A storehouse for your proprietary data


With an ever-expanding set of data and analytics creating a greater challenge to find alpha, quants demand accurate time series data and can benefit from removing data management responsibilities. Enterprise data warehousing is a valuable well of efficiency companies can pull from in such times.

Big Data is nothing new to the financial services industry as the markets produce over 50 TB of data per day. The ability to collect and aggregate the data once for all use cases is a daunting challenge as each application requires different fields and frequencies of the data

OneTick is the ideal solution for the Enterprise which is seeking to aggregate and manage their time series data and analytics as an enterprise service, enabling traders, analysts, wealth managers and clients to access the same content delivered with the specific analytics relevant to each application.


  • High performance collection, aggregation and storage of time series data
  • Broad set of API’s, including web services and JSON formats
  • Sophisticated Content Entitlements system which enable and track usage


  • Real time and historical query and CEP capabilities
  • Eliminate the need for internal and 3rd party time series platforms
  • Reduce operational and hardware expenses associated with the collection of time series data



Quantitative Research

Discover the diamond in the mountain of coal 


Quants apply an empirically-tested and rules-based approach to exploit perceived market inefficiencies manifested by human behavior, geo-political events and market structure. With tighter spreads, thinner margins and lower risk appetite, quantitative traders are exploring more cross asset trading models and cross asset hedging. Consequently, the quest for new and revised models is never ending. The side effect of this is increasing demands for deep data over longer time periods across a multiplicity of markets -equities, futures, options and of course cross border currencies. This data dump is the fuel feeding automation technology, quant’s research and strategy modeling tools. That technology plays a critical role in the trade lifecycle. Its fast paced evolution goes hand-in-hand with innovations in trading.

Data accuracy is vital to determining outcomes; asset prices cannot be inaccurate or missing. It means dealing with the vagaries of multiple data sources, mapping ticker symbols across a global universe, tying indices to their constituents, tick-level granularity, ingesting cancellations and corrections, inserting corporation action price and symbol changes and detecting gaps in history. Any and all of these factors are vital to the science of quantitative trade modeling. With over five billion options contracts traded in 2014, the reliability of the resulting analytics such as implied volatility, delta and gamma for option strategies depend on underlying data accuracy and reliability. Big Data is about linking disparate data sets under some common thread to tease out intelligible answers to drive the creation of smarter trading models.


  • Comprehensive tools for data analysis and research
  • Large library of analytical functions
  • Integrated with R language and MATLAB
  • Asset class neutral across history and live markets


  • Perform in-depth alpha discovery across market microstructures and asset classes
  • Rapidly design, test and deploy algorithmic strategies
  • Same tools and services for research, algos and trade cost analysis

Algo Trading

Enable Effective Signal Generation


Today’s markets are pervaded by economic turmoil and regulatory overhang which have wrought havoc for some time. No longer can this be seen as a phase in the rapidly changing world of algorithmic trading - it is the new normal, and to navigate these volatile seas demands the ability to process massive amounts of data rapidly and efficiently, and, beyond that, to make sense of it all.

OneTick has been adopted by Algo trading leaders across four continents precisely because of its ability to do so. OneTick is an enterprise solution capable of capturing, storing and analyzing Big Data across any asset class, even the massive Options OPRA feed, which has spewed as many as four million messages a second. But it is also a focused solution for financial big data providing the scalable database, the analytics functions and user tools to uncover the narrative in the big data dump. Combined, these benefits form a potent tool for finding alpha and developing and testing strategies for algorithmic trading in today’s turbulent markets.

Data collection and aggregation can no longer reliably provide financial institutions with a competitive edge as each firm replicates the same collection of sources and formats for use in common applications. Customers bear the overhead of managing the collection for historical purposes and must dedicate skilled technical resources to maintain the environment. Public and private cloud platforms are increasingly being used by financial institutions to reduce costs and increase agility to address rapidly changing market conditions.


  • Intuitively design trade signaling logic using the OneTick Graphical Query Builder
  • Easily incorporate your own C++ code for generating trade signals
  • Move from algo design and research to live deployment in one easy step with OneTick
  • Integrated with many EMS or OMS systems


  • Quickly keep pace with dynamically changing markets conditions
  • Easily back test sophisticated algo logic to deploy with confidence
  • Slash strategy time from development to  production




Backtesting Strategy Software Service

Optimize Strategy Profitability


Research the quest for knowledge, an empirical investigation to discover the truth, establish factual evidence opinion aside, to solve existing problems and provide insight into new theories. With technological automation advancing rapidly the need to understand market dynamics, market micro-structure, the influences of geopolitical economics and central bank policy is more important than ever. The tumultuous market turmoil from events such as Knight Capital’s software glitch has sent jitters through market participants and motivated a renewed interested in strategy testing.

Backtesting is to measure profitability as strategies are optimized – this could be targets for profit factor, Sharpe ratio, max drawdown or an equity curve to improve the quality of execution decisions. Historical data sets provide “what if” market conditions as strategy parameters are varied.

Analyzing historical time series data is to use observations from the past to characterize data relationships. Those historical relationships can explain future developments with an assumption that the future behaves like the past. This forms the basis of backtesting trade models.

One Tick provides a fully featured strategy development and large-scale backtesting platform for the most discerning quant:

  • Evaluate alpha or execution strategy logic against controlled market replay
  • Vary and Optimize strategy parameters
  • Compare strategy instances using pre-defined and custom statistical measures
  • Exchange simulator matching engine
  • Ensure robustness of strategy logic
  • Customizable dashboards to plot/chart results


  • Built-in high precision analytical library for algorithm design
  • Built-in support for common performance metrics of P&L, Position management and other statistical measures (Sharpe Ratios, Drawdown) and extensible for user-defined statistics
  • Built-in exchange simulation (i.e. matching engine)
  • Support for large-scale historical ‘what-if’ analysis with generic search optimization
  • Leverage our hosted service complete with over 10 years of global equities and futures level 1 and level 2 market history


  • Unique, detailed and precise analysis for design and large-scale test of strategy algorithmic logic
  • Enhanced insight into execution performance and profitability across numerous statistical measures
  • Flexible and comprehensive solution to design, test and measure profitability for alpha and execution strategies
  • Low Total Cost of Ownership