The next data layer for markets.

The next data layer for markets.

AI generated synthetic capital markets: the new foundation for quantitative analysis

AI generated synthetic capital markets: the new foundation for quantitative analysis


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Synthera: A New Era of Quantitative Market Analysis

Synthera: A New Era of Quantitative Market Analysis

At Synthera, we build proprietary generative AI models trained on historical market data (yield curves, FX, commodities). Our models learn the full distribution and structure of market behavior directly from the data, using millions of parameters to capture non-linear correlations, cross-curve dynamics, regime changes, and rare but high-impact events, delivering realistic unseen market scenarios and insights that give investors an edge in portfolio, trading and risk analysis.

At Synthera, we build proprietary generative AI models trained on historical market data (yield curves, FX, commodities). Our models learn the full distribution and structure of market behavior directly from the data, using millions of parameters to capture non-linear correlations, cross-curve dynamics, regime changes, and rare but high-impact events, delivering realistic unseen market scenarios and insights that give investors an edge in portfolio, trading and risk analysis.

Reduce Market Risk and Improve Returns

Reduce Market Risk and Improve Returns

Reduce Market Risk and Improve Returns

AI Generated Market Simulations

AI Generated Market Simulations

Backtest Strategies on Unlimited, Unseen Market Scenarios

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Conduct Flexible Stress Tests Tailored to Your Market View

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Reduce Hedging Tracking Error on Fixed Income Portfolios

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Advanced Portfolio Analytics

Advanced Portfolio Analytics

Capture Regime Dependent and Non-Linear Correlations Between Assets

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Improve the Accuracy of Value at Risk and Volatility Forecasts

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Uncover Complex Cross-Curve Dynamics for Improved Macro Positioning

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A Fundamental Shift from Parametric to AI Driven Quantitative Analysis

A Fundamental Shift from Parametric to AI Driven Quantitative Analysis

Why Synthera?

Why Synthera?

Value-at-Risk

Value-at-Risk

Volatility and Drawdown

Volatility and Drawdown

Stress Tests

Stress Tests

Price Simulations

Price Simulations

Improve the Accuracy and Quality of existing models

Improve the Accuracy and Quality of existing models

Unlock New Modeling Capabilities

Unlock New Modeling Capabilities

Single model to simulate joint dynamics between yield curves

Single model to simulate joint dynamics between yield curves

Dynamic, regime dependent factor models

Dynamic, regime dependent factor models

Unlimited pool of unseen scenarios for testing strategies

Unlimited pool of unseen scenarios for testing strategies

Data driven, non-parallel yield curve shifts

Data driven, non-parallel yield curve shifts

Synthetic histories for scarce markets

Synthetic histories for scarce markets

Meet the Team

Meet the Team

Lukas Schreiner, Co-Founder and CTO

  • 5+ years as a quantitative engineer, focused on AI for quantitative finance

  • 3 masters degrees in Artificial Intelligence, Quantitative Finance and International Management

  • 5+ years as a quantitative engineer, focused on AI for quantitative finance

  • 3 masters degrees in Artificial Intelligence, Quantitative Finance and International Management

Mariana Barona, Co-Founder and CEO

  • Previously at Goldman Sachs Asset Management

  • First Class Honours graduate from the University of Cambridge

  • Previously at Goldman Sachs Asset Management

  • First Class Honours graduate from the University of Cambridge

Thomas French, Founding Engineer

Thomas French, Founding Engineer

  • PhD in Artifical Intelligence from the University of Edinburgh

  • 10+ years experience scaling synthetic data/AI startups

  • PhD in Artifical Intelligence from the University of Edinburgh

  • 10+ years experience scaling synthetic data/AI startups

Yucheng Gong, Machine Learning Researcher

  • PhD in Applied Machine Learning from Imperial College London, with a focus on time-series simulation and forecasting

  • MS in Advanced Computational Methods from Imperial College London, ranked 2nd in his cohort

Mathias Kling, Strategy and Operations

Mathias Kling, Strategy and Operations

  • 3+ years at JP. Morgan Wealth Management, multi-asset

  • 2+ years in startup strategy and operations

  • NYU BA in Economics

Isha Singla, Quantitative Researcher

  • BE in Computer Science from Birla Institute of Technology and Science

  • 4+ years at JP. Morgan as a fixed income quantitative researcher

Our Scientific Advisor

Our Scientific Advisor

Professor Rama Cont, Scientific Advisor

Professor Rama Cont, Scientific Advisor

  • Professor of Mathematics at the University of Oxford and head of the Oxford Mathematical & Computational Finance group.

  • Globally renowned for pioneering contributions to financial mathematical modeling and quantitative risk management.

  • His innovative research on stochastic analysis, market liquidity, systemic risk and machine learning has been widely published in top-tier journals.

  • Honored with numerous awards for his academic excellence and has acted as a consultant to major financial institutions and regulatory bodies worldwide.

  • Professor of Mathematics at the University of Oxford and head of the Oxford Mathematical & Computational Finance group.

  • Globally renowned for pioneering contributions to financial mathematical modeling and quantitative risk management.

  • His innovative research on stochastic analysis, market liquidity, systemic risk and machine learning has been widely published in top-tier journals.

  • Honored with numerous awards for his academic excellence and has acted as a consultant to major financial institutions and regulatory bodies worldwide.

  • Professor of Mathematics at the University of Oxford and head of the Oxford Mathematical & Computational Finance group.

  • Globally renowned for pioneering contributions to financial mathematical modeling and quantitative risk management.

  • His innovative research on stochastic analysis, market liquidity, systemic risk and machine learning has been widely published in top-tier journals.

  • Honored with numerous awards for his academic excellence and has acted as a consultant to major financial institutions and regulatory bodies worldwide.