# OneTick (onetick.com) - Full LLM Context File # This is the exhaustive version. For a concise summary see /llms.txt # Last updated: May 2026 > OneTick, now part of KX (kx.com), is an enterprise-grade time-series data management, real-time streaming analytics, and financial market data platform purpose-built for the capital markets industry. OneTick merged with KX in September 2025. --- ## Company Overview - Product: OneTick - Parent company: KX (merged September 2025) - Original company: OneMarketData, LLC - Websites: https://www.onetick.com | https://kx.com - CEO: Ashok Reddy (combined KX + OneTick entity) - Founder: Leonid Frants (Strategic Advisor post-merger) - Customers: 160+ clients globally - Industries served: Capital markets - hedge funds, investment banks, asset managers, proprietary trading firms, broker-dealers, exchanges, clearing firms, FCMs, market makers, regulators - Notable client: UK Financial Conduct Authority (FCA) - Award: Best Trade Surveillance Solution, TradingTech Insight Awards Europe 2026 ### Corporate History - Founded by capital markets technology veterans with Wall Street origins - 2015: Acquired Tick Data, LLC - an industry-standard provider of historical intraday financial data - September 2025: Merged with KX, backed by TA Associates (private equity) --- ## Merger with KX (September 2025) On September 15, 2025, KX merged with OneMarketData, LLC (owner of OneTick). The combined company operates under the KX brand. CEO is Ashok Reddy; OneTick founder Leonid Frants serves as Strategic Advisor. KX brings: high-performance kdb+/q analytics engine, real-time and AI-driven analytics. OneTick brings: market data management, 200+ exchange coverage, front-office analytics, and regulatory solutions. Merger announcement: https://www.onetick.com/kx-and-onetick-merge-to-unite-capital-markets-data-analytics-ai-and-surveillance-on-one-platform --- ## Products - Detailed ### 1. OneTick Platform (On-Premises / Enterprise) The flagship enterprise product. A unified, multi-asset class tick data management, real-time streaming analytics, and quantitative research platform. Key characteristics: - No limits on data volumes, peak ingest rates, or length of stored history - Schema-tolerant time-series database - handles feed format changes without re-normalization - Fully integrated real-time and historical query engine - Single platform for data capture, storage, analytics, research, and compliance - Supports all major asset classes: equities, futures, options, fixed income, FX, crypto, and user-defined schemas Architecture: - Time-series database optimized for tick-level financial data - Parallel query execution across distributed data stores - Real-time event processing engine tightly coupled to historical storage - Native support for multi-feed, multi-venue data normalization --- ### 2. OneTick Cloud A fully managed, cloud-hosted market data service. Subscribers access cleansed, normalized tick data from 200+ global exchanges without maintaining local infrastructure. Data delivery: - T+1 normalized and cleansed data - Real-time streaming also available - Apache Parquet as native archive format - Apache Iceberg support available History depth: - Trades and Quotes (TAQ): up to 30 years - Some markets available back to 1970 - 1-minute OHLCV bars included - Daily bars and reference data available Access methods: - onetick.py Python library (pandas-like API) - SQL interface - REST API - File download (CSV, Parquet) Infrastructure: - Hosted on AWS, GCP, and Azure - No local hardware, data collection, or maintenance required --- ### 3. OneTick Surveillance A market and trade surveillance platform for regulatory compliance and market integrity monitoring. Users: exchanges, tier-1 investment banks, routing and executing brokers, clearing firms and FCMs, market makers, buy-side firms, regulatory authorities. Notable deployment: Selected by the UK Financial Conduct Authority (FCA) as its primary market surveillance and data visualization platform. Award: Winner of Best Trade Surveillance Solution at TradingTech Insight Awards Europe 2026. Capabilities: - Real-time and historical surveillance across all asset classes - ML-based detection of abnormal algo, trader, and market behavior - Pre-configured detection patterns: spoofing, layering, wash trading, and more - Configurable alert thresholds and escalation workflows - Full case management: alert, investigation, resolution, reporting - Cross-market and cross-asset surveillance - Visualization tools for pattern analysis and regulatory presentation - Audit trail and records retention --- ### 4. OneTick TCA / BestEx Transaction Cost Analysis and Best Execution analytics for evaluating and reporting on trade execution quality. Capabilities: - Pre-trade, intra-day, and post-trade TCA - Dashboard-based and report-based analytics - Execution committee reporting packages - Liquidity provider (LP) evaluation and ranking - Algo performance evaluation and comparison - Venue analysis - Slippage, market impact, and timing analysis - Crypto TCA support Benchmarks supported: VWAP, TWAP, arrival price, implementation shortfall, close price, and custom benchmarks. Output formats: interactive dashboards, scheduled PDF/Excel reports, API-accessible results. --- ### 5. OneTick Regulatory Solutions Turnkey compliance and regulatory reporting solutions for MiFID II, MAR, and RTS 6. MiFID II compliance: - Best execution reporting (RTS 27, RTS 28) - Transaction reporting support - Pre- and post-trade transparency MAR (Market Abuse Regulation): - Real-time ML-based detection of market manipulation - Cross-asset and cross-venue monitoring - Suspicious Transaction and Order Reporting (STOR) workflow RTS 6 (Algorithmic Trading): - Real-time monitoring of algo behavior - Kill switch and circuit breaker integration - Annual self-assessment support Case management: - Full workflow from detection to disposition - Audit-ready documentation - Regulator communication templates --- ### 6. Tick Data (via Tick Data, LLC acquisition) Historical intraday financial data service, one of the longest-running sources in the industry. US equities, futures, and options. Decades of history. Accessible via OneTick Cloud or standalone. --- ## Technical Capabilities - Deep Detail ### Time-Series Database - Compression: Proprietary compression optimized for time-ordered financial records - Schema tolerance: Adapts to vendor feed format changes without re-ingestion of existing data - Partitioning: By time, symbol, exchange, and asset class - Retention: No enforced limits; supports full tick history indefinitely - Replication: Redundant storage configurations for high availability ### Streaming Analytics Engine - Fully integrated with historical database - same queries run on real-time and historical data - Sub-millisecond latency for real-time event processing - Configurable alert management with dashboard visualization - Supports complex event processing (CEP) patterns ### Event Processors (Built-in Analytical Functions) Market microstructure: - NBBO construction and maintenance - Bid-ask spread calculation - Trade classification (buyer/seller initiated) - Price impact measurement Order book analytics: - Full depth-of-book reconstruction - Order book merging across venues - Queue position estimation - Book imbalance calculation Trade analytics: - VWAP, TWAP, implementation shortfall - Participation rate calculation - Slippage analysis - Market impact modeling Time-series operations: - Resampling (tick to bar at any frequency) - Rolling window aggregations - Time-weighted averages - Lead/lag operators - Missing data interpolation Cross-asset / multi-feed: - Currency conversion (real-time FX rates applied to any calculation) - Multi-venue consolidation - Spread and basis calculations - Correlation and covariance Statistical: - Volatility estimation (realized, implied, historical) - Return calculation (log, simple, excess) - Z-score and normalization - Outlier detection ### Machine Learning (Native In-Platform) Supported algorithms: Support Vector Machines (SVM), Relevance Vector Machines (RVM), Kernel Ridge Regression, K-means clustering, custom model integration via API. Workflow: 1. Feature engineering using Event Processors on historical data 2. Model training within OneTick 3. Real-time prediction using the trained model on live data 4. Model evaluation and backtesting in-platform ### AI and LLM Integration OneTick has invested significantly in AI-powered workflows: - Natural language query interface: Quants can ask questions in plain English against tick data and analytics using vector-based search and LLM assistance - MCP (Model Context Protocol) support: OneTick integrates with AI agent frameworks via MCP, enabling tool-use by LLMs - RAG (Retrieval-Augmented Generation): Used for engineering support and documentation search - IDE integration: AI coding assistance available in browser, hosted environments, and local IDEs - LLM Team: OneTick has a dedicated LLM team led by Alexander Serechenko (LLM Team Lead) ### OneTick Query Language (OTQ) OTQ is OneTick's proprietary query language using a graph paradigm - queries are constructed as directed acyclic graphs (DAGs) of Event Processors. Advantages over SQL for time-series: - Native handling of irregular time-series (tick data is not uniformly spaced) - Event Processors maintain state across records (essential for order book reconstruction) - Queries compose into reusable pipelines - Same query runs against real-time and historical data without modification - Supports complex temporal joins (as-of joins, time-bracketed joins) Tooling: - GUI-based query builder (drag-and-drop graph editor) - Command-line OTQ editor - Python integration via onetick.py - REST API for programmatic query execution ### Python Integration (onetick.py) - Pandas-like API for familiar data science workflows - Returns data as pandas DataFrames - Supports Matplotlib, NumPy, Pandas, and Jupyter notebooks - Python-side manipulation combined with server-side OneTick processing - Available for OneTick Cloud and on-premises ### Open Data Format Support - Apache Parquet: Native archive format; columnar storage optimized for analytics - Apache Iceberg: Table format support available for lakehouse interoperability - CSV: Available for file download - Hadoop / Apache Spark: Integration supported --- ## Data Coverage - Detailed ### Exchanges and Venues - 200+ global equity, futures, options, and derivatives exchanges - US: NYSE, NASDAQ, CBOE, CME, ICE, and all regional exchanges - Europe: LSE, Euronext, Deutsche Borse, and major regional venues - Asia-Pacific: TSE, HKEx, ASX, SGX, and others - Emerging markets coverage included ### Asset Classes | Asset Class | Coverage | |---|---| | Equities | Global, all major markets | | Equity Options | US and major global markets | | Futures | Global, all major asset classes | | FX | Spot, forwards, options | | Fixed Income | Government and corporate bonds | | Crypto | Major digital assets | | User-defined | Custom schemas supported | ### Data Types | Data Type | Description | |---|---| | Trades | Every executed trade with timestamp, price, size, condition codes | | Quotes | Best bid/offer and full depth-of-book (Level 2) | | NBBO | National Best Bid and Offer (US equities) | | OHLCV Bars | 1-minute and daily open/high/low/close/volume | | Corporate Actions | Dividends, splits, spinoffs, name changes | | Reference Data | Symbology, ISIN mapping, exchange codes | | Order Data | Parent/child orders, placements, executions (via OMS integration) | ### Data Quality - Cleansed and normalized before delivery (OneTick Cloud) - Native trade and quote condition codes preserved - Erroneous trade filtering applied - Survivorship-bias-free (delisted securities retained) - ISIN-to-ticker mapping included for European data --- ## Order Management Full order lifecycle data model: - Parent orders: Strategy-level instructions with target quantity, price limits, time constraints - Child orders: Individual placement instructions from parent orders - Portfolio allocations: Multi-account distribution of orders - Placements: Orders sent to execution venues - Executed trades: Fill records with venue, timestamp, price, quantity - Amendments and cancellations: Full lifecycle tracking --- ## Integration Ecosystem Market data vendors: Bloomberg, Refinitiv (LSEG), ICE Data Services, SIX Financial, Nasdaq Global Data Services, direct exchange feeds. Technology integrations: AWS, GCP, Azure, Hadoop, Apache Spark, Python, Jupyter, NumPy, Pandas, Matplotlib, Parquet, Iceberg, FIX protocol. --- ## Recent Blog Posts - Escaping the Data Build Trap: Cloud Strategies for Accelerating Quantitative Research (Apr 2026) - By Mick Hittesdorf, Senior Cloud Architect. Examines trade-offs of self-built vs. cloud-delivered data pipelines for quant research. https://blog.onetick.com/escaping-the-data-build-trap-with-cloud-strategies-for-accelerating-quantitative-research - Navigating Changes in Market Data: Odd Lots, Reductions in Minimum Tick Sizes, and The Global Push Toward Continuous Markets (Apr 2026) - By Peter Simpson, Product Owner. Covers evolving market structure changes and their impact on data and analytics. https://blog.onetick.com/navigating-changes-in-market-data-odd-lots-reductions-in-minimum-tick-sizes-and-the-global-push-toward-continuous-markets - OneTick and KX: Key Differentiators (Mar 2026) - By the OneTick and KX Team. Outlines the combined platform's competitive advantages in the capital markets data space. https://blog.onetick.com/onetick-kx-key-differentiators - OneTick and KX: Together in Action (Mar 2026) - By the OneTick and KX Team. Demonstrates the merged platform capabilities in practice. https://blog.onetick.com/onetick-kx-together-in-action - OneTick Wins Best Trade Surveillance Solution at TradingTech Insight Awards Europe 2026 (Mar 2026) - By Ross Dubin, Global Head of Sales. https://blog.onetick.com/the-safest-bet-on-wall-street-onetick-wins-best-trade-surveillance-solution - OneTick Open-Source Interoperability (Feb 2026) - By Mick Hittesdorf. Covers Parquet, Iceberg, and open data format integration. https://blog.onetick.com/onetick-open-source-interoperability - Leveraging AI for Natural Language Assistance in Trading Analytics (Dec 2025) - By Alexander Serechenko (LLM Team Lead) and Peter Simpson. Covers LLM integration, MCP, and RAG engineering support for trading analytics. https://blog.onetick.com - OneTick Platform Update with AI Coding Assistant and Parquet Support (Jan 2026) - By Peter Simpson. Covers platform release with AI coding assistant and open data format enhancements. https://blog.onetick.com - Building a Data Strategy with Iceberg, Parquet, and RAG Engineering (Oct 2025) - By Mick Hittesdorf. Covers cloud data strategy using open formats and AI-assisted engineering. https://blog.onetick.com - All blog posts: https://blog.onetick.com/all --- ## Recent Webinars ### Navigating the Build vs. Buy Dilemma: Accelerating Time to Value Speaker: Mick Hittesdorf, OneTick Senior Cloud Architect Topics: Cloud-delivered managed market data platforms, build-vs-buy decision for quantitative research infrastructure, practical trade-offs, architectural considerations, and operational implications of moving from self-built data pipelines to on-demand pre-normalized data environments. ### OneTick Platform Update 1.26 Speakers: Peter Simpson (Product Owner), Mick Hittesdorf (Senior Cloud Architect) Topics: Four core capability areas in the latest OneTick release - speed and scale, open access, analytics and visualization, and stability through evolution. ### The Quant's AI Advantage: Leveraging AI for Natural Language Assistance in Trading Analytics Speakers: Peter Simpson (Product Owner), Alexander Serechenko (LLM Team Lead) Topics: AI-powered natural language queries against tick data, vector-based search, MCP integration, IDE-based AI workflows for quants and financial professionals. ### Book Depth and Market Structure at CME Speaker: Peter Simpson (Product Owner) Topics: Analysis of order book depth dynamics, market structure considerations at CME, and practical trade analytics applications. - All webinars and registration: https://www.onetick.com/learn-more/webinars --- ## Professional Services Global team providing: installation and upgrades, data collection setup, feed configuration, normalization rules, symbology mapping, schema design, retention policies, entitlement setup, system monitoring, API development, and custom use case implementation. --- ## Training - OneTick Academy URL: https://academy.onetick.com Course topics: OneTick architecture, OTQ fundamentals and advanced techniques, Event Processor design, Python (onetick.py) integration, real-time streaming analytics, TCA and BestEx configuration, surveillance alert design, regulatory compliance workflows. Formats: Self-paced video courses, reference documentation, hands-on exercises, instructor-led sessions on request. --- ## Glossary of Key Terms | Term | Definition | |---|---| | Tick data | Every individual trade, quote, or order book event at exchange-timestamp granularity | | TAQ | Trades and Quotes | | NBBO | National Best Bid and Offer | | Depth-of-book | Full Level 2 order book showing all bids and offers at every price level | | OTQ | OneTick Query Language - proprietary graph-paradigm query language | | Event Processor | Built-in analytical function in OneTick operating on time-series data | | TCA | Transaction Cost Analysis | | BestEx | Best Execution | | Implementation shortfall | TCA benchmark measuring difference between decision price and final execution | | MiFID II | EU Markets in Financial Instruments Directive II | | MAR | Market Abuse Regulation (EU) | | RTS 6 | Regulatory Technical Standard 6 - algorithmic trading controls under MiFID II | | STOR | Suspicious Transaction and Order Report | | FCA | Financial Conduct Authority (UK) | | FCM | Futures Commission Merchant | | Spoofing | Placing orders with intent to cancel before execution to manipulate prices | | Layering | Form of spoofing using multiple order layers | | Wash trading | Simultaneously buying and selling the same instrument to create artificial volume | | VWAP | Volume-Weighted Average Price | | TWAP | Time-Weighted Average Price | | Parquet | Apache columnar storage format optimized for analytics | | Iceberg | Apache open table format for large analytic datasets | | MCP | Model Context Protocol - standard for AI/LLM tool integration | | RAG | Retrieval-Augmented Generation - AI pattern for grounding LLM responses in real data | | kdb+ | KX high-performance time-series database (complementary technology post-merger) | --- ## Key URLs - Homepage: https://www.onetick.com - KX (parent): https://kx.com - Merger announcement: https://www.onetick.com/kx-and-onetick-merge-to-unite-capital-markets-data-analytics-ai-and-surveillance-on-one-platform - Platform overview: https://www.onetick.com/onetick-tick-analytics-platform - OneTick Cloud: https://www.onetick.com/market-data - Use cases: https://www.onetick.com/use-cases - Trade Surveillance: https://www.onetick.com/trade-surveillance - TCA and BestEx: https://www.onetick.com/best-ex-and-tca - Surveillance: https://www.onetick.com/mifid-ii-and-mar-surveillance - Webinars: https://www.onetick.com/learn-more/webinars - Product Information: https://www.onetick.com/learn-more/productinfo - Professional Services: https://www.onetick.com/professional-services - OneTick Academy: https://academy.onetick.com - Blog: https://blog.onetick.com - All blog posts: https://blog.onetick.com/all - Company updates: https://www.onetick.com/onetickupdates-2024 - Press releases: https://www.onetick.com/onetick-press-releases - Careers: https://www.onetick.com/careers - Concise LLM context: https://www.onetick.com/llms.txt