1.5245,
Positive Sentiment: 0.2595, Negative Sentiment 0.0649

S&P agrees to pay a staggering $44 billion for IHS Markit, but will it be allowed?

Although the deal is yet to be approved by regulators, and could be thwarted if deemed to create a data monopoly, IHS Markit’s sale represents a potentially massive transaction and shows that data is the absolute essence of the future of markets.

Data, and its vital importance in capital markets, is most certainly the order of the day.

The astonishing price that S&P has agreed to pay for IHS Markit, about which CEO Lance Uggla told employees in…
2020-11-30 16:24:19+02:00 Read the full story…
Weighted Interest Score: 2.5731, Raw Interest Score: 1.4295,
Positive Sentiment: 0.0953, Negative Sentiment 0.2224

CloudQuant Thoughts : This week’s big news in the Alternative Data Universe!


Pandas Sidetable: A Smarter Way of Using Pandas

A great merge of value counts and cross tab functions

Pandas is a very powerful and versatile Python data analysis library that expedites the preprocessing steps of data science projects. It provides numerous functions and methods that are quite useful in data analysis.

Although the built-in functions of Pandas are capable of performing efficient data analysis, custom made functions or libraries add value to Pandas. Sidetable is one of these add-ons which makes it easier to create summaries of dataframes. It can be considered as a combination of value counts and cross tab functions.
2020-12-02 13:11:07.448000+00:00 Read the full story…
Weighted Interest Score: 3.1081, Raw Interest Score: 1.2838,
Positive Sentiment: 0.4054, Negative Sentiment 0.0000

CloudQuant Thoughts : Sidetable looks like a very nice, useful library!

A.I. Specialist, Robotics Engineer Top Emerging Jobs List

Which technology jobs are poised to go from niche to mainstream over the next few years? That’s a vital question to answer, especially for those technologists who spend lots of time and resources acquiring highly specialized skills in arenas such as machine learning and artificial intelligence (A.I.).

For the third year in a row, LinkedIn has produced an Emerging Jobs Report (PDF) that tries to guess which jobs will experience “tremendous growth” over the next few years. As you might expect, most of these roles are technology-related; once businesses realize that embracing A.I. or data science can mean the difference between wild success and complete implosion, they rush to employ as many technologists as they can.

LinkedIn’s report concludes that it’s never a bad time to become an engineer or a data scientist: “engineering roles across the board are still seeing tremendous growth. More than 50% of this year’s list was made up of roles related to engineering or development, with the emerging field of robotics appearing for the first time.” Here’s the breakdown of the top positions, along with anticipated growth and the necessary skills for each:

2020-12-02 00:00:00 Read the full story…
Weighted Interest Score: 2.8398, Raw Interest Score: 1.8247,
Positive Sentiment: 0.1935, Negative Sentiment 0.1106

CloudQuant Thoughts : AI Specialist is streaking out in the lead!!

14 Data Science projects to improve your skills

There’s a lot of data out there and so many data science techniques to master or review. Check out these great project ideas from easy to advanced difficulty levels to develop new skills and strengthen your portfolio.

Take this time in isolation to learn new skills, read books, and improve yourself. For those interested in data, data analytics, or data science, I’m providing a list of fourteen data science projects that you can do during your spare time!

There are three types of projects:

  • Visualization projects
  • Exploratory data analysis (EDA) projects
  • Prediction modeling

2020-12-14 00:00:00 Read the full story…
Weighted Interest Score: 4.6355, Raw Interest Score: 1.4865,
Positive Sentiment: 0.2973, Negative Sentiment 0.2973

CloudQuant Thoughts : Lots of Easy level projects for people to try!


ESG Section

CloudQuant also provides Alternative Data Sets including an excellent ESG data set with proven Alpha. Head over to our data catalog for more information.

Diligend launches new module for ESG & Diversity data disclosures

Diligend, a financial data collection and analysis software provider, has laucnhed an ESG and Diversity disclosure module for Limited Partners (LPs), General Partners (GPs), consultants, fund of funds, fund managers and fund administrators.

The tailored and flexible set of new features allows the clients to request specific ESG & Diversity data quickly, then, swiftly rate, and assess considerations at the firm or fund level.

Diligend provides clients with readily available and automated ESG & Diversity questionnaires that they can instantly distribute to hundreds of fund managers or portfolio companies. Clients can also adjust questions and refine scoring metrics to fit their process.

2020-12-01 00:00:00 Read the full story…
Weighted Interest Score: 6.5068, Raw Interest Score: 3.0822,
Positive Sentiment: 0.0000, Negative Sentiment 0.0000

NASDAQ’s VC arm invests in Danish sustainable analytics firm as part of European Data business

Data continues to be the order of the day, as NASDAQ takes a shine to Matter, which provides retail and institutional investors with in-depth insight of the ESG impact of their portfolios.

Nasdaq Ventures, Nasdaq’s (Nasdaq: NDAQ) investment arm, announced today a strategic investment in Matter, the sustainability analysis and reporting provider, as it continues to innovate capabilities that help enlighten sustainable investing decisions. Nasdaq’s investment in Copenhagen-based Matter further extends and complements its existing partnership with Matter via Nasdaq’s European data business.

The Nasdaq ESG Footprint solution is powered by Matter’s analytics technology and provides retail and institutional investors with in-depth insight of the ESG impact of their portfolios.
2020-12-01 14:16:55+02:00 Read the full story…
Weighted Interest Score: 5.1819, Raw Interest Score: 2.4763,
Positive Sentiment: 0.4370, Negative Sentiment 0.1092

Nasdaq Ventures Invests In ESG Analytics Provider

“We are excited to welcome Nasdaq Ventures as an investor and look forward to strengthening our partnership with Nasdaq around sustainability,” said Niels Fibæk-Jensen, CEO of Matter. “The investment will enable us to continue the expansion of our sustainability analysis and reporting solutions for financial institutions. Together with Nasdaq, we can enable a better understanding of the impact of capital by delivering sustainability insights in a…
2020-12-01 06:10:02+00:00 Read the full story…
Weighted Interest Score: 4.3011, Raw Interest Score: 2.0417,
Positive Sentiment: 0.5326, Negative Sentiment 0.0888

ICE And CTBC Investments Collaborate On ESG

r of global exchanges and clearing houses and provider of mortgage technology, data and listings services, today announced that ICE Data Services and CTBC Investments Co., will collaborate to develop environmental, social and governance (ESG) indices and financial products for market participants.

ICE has launched two new ESG bond indices, the ICE 15+ Year Large Cap USD Emerging Markets External Sovereign Carbon Reduction Index and the ICE 15+ Year Ultra Large Cap Developed Markets US Corporate Best-in-Class ESG Index. The new ESG indices are administered and calculated by ICE Data Indices, LLC (“IDI”) and are broadly dissemina…
2020-12-01 05:59:03+00:00 Read the full story…
Weighted Interest Score: 3.4572, Raw Interest Score: 1.5578,
Positive Sentiment: 0.3462, Negative Sentiment 0.0000

ICE looks to clean up its act with the launch of new fixed income ESG indices

CTBC Investments will launch investable tracking products, such as ETFs to reflect the performance of the ESG indices.

ESG, a three letter acronym for Environmental Social and Governance, has been the buzzword-du-jour for financial markets throughout 2020 and seem likely to remain so into 2021 and beyond.

Asset managers have been busy launching new funds and repurposing old vehicles to meet the demand from investors for more ethically surefooted products, whilst rating agencies are actively promoting their own scoring and ranking systems for ESG and sustainability criteria.

The…
2020-12-01 14:49:42+02:00 Read the full story…
Weighted Interest Score: 3.2168, Raw Interest Score: 1.4040,
Positive Sentiment: 0.1053, Negative Sentiment 0.0351

The problem with data on investing in ESG stocks

Investing in ESG stocks has been heating up in recent years, but the firms that provide the data may be the only ones that are winning in the ESG revolution. In a recent report, Factor Research examined the ESG data from one provider and analyzed stock performance.

Author Nicolas Rabener found that the stocks with the worst ESG rating in the data set he looked at outperformed over the last 12 months. This suggests that proponents who claim ESG boosts stock prices may not be seeing the whole story when it comes to the data.

Rabener explained that the “ESG ecosystem” has three categories of players. They are the data providers, data consumers like asset managers and index providers, and asset allocators. However, he argues that there’s only one winner in ESG investing, and that’s the data providers that sell ESG ratings.

2020-12-01 18:59:09+00:00 Read the full story…
Weighted Interest Score: 3.1592, Raw Interest Score: 1.8075,
Positive Sentiment: 0.2312, Negative Sentiment 0.1681


NVIDIA Launches MONAI Framework To Accelerate AI In Healthcare

In an attempt to accelerate artificial intelligence in the healthcare industry, NVIDIA has launched MONAI — a Medical Open Network for AI, a domain-optimised, open-source framework for healthcare. According to the official release by NVIDIA, MONAI is now ready for production with the upcoming release of the company’s Clara application framework for AI-powered healthcare and life sciences.

The framework, MONAI, is a PyTorch-based framework which was introduced in April 2020 and has already been adopted by some of the leading healthcare research institutions. This framework advances the usage of artificial intelligence for medical imaging. This is done with industry-specific data handling, reproducible reference implementations of state-of-the-art approaches, and high-performance training workflows.

2020-12-01 07:45:10+00:00 Read the full story…
Weighted Interest Score: 2.9425, Raw Interest Score: 1.4828,
Positive Sentiment: 0.2399, Negative Sentiment 0.0436

Next gen of alt data

While the relationship between systematic hedge funds and alternative data sources is not new, quants have recently raised concerns that alt data is not giving the same alpha as it used to. This is because people are increasingly accessing the same data sets (web scraping, search analytics, satellite feeds etc.), making it difficult to find investing signals and high-frequency insight amongst the noise.

New data sets are needed to satisfy the demand for data-driven insights to spot long-term trends, improve trading decisions and ultimately drive performance. And while the industry understands the benefits of real-time (or near real-time) data, market participants are waking up to the predictive power of pricing data that comes from having access to vast amounts of historic data. Having a minimum of 5 years’ worth of historic Level 3 order book data is what is needed to have a meaningfully predictive data set. Or in other words…the next generation of alternative data.

2020-12-01 00:00:00 Read the full story…
Weighted Interest Score: 6.2447, Raw Interest Score: 2.7538,
Positive Sentiment: 0.1689, Negative Sentiment 0.1352

Is synthetic data the key to the next data boom in financial services?

Across industries, data is recognised as an organisation’s most valuable asset. From data comes knowledge and new insights that can be used to improve every function of a business, from new and better products and services for customers, to operational efficiencies. As data strategies mature, firms are turning an increasingly expectant eye toward the possibilities enabled by advanced technologies such as AI, machine learning and data science.

AI and ML models have delivered unprecedented value in many industries. In financial services, they have unlocked incredible efficiencies by automating decision-making processes, risk calculation and enabled the creation of ever more intelligent solutions. In each case, the quality of the models is determined by two major factors: quantity and quality.
2020-11-27 Read the Full Story…

TORA’s OEMS Integrates with Liquidnet’s IA Trader to offer real time actionable decision making tools

has integrated its order & execution management system (OEMS) with global institutional investment network, Liquidnet’s IA Trader.

The integration offers access to advanced artificial intelligence, data analytics tools and a broad range of Liquidnet trading algorithms.

Integrating IA Trader directly in the TORA OEMS helps equity traders enhance their decision making process at the point of trade. The system delivers actionable signals, alerts, compact stamp summaries and data visualisation capabilities that are designed to provide clients greater day-to-day efficiency and enhanced operational workflow …
2020-12-01 00:00:00 Read the full story…
Weighted Interest Score: 4.9705, Raw Interest Score: 2.5304,
Positive Sentiment: 0.6326, Negative Sentiment 0.0973

TORA’s OEMS integrates with Liquidnet’s IA Trader to offer real time actionable decision making tools

t has integrated its order & execution management system (OEMS) with global institutional investment network, Liquidnet’s IA Trader. The integration offers access to advanced artificial intelligence, data analytics tools and a broad range of Liquidnet trading algorithms.

Integrating IA Trader directly in the TORA OEMS helps equity traders enhance their decision making process at the point of trade. The system delivers actionable signals, alerts, compact stamp summaries and data visualisation capabilities that are designed to provide clients greater day-to-day efficiency and enhanced operational workflow in…
2020-12-01 14:12:04+02:00 Read the full story…
Weighted Interest Score: 4.8099, Raw Interest Score: 2.4479,
Positive Sentiment: 0.6346, Negative Sentiment 0.0907

How software engineers and data scientists can collaborate together

Data scientists are great mathematicians with a lot of cross-disciplinary knowledge and a super ability for analysis. The task of this specialist is to find the ideal formula for training artificial intelligence. Among all the existing algorithms, they should look for the one that is better suited to solving the project’s problems and understand what exactly is going wrong. However, in order to increase the competitive advantage of the company, data scientists need to cooperate with software engineers, like dedicated Laravel engineer

2020-11-24 12:36:23+00:00 Read the full story…
Weighted Interest Score: 4.2899, Raw Interest Score: 2.3059,
Positive Sentiment: 0.3334, Negative Sentiment 0.3751

Consolidated Tape: A Vaccine for Fragmentation?

Since MiFID introduced competition to our equity markets in 2007, the resulting fragmentation of liquidity had a significant impact on the efficiency of sourcing liquidity. Whilst competition resulted in lower explicit costs (spreads), the implicit costs of accessing liquidity and data from a broad spectrum of competing markets have offset the gains. Costs aside, the visibility of liquidity in the market has been impaired to the point that investors are flying blind – ask 5 different people how much turnover traded in Air France KLM today and you will get 5 different answers.

Soon after MiFID was implemented, when these issues were first observed in equity markets, the immediate conclusion was the need for a consolidated tape which would logically provide a single source of information about market liquidity. A closer look, however, reveals a more complex challenge resulting from the quality of this information. Aside from aggregating the fragmented sources of trading venue data, the data provided by APAs for OTC trading has proven to be wildly inaccurate thereby undermining any attempts to assemble a clear picture of market liquidity. Unfortunately, these problems have little to do with how data is consolidated and reveal the actual challenge of how data is collected by APAs who are not empowered nor motivated to address these issues.
2020-11-25 10:30:08-05:00 Read the full story…
Weighted Interest Score: 2.6992, Raw Interest Score: 1.0497,
Positive Sentiment: 0.3187, Negative Sentiment 0.6560

How This Startup Is Using Computer Vision To Provide Video KYC

The potential of IoT and AI can be said as limitless. The key to finding the potential is basically to find practical use-cases where businesses can rapidly realise the value of these AI and IOT heavy investments.

At the present scenario, the whole world is moving towards a digitally connected and automated world revolving around smart gadgets, homes and cars to animated customer engagement outposts, chatbots, and personalisation of products and services.

Regarding the practical use-case of AI and IoT, one such use-case is known as Video KYC. Video KYC with its embedded capabilities can offer many enhancements, such as geo-tagging, liveness detection, image recognition, fuzzy matching, computer vision and optical character recognition, neural networks, and scalable infrastructure- to deliver better accuracy at a fraction of the cost.

2020-11-27 12:30:16+00:00 Read the full story…
Weighted Interest Score: 2.6842, Raw Interest Score: 1.5558,
Positive Sentiment: 0.0980, Negative Sentiment 0.0613


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