- HTTP & SOCKS
- unlimited bandwidth
- Price starting from $0.08/IP
- Locations: EU, America, Asia
Alternative data (finance) – Wikipedia
Alternative data (in finance) refers to data used to obtain insight into the investment process.  These data sets are often used by hedge fund managers and other institutional investment professionals within an investment company.  Alternative data sets are information about a particular company that is published by sources outside of the company, which can provide unique and timely insights into investment opportunities. 
Alternative data sets are often categorized as big data,  which means that they may be very large and complex and often cannot be handled by software traditionally used for storing or handling data, such as Microsoft Excel. An alternative data set can be compiled from various sources such as financial transactions, sensors, mobile devices, satellites, public records, and the internet.  Alternative data can be compared with data that is traditionally used by investment companies such as investor presentations, SEC filings, and press releases.  These examples of “traditional data” are produced directly by the company itself.
Since alternative data sets originate as a product of a company’s operations, these data sets are often less readily accessible and less structured than traditional sources of data.  Alternative data is also known as “exhaust data. ” The company that produces alternative data generally overlooks the value of the data to institutional investors. During the last decade, many data brokers, aggregators, and other intermediaries began specializing in providing alternative data to investors and analysts. 
Examples of alternative data include:
Geolocation (foot traffic)
Credit card transactions
Web site usage
Mobile App or App Store analytics
Obscure city hall records
Social media posts
Online browsing activity
Shipping container receipts
Internet activity and quality data
Example of sentiment analysis against stock price (S&P 500)
Alternative data is being used by fundamental and quantitative institutional investors to create innovative sources of alpha. The field is still in the early phases of development, yet depending on the resources and risk tolerance of a fund, multiple approaches abound to participate in this new paradigm. 
The process to extract benefits from alternative data can be extremely challenging. The analytics, systems, and technologies for processing such data are relatively new and most institutional investors do not have capabilities to integrate alternative data into their investment decision process.  However, with the right tools and strategy, a fund can mitigate costs while creating an enduring competitive advantage. 
Most alternative data research projects are lengthy and resource intensive; therefore, due-diligence is required before working with a data set. The due-diligence should include an approval from the compliance team, validation of processes that create and deliver this data set, and identification of investment insights that can be additive to the investment process. 
However, the usage of the alternative data is not restricted by investment sphere, it’s successfully used in economics and politics as well as retail and e-commerce spheres. It’s possible to predict geopolitical risk through a profound alternative data analysis, while social media sites reveal a host of data for consumer sentiment analysis.
Alternative data can be accessed via:
Web scraping (or web Harvesting, performed by computer programmers that design an algorithm that searches websites for specific data on a desired topic)
Acquisition of Raw data
In finance, Alternative data is often analysed in the following ways:
Scarcity: the data Information overload within financial markets
Granularity: the level of detail and aggregation of data (including time)
History: the trajectory of data
Structure: the form of the data (csv, json etc. )
Coverage: the stocks or geographical locations that data can be linked with
While compliance and internal regulation are widely practiced in the alternative data field, there exists a need for an industry-wide best practices standard. Such a standard should address personally identifiable information (PII) obfuscation and access scheme requirements among other issues. Compliance professionals and decision makers can benefit from proactively creating internal guidelines for data operations. Publications such as NIST 800-122 provide guidelines for protecting PII and are useful when developing internal best practices. Investment Data Standards Organization (IDSO) was established to develop, maintain, and promote industry-wide standards and best practices for the Alternative Data industry.
Legal aspects surrounding web scraping of alternative data have yet to be defined. Current best practices address the following issues when determining legal compliance of web crawling operations:
Review of the terms and conditions associated with the websites crawled
Control over the potential interference with crawled websites
Web scraped data refers to data harvested from public websites. With 4 billion webpages and 1. 2 million terabytes of data on the internet, there is a mountain of information that can be valuable to investors when analyzing a corporate performance.
The companies that specialize in this type of data collection, like Thinknum Alternative Data,  write programs that access targeted websites and collect and store the scraped information on a periodic basis. In some cases web scraping requires use of public APIs as a way to access the data within those pages directly without visiting the actual website.
Types of web scraped data include:
Job listings: A company that is increasing hiring and headcount is likely experiencing growth.
Company ratings: Sites like Glassdoor allows employees to rate their company; increasing ratings, especially (in conjunction with increasing job listings) can be another growth indicator.
Online retail data: High product rankings on online retailers suggest strong sales for those product manufacturers. On the flip side, heavy discounting of products suggest weak sales. 
Standards Board for Alternative Investment (SBAI) is the global standard-setting agency for the alternative investment industry and guardian of the Alternative Investment Standards. The agency supported by approximately 200 alternative investment managers and institutional investors and collectively manage $3. 5 trillion. The SBAI has published the Standardised Trial Data License Agreement which addresses investment managers’ issues when comes to new data trailing process, like alternative data and big data.  Thomas Deinet, Executive Director of the SBAI said: “This Trial Data Licence Agreement template highlights a number of very important issues, including personal data protection, which has become a hot topic in light of the overhaul of data protection regulation in many jurisdictions. It also includes key protections for managers in areas such as prevention of insider trading and ‘right to use data’. It is crucial that managers and data vendors fully understand all risks when selling and using new data. “
^ Z., W. (2016-08-22). “Why investors want alternative data”. The Economist. Retrieved 21 August 2017.
^ Flanagan, Terry (2016-12-07). “‘Early Days’ For Alternative Data”. Markets Media. Retrieved 21 August 2017.
^ a b c d Kolanovic, Marko; Krishnamachari, Rajesh. “Big Data and AI Strategies – Machine Learning and Alternative Data Approach to Investing”. RavenPack. J. P. Morgan, Global Quantitative & Derivatives Strategy. Archived from the original on July 22, 2018. Retrieved June 29, 2017.
^ Nathan, Krishna (2017-01-03). “What is ‘alternative data’ and how can you use it? “. CIO. Retrieved 20 August 2017.
^ Belissent, Jennifer (2017-06-23). “The Age of Alt: Data Commercialization Brings Alternative Data To Market”. Forrester Research. Forrester Research, Inc. Retrieved 20 August 2017.
^ a b c “Searching for Alpha: Big Data. Navigating New Alternative Datasets”. Eagle Alpha. Citi Research. Retrieved July 3, 2017.
^ Hafez, Peter. “Data Hoarding and Alternative Data In Finance – How to Overcome the Challenges”. RavenPack.
^ Savi, Raffaele; Shen, Jeff; Betts, Brad; MacCartney, Bill. “The Evolution of Active Investing Finding Big Alpha in Big Data” (PDF). BlackRock. Retrieved August 9, 2017.
^ Kilburn, Faye (2017-07-19). “Quants look to image recognition to process alternative data”. Retrieved 21 August 2017.
^ Sapnu, Raquel. “Why Alternative Data is the New Financial Data for Industry Investors”. Datafloq. Retrieved 21 August 2017.
^ Barnes, Dan (2017-07-02). “The role of data in gaining valuable financial insights”. Raconteur. Raconteur Media Ltd. Retrieved 21 August 2017.
^ Turner, Matt. “This is the future of investing, and you probably can’t afford it”. Business Insider. Retrieved 11 August 2017.
^ Iati, Robert. “Alternative Data: The Hidden Source of Alpha” (PDF). Dun & Bradstreet. Retrieved August 9, 2017.
^ Noyes, Katherine (2016-05-13). “5 things you need to know about data exhaust”. Computer World. IDG News. Retrieved 11 August 2017.
^ Levy, Rachael. “Hedge funds are tracking your every move, and ‘it’s the future of investing”. Retrieved 21 August 2017.
^ Wigglesworth, Robin (30 March 2016). “Investors mine Big Data for cutting-edge strategies”. Financial Times. Retrieved 21 August 2017.
^ Borzykowski, Bryan (2016-06-09). “How investors are using social media to make money”. Retrieved August 3, 2017.
^ Wieczner, Jen. “How Social Media Is Helping Investors Make Money”. Fortune. Retrieved August 4, 2017.
^ a b c Ekster, Gene. “Driving Investment Performance with Alternative Data”. Integrity Research. Retrieved August 2, 2017.
^ McPartland, Kevin. “Alternative Data for Alpha” (PDF). GREENWICH ASSOCIATES. Retrieved 11 August 2017.
^ Najork, Marc; Heydon, Allan (2002). Handbook of Massive Data Sets. Springer US. pp. 25–45. doi:10. 1007/978-1-4615-0005-6. ISBN 9781461348825. S2CID 46033589.
^ Ekster, Gene (2015-08-19). “Alternative Data Cross-functional Teams and Workflow”. Retrieved August 7, 2017.
^ Ekster, Gene (2016-05-02). “Mitigating Alternative Data Compliance Risks Associated with Web Crawling”. Retrieved June 20, 2017.
^ McCallister, Erika; Grance, Tim; Scarfone, Karen. “National Institute of Standards and Technology Special Publication 800-122: Guide to Protecting the Confidentiality of Personally Identifiable Information (PII)” (PDF). National Institute of Standards and Technology. Retrieved June 25, 2017.
^ “Data firm that monitors Reddit says it saw GameStop mentions spiking days ago”. 25 February 2021.
^ Demos, Telis (February 2021). “GameStop Stock Frenzy May Not be So Bad for Wall Street”. Wall Street Journal.
^ Johnson, Richard. “Alternative Data in Action: Web-Scraping. ” 14 January 2019
^ “SBAI Publishes Standardised Trial Data License Agreement” 6 February 2019. Retrieved 15 May 2019. [permanent dead link]
^ “SBAI publishes Standardised Trial Data License Agreement. “6 February 2019. Retrieved 15 May 2019.
Alexander Denev and Saeed Amen, The Book of Alternative Data: A Guide for Investors, Traders and Risk Managers (Wiley 2020)
Marko Kolanovic and Rajesh T. Krishnamachari, Big Data & AI Strategies: Machine Learning and Alternative Data Approach to Investing (JP Morgan 2018)
HTTP Rotating & Static
- 40 million IPs for all purposes
- 195+ locations
- 3 day moneyback guarantee
How Much Are Managers Paying for Data? | Institutional Investor
Asset managers are increasingly using nontraditional data to make investment decisions — but it doesn’t always come cording to consulting firm Neudata, which helps investors evaluate data providers, yearly subscriptions for alternative data sets can range from less than $25, 000 to $500, 000 or more. The most expensive include transactional data like credit card spending, as well as location and web- and app-tracking data. About 30 percent of transactional data subscriptions, for example, cost more than $150, 000 a year, Neudata said. “To us, this makes perfect sense given that data providers operating in these three categories typically collect data on vast panels (often comprising millions of users), requiring a lot of work from the provider in terms of cleaning the data and preparing it for use by the investment world, ” the firm said in its 2020 report on data suming that asset managers use multiple data sets, it’s easy to see how costs could add up. Among hedge funds that were using alternative data in some capacity last year, more than a third spent more than $1 million on data annually, according to a 2019 survey by law firm Lowenstein Sandler.
[II Deep Dive: Hedge Funds Plan to Pour More Money Into Alternative Data]However, Neudata reported that alternative data has gotten cheaper, with more data subscriptions being offered at prices below $25, 000 — and some data being given away for free. “A common misconception is that useful alternative data is overwhelmingly expensive, ” the consulting firm said. “In reality, we find that datasets are more likely to fall within lower price brackets ($25k up to $150k per year) than the most expensive price brackets. ”Environmental, social, and governance datasets tended to be the cheapest, with over 40 percent of subscriptions tracked by Neudata costing less than $25, 000 annually. It was also the most likely to be free, although free datasets still made up less than 10 percent of all ESG data offerings.
Satellite and aerial data and sentiment data were the next cheapest categories, with about 30 percent of data subscriptions in each segment costing less than $25, 000 demand for alternative data is growing among institutional investors, including fundamental managers, Neudata said that this higher demand would not necessarily lead to higher prices. “The jury is still out on how the growing number of fundamental investors exploring the alternative data space will impact pricing over the long term, ” the consultant said. “One could argue that either 1) the resulting boost in demand for data will allow providers to sustain their existing price levels, or 2) providers will need to lower their prices to appeal to fundamental clients with lower budgets than quants. ”
Casting the Net – Alternative Investment Management …
The global economy and financial markets are always changing. With them, the information that hedge fund managers can gain from analysing the world around them also evolves. Consequently, the tools needed to extract data from such information need to adapt – successful investing, irrespective of what strategy or style one employs, depends to a good extent on gaining and maintaining a legitimate information edge over the rest of the market. To put it differently, for hedge fund managers to meet the investment needs of their clients, they need to have a greater understanding of how the world functions than their competitors.
While traditional sources of economic and financial knowledge, such as textbooks, industry literature and established data bases are excellent in providing a level-playing field for hedge fund managers, going above and beyond these commonly used sources is crucial for managers to remain innovative and therefore, to stay competitive. In doing so, more and more alternative investment funds are adopting a ‘quantamental’ approach, a blend of fundamental investing combined with a more quantitative approach. Central to this new way of thinking is the emergence of alternative data.
As a concept, alternative data is not new: for thousands of years market savvy business people have tried to understand their trading environment by looking at the world around them through different lenses and, from their observations, extracting data that, although not conventional, helped them to navigate the market successfully.
However, in recent years, enabled by the technological advancements across a number of industries, accessibility to alternative data sets has improved tremendously: with a growing number of alternative data providers, hedge fund managers now have access to a large number of non-traditional data sources, such as satellite imagery, social-media trends and weather patterns.
The aim of this publication is to offer an in-depth analysis of this topic, as well as to invite all stakeholders interested in how alternative data is being used by the hedge fund industry to further discuss its broader adoption. In it, you will discover how widely adopted alternative data is within the hedge fund industry, what are the main uses that managers are employing alternative data for, the opportunities and challenges that these data sets present and what the future holds for alternative data within the hedge fund sector.
We would like to thank AIMA’s research committee for their valuable input and for taking the time to discuss these findings. We would also like to thank the various asset managers for their generosity in contributing the several testimonials included throughout this paper, and to Eagle Alpha for their insight. Finally, thank you for taking the time to read this paper.
We would love to hear your thoughts.
Chief Executive Officer, AIMA
Managing Director, Regulatory Analytics and Data, SS&C Technologies
Managing Director, Regulatory Analytics and Data, SS&C Technologies
Change is the only constant in the known universe. Nowhere else is this truer than in the world of asset management, especially in alternative investments. Within this space, hedge funds continue to adapt to an evolving landscape of challenges and opportunities. Among other things, this includes adopting novel technologies for managing risks, researching investment ideas and, ultimately, generating alpha.
The Alternative Investment Management Association (AIMA), being well-positioned at the heart of the industry, has been witnessing this transformation first-hand. Moreover, AIMA has been assessing the impact of technology on hedge fund managers and their clients through a series of in-depth research papers, including the landmark publication “Perspectives”. This paper continues AIMA’s work in this space and, in collaboration with global fund service provider SS&C, it looks at how hedge fund managers are using alternative data.
As a concept, alternative data is not new. Indeed, it goes as far back as ancient Babylon when merchants used measurements of the Euphrates’ depth and flow to inform their decisions in trading various commodities, as they realised that these variables were correlated with market supply3. However, what is new in recent years is the increasing level of accessibility to this type of data. With a growing number of alternative data providers, hedge funds have access to a myriad of data sources, such as satellite imagery, social-media trends, and consumers’ shopping behaviour.
Considering how fast technology is moving, those that fail to adapt risk losing a potential advantage in the competitive race to deliver the rarest of returns – alpha. Consequently, most managers are in the process of updating their investment processes and business models in order to accommodate the growing amount of alternative data.
We hope you find this publication insightful and useful and we invite other stakeholders to join the conversation around alternative data within the hedge fund industry.
In order to collect the necessary data, we ran a survey to which 100 hedge fund managers responded, managing a total of about $720bn in assets. Additionally, we have collected insights from conversations with managers and alternative data providers.
“Casting the Net” is available to Members and Non-Members of AIMA. For more information about the report, contact AIMA’s Global Head of Research and Communications, Tom Kehoe, at [email protected]
Frequently Asked Questions about alternative data hedge funds
How much do hedge funds spend on alternative data?
Among hedge funds that were using alternative data in some capacity last year, more than a third spent more than $1 million on data annually, according to a 2019 survey by law firm Lowenstein Sandler.Jul 9, 2020
What data sources do hedge funds use?
With a growing number of alternative data providers, hedge funds have access to a myriad of data sources, such as satellite imagery, social-media trends, and consumers’ shopping behaviour.
What is alternative data?
What is Alternative Data? Alternative data refers to data used by investors to evaluate a company or investment that is not within their traditional data sources (financial statements, SEC filings, management presentations, press releases, etc.).