Proprietary Generative AI Model
Like an LLM for market time series data
Traditional back testing relies on historical data, limiting your ability to anticipate evolving market dynamics. Our proprietary generative AI creates realistic, high-fidelity synthetic data, allowing traders to test strategies with unlimited, realistic market scenarios based on the current market regime.
Strategy Gym
Every trade influences the market
Our Strategy Gym lets you engage directly with our data generation process, giving you the most realistic sense of the market impact of your trades. Simulate market conditions, improve the expectation of your strategy’s performance and hyper-optimize its parameters.
Level 3 Data
Build on the most granular data
Research, develop and deploy your strategy on level 3 order book data, with queue tracking, timestamped at the nanosecond level. Directly impute your orders into the order book using our strategy testing engine for the most realistic simulation.
Team
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Andrew Dennehy
AI
Daniel Gold
CEO
Eran Cohen
Head Developer
Connect with us
Proprietary Generative AI Model
Like an LLM for market time series data
Traditional back testing relies on historical data, limiting your ability to anticipate evolving market dynamics. Our proprietary generative AI creates realistic, high-fidelity synthetic data, allowing traders to test strategies with unlimited, realistic market scenarios based on the current market regime.
Proprietary Generative AI Model
Like an LLM for market time series data
Traditional back testing relies on historical data, limiting your ability to anticipate evolving market dynamics. Our proprietary generative AI creates realistic, high-fidelity synthetic data, allowing traders to test strategies with unlimited, realistic market scenarios based on the current market regime.
Strategy Gym
Every trade influences the market
Our Strategy Gym lets you engage directly with our data generation process, giving you the most realistic sense of the market impact of your trades. Simulate market conditions, improve the expectation of your strategy’s performance and hyper-optimize its parameters.
Strategy Gym
Every trade influences the market
Our Strategy Gym lets you engage directly with our data generation process, giving you the most realistic sense of the market impact of your trades. Simulate market conditions, improve the expectation of your strategy’s performance and hyper-optimize its parameters.
Level 3 Data
Build on the most granular data
Research, develop and deploy your strategy on level 3 order book data, with queue tracking, timestamped at the nanosecond level. Directly impute your orders into the order book using our strategy testing engine for the most realistic simulation.
Level 3 Data
Build on the most granular data
Research, develop and deploy your strategy on level 3 order book data, with queue tracking, timestamped at the nanosecond level. Directly impute your orders into the order book using our strategy testing engine for the most realistic simulation.
Team
Daniel Gold
CEO
Master’s graduate with a degree in CAM from University of Chicago, with a foundation in economics and mathematics from Mount Allison University. As an M&A researcher at Constellation Software, Daniel sourced potential acquisitions, engaging CEOs, VC, PE and decision makers. Daniel's primary responsibilities are customer acquisition, product management and statistical research.
Daniel Gold
CEO
Master’s graduate with a degree in CAM from University of Chicago, with a foundation in economics and mathematics from Mount Allison University. As an M&A researcher at Constellation Software, Daniel sourced potential acquisitions, engaging CEOs, VC, PE and decision makers. Daniel's primary responsibilities are customer acquisition, product management and statistical research.
Ruihong Huang
CTO
PhD in Applied Econometrics from Humboldt University in Berlin. Ruihong has extensive experience in quant trading, having served in senior roles at Credit Suisse, Barclays and UBS. During his PhD, Ruihong founded LOBSTER Data, the preeminent dataset in academic limit order book research. Ruihong’s expertise centers around high frequency data. Ruihong’s role is as technology team lead and CTO.
Ruihong Huang
CTO
PhD in Applied Econometrics from Humboldt University in Berlin. Ruihong has extensive experience in quant trading, having served in senior roles at Credit Suisse, Barclays and UBS. During his PhD, Ruihong founded LOBSTER Data, the preeminent dataset in academic limit order book research. Ruihong’s expertise centers around high frequency data. Ruihong’s role is as technology team lead and CTO.
Eran Cohen
Head Dev
Graduated Summa Cum Laude from the Technion with a BSc in Computer Science. Eran is a Software Engineer with expertise in developing simulations, computer graphics frameworks, and high-performance distributed database systems, gained through his work in the Israeli defense industry at Rafael and later at Microsoft.
Eran Cohen
Head Dev
Graduated Summa Cum Laude from the Technion with a BSc in Computer Science. Eran is a Software Engineer with expertise in developing simulations, computer graphics frameworks, and high-performance distributed database systems, gained through his work in the Israeli defense industry at Rafael and later at Microsoft.
Andrew Dennehy
AI
Third year PhD student in Computational and Applied Mathematics (CAM) at the University of Chicago, holding an Honors degree in applied mathematics from UC San Diego. Andrew's expertise lies in machine learning and statistical methods, honed through his extensive professional experience as an ML Engineer at Leidos Inc. His primary role involves leading the development of innovative experimentation frameworks and generative AI models.
Andrew Dennehy
AI
Third year PhD student in Computational and Applied Mathematics (CAM) at the University of Chicago, holding an Honors degree in applied mathematics from UC San Diego. Andrew's expertise lies in machine learning and statistical methods, honed through his extensive professional experience as an ML Engineer at Leidos Inc. His primary role involves leading the development of innovative experimentation frameworks and generative AI models.
Connect with us
Proprietary Generative AI Model
Like an LLM for market time series data
Traditional back testing relies on historical data, limiting your ability to anticipate evolving market dynamics. Our proprietary generative AI creates realistic, high-fidelity synthetic data, allowing traders to test strategies with unlimited, realistic market scenarios based on the current market regime.
Proprietary Generative AI Model
Like an LLM for market time series data
Traditional back testing relies on historical data, limiting your ability to anticipate evolving market dynamics. Our proprietary generative AI creates realistic, high-fidelity synthetic data, allowing traders to test strategies with unlimited, realistic market scenarios based on the current market regime.
Strategy Gym
Every trade influences the market
Our Strategy Gym lets you engage directly with our data generation process, giving you the most realistic sense of the market impact of your trades. Simulate market conditions, improve the expectation of your strategy’s performance and hyper-optimize its parameters.
Strategy Gym
Every trade influences the market
Our Strategy Gym lets you engage directly with our data generation process, giving you the most realistic sense of the market impact of your trades. Simulate market conditions, improve the expectation of your strategy’s performance and hyper-optimize its parameters.
Level 3 Data
Build on the most granular data
Research, develop and deploy your strategy on level 3 order book data, with queue tracking, timestamped at the nanosecond level. Directly impute your orders into the order book using our strategy testing engine for the most realistic simulation.
Level 3 Data
Build on the most granular data
Research, develop and deploy your strategy on level 3 order book data, with queue tracking, timestamped at the nanosecond level. Directly impute your orders into the order book using our strategy testing engine for the most realistic simulation.
Team
Daniel Gold
CEO
Master’s graduate with a degree in CAM from University of Chicago, with a foundation in economics and mathematics from Mount Allison University. As an M&A researcher at Constellation Software, Daniel sourced potential acquisitions, engaging CEOs, VC, PE and decision makers. Daniel's primary responsibilities are customer acquisition, product management and statistical research.
Daniel Gold
CEO
Master’s graduate with a degree in CAM from University of Chicago, with a foundation in economics and mathematics from Mount Allison University. As an M&A researcher at Constellation Software, Daniel sourced potential acquisitions, engaging CEOs, VC, PE and decision makers. Daniel's primary responsibilities are customer acquisition, product management and statistical research.
Eran Cohen
Head Dev
Graduated Summa Cum Laude from the Technion with a BSc in Computer Science. Eran is a Software Engineer with expertise in developing simulations, computer graphics frameworks, and high-performance distributed database systems, gained through his work in the Israeli defense industry at Rafael and later at Microsoft.
Eran Cohen
Head Dev
Graduated Summa Cum Laude from the Technion with a BSc in Computer Science. Eran is a Software Engineer with expertise in developing simulations, computer graphics frameworks, and high-performance distributed database systems, gained through his work in the Israeli defense industry at Rafael and later at Microsoft.
Andrew Dennehy
AI
Third year PhD student in Computational and Applied Mathematics (CAM) at the University of Chicago, holding an Honors degree in applied mathematics from UC San Diego. Andrew's expertise lies in machine learning and statistical methods, honed through his extensive professional experience as an ML Engineer at Leidos Inc. His primary role involves leading the development of innovative experimentation frameworks and generative AI models.
Andrew Dennehy
AI
Third year PhD student in Computational and Applied Mathematics (CAM) at the University of Chicago, holding an Honors degree in applied mathematics from UC San Diego. Andrew's expertise lies in machine learning and statistical methods, honed through his extensive professional experience as an ML Engineer at Leidos Inc. His primary role involves leading the development of innovative experimentation frameworks and generative AI models.