Dune Analytics has introduced a unified dataset that brings together data from Polymarket and Kalshi, offering a valuable new resource for macro, equity, and quantitative researchers. The platform now delivers clean, easily queryable information that includes hourly candlestick prices, detailed per-fill trades, position-level insights, and a history of resolved markets going back four years.
Dune Analytics also mentioned that prediction markets have grown into instruments that price real-world events where participants put real capital at stake.
These platforms now address catalysts that impact investment portfolios, ranging from Federal Reserve policy choices and earnings results to tariff implementations, merger approvals, commodity settlements, and geopolitical shifts.
What sets them apart from traditional polls or analyst predictions is their ability to reflect ongoing probability adjustments based on traders with genuine financial exposure, delivering dynamic and market-validated signals.
In the past, integrating this type of data into analytical workflows demanded considerable technical resources, including handling separate APIs, onchain indexing, differing data structures, and continuous upkeep.
Dune Analytics explained that it has simplified the entire process by providing a standardized, ready-to-use source that can be accessed through SQL queries or integrated directly into data warehouses.
The combined dataset presents both platforms under a consistent schema within the prediction markets tables. This setup allows for effortless cross-platform comparisons, probability tracking, positioning analysis, and signal validation without the need for platform-specific adjustments.
The coverage spans several critical domains.
In finance and macro research, the data encompasses detailed pricing for Federal Reserve rate decisions at various thresholds, CPI releases, employment figures, government shutdown risks, debt ceiling concerns, and equity-specific events such as single-name price targets for companies like AAPL and NVDA, S&P 500 inclusions, earnings thresholds, and merger outcomes.
Analysts can examine complete probability distributions instead of relying on single point forecasts, which supports better duration management and event-driven investment strategies.
Dune Analytics pointed out that users can also conduct robust back-testing against historical outcomes dating back to June 2021.
On the political and policy front, markets covering elections, trade policies, tariffs, and regulatory changes deliver actionable insights for sector rotations in areas like defense, energy, healthcare, and globally exposed equities.
These signals help identify potential policy regime shifts that could impact market performance.
In crypto and technology, the dataset tracks token price levels, ETF approval chances, governance decisions, and antitrust developments.
This information proves especially useful for technology and crypto-related stocks, with Polymarket’s wallet data integrating smoothly into Dune’s broader onchain analytics ecosystem for deeper attribution analysis.
Global events receive strong attention as well, with coverage of geopolitical risks and international trade resolutions that inform strategies around commodities, defense, and energy exposure.
Accessibility varies by platform. Polymarket provides access to probabilities, market metadata, and basic trades onchain via Polygon since late 2022, while enterprise users gain advanced features like smart-money tracking and conviction analysis.
Kalshi, operating as a CFTC-regulated exchange, offers free daily summaries but requires enterprise access for granular per-fill details and extensive hourly data series stretching back to June 2021, making it particularly suited for thorough historical testing around economic events.
This integration comes at a time when prediction markets are showing increased relevance in professional research.
Quantitative teams are leveraging them for timing advantages on tariffs, earnings, and policy developments, incorporating crowd-sourced probabilities into broader equity and macro strategies.
By managing the complex work of data collection and normalization, Dune Analytics has made these markets far more practical for both institutional and independent analysts.
What was once a somewhat niche data source is now gradually transforming into a reliable, back-testable component for informed portfolio decision-making. Dune Analytics has concluded that as prediction markets continue to mature and expand across jurisdictions, their impact as real-time probability engines is expected to grow significantly within research frameworks.
