Market Data Blog
Market Data Blog
In the intricate and complex world of financial markets, one of the most critical elements is market data. In this post, we're going to dismantle some of the myths surrounding market data that I have come across in my career and shed light on the realities.
This is a commonly held misconception that I’ve encountered numerous times over my career. Often this relates to exchange-based data where specific fees normally apply for real-time rates. While it's true that fees for real-time data are generally higher, many exchanges still charge for access to their delayed data, albeit at a reduced rate. It's imperative for consumers to carefully examine the market data policies of each exchange to understand the costs associated with delayed data usage before making any presumptions about the absence of fees.
Many believe that when technology teams use market data for development and support, it's free of charge. However, this isn't a universal truth. Similar to the policies governing delayed data, the cost implications for IT usage can greatly vary. Certain vendors and exchanges permit the use of data at no cost for a set period during the development phase of a new application, while others may offer it at a reduced fee. Given this diversity in policies, it's crucial to consult with your data provider to understand their specific terms and conditions regarding the use of market data in development environments. Failure to do so could inadvertently lead to unexpected costs or compliance issues.
I was asked this by a senior executive who was sponsoring the development of a new portal that would display some market data to clients. The rationale was that the data they wanted to display was already available on sites like Yahoo Finance and could be “scraped” and used in the application.
The reality is sourcing data from another website in such a fashion would be explicitly prohibited in the terms of service and would likely result in legal action from both the website displaying the data and the intellectual property owner ie the exchanges providing the data. In this case, an agreement was negotiated with a market data vendor to provide the data for display on the customer portal.
The advantage of having extensive market data is not just in its quantity but in its quality and relevance. An overabundance of data can lead to 'analysis paralysis,' where the vast array of information impedes quick and informed decision-making. Organizations must focus on acquiring data that is pertinent to their specific goals and can be transformed into actionable insights.
This influx of data also impacts infrastructure and IT staff, necessitating enhanced systems capable of managing increased volumes, while maintaining performance and security. IT teams are faced with the dual challenge of upgrading their technological capabilities within budgetary constraints and ensuring their personnel are adept at navigating the complexities of modern data management. Success hinges on balancing the scale of data with the infrastructure's ability to handle it and the team's proficiency in utilizing it effectively.
There is a common misconception that market data is a commodity, easily interchangeable between sources. The reality is far more complex. Different vendors may excel in certain asset classes, offering distinct data strengths. Even exchange data, which one might assume is uniform across vendors, can present challenges when swapping due to inconsistent symbology (refer to my previous post for an in-depth discussion on this issue).
On the technical side, most vendors use proprietary distribution technologies, necessitating specialized feed handlers or modifications to applications that are processing this data. While migrating between vendors is feasible when data quality is on par, its important to recognize and plan for the additional technical hurdles that such a transition entails. Successful vendor changeovers require careful navigation through these complexities.
I hope this sample of some of the misconceptions around market data I’ve encountered was interesting, let me know your thoughts in the comments. Market data is a broad and complex topic from both a technical and commercial perspective. At Sprada we provide clients with the expertise to navigate these complexities to optimise market data spend and improve operational efficiency. Get it touch for a conversation about how we can assist with your market data challenges. Visit our website for more information.
In the intricate world of financial markets, understanding and managing market data symbology - the method of identifying and naming financial instruments across different markets - is crucial yet complex. This article delves into the challenges and impacts of this system on the financial industry.
A key hurdle is the absence of a universal standard. Different exchanges and data providers use distinct identifiers for the same instruments, leading to confusion and inefficiencies. For example, a stock listed on several exchanges might have different symbols on each, complicating data aggregation and analysis.
Many symbologies are proprietary, locking firms into specific data vendors and hindering competition and cost-effectiveness. Integrating data from varied sources poses another challenge, where ensuring quality and consistency is vital for accurate analysis and decision-making.
Technological solutions exist for mapping between symbologies, easing the transition between data sources. Yet, licensing issues can complicate this process. Some symbologies even require costly licenses for use and storage.
One potential solution is adopting an open symbology like OpenFIGI, mapping all data to this universal standard. However, this approach demands significant system overhauls and poses challenges in adaptability and cost.
The constant introduction of new financial products further complicates symbology management, necessitating ongoing updates. Emerging technologies like blockchain and AI offer promising avenues for more dynamic symbology systems but integrating these with existing systems while ensuring reliability and accuracy remains challenging.
In summary, the market data symbology landscape faces issues of standardization, global complexity, evolving products, and technological integration. A collaborative approach among market players, regulators, and tech providers is essential. Developing unified, adaptable, and advanced symbology systems is key for efficient market data management in the ever-evolving global financial markets.
According to industry analysts global spend on financial market data services is expect to rise more than 7% this year, putting global spend on market data services in excess of US$35B per annum.
Terminal spend is up 6% over the last 12 months and 13% since 2019, this may have been driven by additional terminals required to support work from home during the pandemic.
Research and Analytics is up 10% driven by ESG data requirements.
Pricing and Reference data is up 6% driven by a 15% increase in Bloomberg data license spend.