In today’s fast-paced financial world, access to real-time, high-quality data has become a game-changer for investors at all levels. OpenBB’s mission to democratize advanced market data and make it accessible to everyone aligns seamlessly with the groundbreaking efforts of Pyth Network. To explore how Pyth is powering OpenBB’s real-time data feeds and transforming the investment landscape, we sat down with Michael Cahill, CEO of Douro Labs and a core contributor to Pyth Network. In this interview, Cahill shares insights on the partnership with OpenBB, the role of Pyth in leveling the playing field for non-institutional investors, and the future of financial data democratization.
Q1. OpenBB is being described as a $0 alternative to the Bloomberg Terminal, making advanced market data accessible to everyone. How is Pyth contributing to this mission by powering OpenBB’s real-time data feeds?
Pyth is fully aligned with OpenBB’s mission to democratize access to advanced market data. The network’s real-time data feeds are available to everyone, either on-chain via a secured, signed message through Wormhole, or off-chain without restrictions, ensuring accessibility across platforms. What differentiates Pyth is the breadth and depth of its data, sourced from a diverse group of trading firms, exchanges, and banks—many of whom are participating in the market data economy for the first time. This collaborative approach allows Pyth to provide institutional-grade data at a minimal cost, further advancing OpenBB’s goal of eliminating traditional barriers to financial information. Pyth’s partnership with OpenBB reflects a shared commitment to disrupting the centralized data monopoly and empowering users with the tools they need to make informed decisions in real time.
Q2. The integration of 405 free data sources, including Pyth Price Feeds, transforms the investment research process. How does this open access reshape opportunities for non-institutional investors?
This integration provides one of the most comprehensive sets of real-time data available to non-institutional investors, offering access as close to time-zero as possible. The market data industry generates nearly $7 billion in revenue, with most of the value concentrated in the first 15 minutes of data availability. After that period, much of the data becomes public. The advantage of using Pyth data is that it’s only delayed by 400 milliseconds, and it’s freely accessible to anyone through OpenBB or any other platform powered by Pyth. This democratization of tools and data opens the door for non-professional investors to develop sophisticated trading strategies that were once exclusive to institutions alone. Historically, the barrier to entry for creating algorithmic trading strategies has been the need to purchase prohibitively costly market data packages from providers or buy access to a Bloomberg Terminal for tens of thousands of dollars—blocking 99% of individuals from participating.
Q4. Considering OpenBB’s focus on ease of use (e.g., no coding required, simple setup), how does Pyth’s data integration enhance the user experience for those unfamiliar with traditional financial tools like Bloomberg?
Pyth’s data integration helps lower the barrier to entry, enabling more people to test strategies, conduct research, and become better-informed traders. What’s truly transformative is that tools once reserved for a select few are now accessible to the broader public. The astronomical cost of traditional financial tools has long created an unbreachable moat around the industry. By providing fair and equitable access to advanced market data, Pyth and OpenBB are not only leveling the playing field, but fostering greater innovation and value creation for users on a global scale.
Q5. The OpenBB Terminal Pro provides charting capabilities similar to TradingView. How do Pyth’s real-time price feeds complement these charting features for more advanced market analysis?
Pyth’s real-time price feeds bring institutional-grade market data directly into the charting features of OpenBB Terminal Pro, enabling users to perform more advanced and accurate market analysis. Unlike delayed data, Pyth provides price updates every 400 milliseconds, ensuring that traders and analysts have access to the most up-to-date market conditions. This immediacy is crucial for those relying on technical analysis and precision timing, as they can identify market trends, price movements, and liquidity shifts in real time. In addition to powering OpenBB’s advanced charting, Pyth also provides real-time data to TradingView, further extending its reach and allowing users across multiple platforms to benefit from high-quality, low-latency market data.
Q6. In your view, what is the most significant impact that OpenBB will have on the investment research landscape by offering a free, AI-enhanced alternative to tools traditionally reserved for elite investors?
OpenBB’s greatest impact will be democratizing access to institutional-grade data and advanced analytical tools that were previously out of reach for most investors. By integrating Pyth’s real-time, high-quality market data, OpenBB enables non-institutional investors to leverage the same insights and tools as elite professionals. This combination of free, AI-enhanced research capabilities and cutting-edge data reshapes the investment landscape, empowering more people to make informed decisions and develop sophisticated strategies without the financial barriers of traditional platforms.
Q7. With Pyth’s data making a free, AI-powered investment research tool accessible to everyone, what trends do you foresee in the democratization of financial data?
As more people gain access to institutional-grade financial data, we expect to see a surge in active portfolio management by individual investors. There’s a clear appetite for participation in markets, as evidenced by the rise of memecoins. However, with tools like OpenBB powered by Pyth’s real-time data, investors will have the ability to engage in more meaningful trades, focusing on assets that generate revenue and long-term value. This shift from speculative trading to more informed, data-driven strategies will drive broader market participation and help individual investors make more sophisticated decisions in addition to breaking down barriers to entry.
Q8. What challenges do you anticipate in maintaining the accuracy and reliability of Pyth’s real-time data feeds as platforms like OpenBB scale?
As platforms like OpenBB scale, the primary challenge for Pyth will be expanding the breadth of data coverage while maintaining the low-latency updates that set the network apart. Currently, Pyth offers around 500 symbols with data refreshed every 400 milliseconds, but there is significant potential to increase both the number of assets and the frequency of updates. Scaling these capabilities while ensuring accuracy and reliability across both on-chain and off-chain platforms will be critical. However, Pyth is continually evolving, and both OpenBB and other platforms will benefit from its ongoing commitment to delivering high-quality, real-time data at ever-increasing levels of scale.
Q9. Total Transaction Value (TTV) is increasingly becoming a critical metric in evaluating oracles. Could you explain how Pyth’s focus on TTV helps better measure oracle performance and revenue potential?
In traditional markets, the majority of market data revenue is generated by real-time transaction data, largely due to the high turnover on exchanges. Total Transaction Value (TTV) aligns closely with this model, as it reflects the volume of transactions that oracles facilitate. In contrast, Total Value Secured (TVS) is more akin to assets under management, where the data that matters most tends to be index-based and formulaic. Given the current state of crypto markets, where mature index products are not yet prevalent, evaluating oracles based on TTV provides a more accurate reflection of their performance and revenue potential. Focusing on TTV allows Pyth to measure how much transaction volume its oracle drives, which is a more relevant metric in a fast-moving market like crypto.
Q10. With derivatives markets booming, how do you see Pyth playing a role in delivering real-time data that drives the growth of these financial instruments?
On-chain derivatives volumes have surged over the past year, growing from 1% to 8% of Binance’s perpetuals volume, and Pyth is securing around 65% of all on-chain derivatives DEXs. To date, Pyth has played a critical role in this growth by providing real-time, accurate price data that is essential for derivatives trading. The network focuses on expanding the range of supported symbols, reducing latency, and ensuring data accuracy to meet the high demands of this market. Additionally, the introduction of Oracle Incentive Systems (OIS) further enhances the precision and economic security of Pyth’s data, offering application builders even greater reliability for derivatives trading.
Q11. In terms of the frequency of oracle price updates, what advancements or strategies does Pyth employ to ensure the most accurate and timely data for traders?
Pyth’s architecture is designed to eliminate unnecessary costs and latencies, ensuring the fastest and most accurate data delivery. One key strategy is having data providers—such as trading firms and exchanges—submit their data directly to Pyth, bypassing traditional data aggregators. This direct submission not only reduces the time and cost associated with middlemen, but also guarantees the integrity of the data, maintaining a clear chain of ownership. In contrast to models where using aggregated data can sometimes violate terms of service, Pyth’s approach incentivizes publishers to submit data free from restrictions, making it publicly available and blockchain-ready in real time.
Q12. Looking ahead, what are Pyth’s long-term goals in terms of expanding its real-time data offerings, and how do you envision its role evolving in transforming the financial data ecosystem through partnerships like the one with OpenBB?
Pyth’s long-term vision is to scale its real-time data offerings to encompass tens of thousands, or even hundreds of thousands, of data symbols, with even greater precision than what is available today. While certain asset categories are particularly suited to DeFi applications, Pyth is eager to expand its coverage across a broad range of assets, including equities, FX, interest rates, and commodities. Currently, of the 500 symbols available, 75 fall within the real-world assets (RWA) category, and we see significant potential to grow this even more in the future. Through partnerships like OpenBB, Pyth is revolutionizing the financial data ecosystem by delivering broader, faster, and more inclusive access to real-time data. This approach empowers a global audience—from institutional investors to everyday traders—with the tools to make smarter, data-driven decisions. In this way, Pyth is driving innovation and participation across all levels of the market.
Conclusion
As Michael Cahill highlighted, Pyth Network’s collaboration with OpenBB is revolutionizing access to real-time market data, offering non-institutional investors tools that were once the exclusive domain of large institutions. By providing institutional-grade data at low cost and ensuring seamless accessibility across platforms, Pyth is at the forefront of a financial data revolution. With a shared commitment to breaking down traditional barriers, Pyth and OpenBB are empowering traders and investors globally, shaping a future where advanced data-driven strategies are within reach for all.
