AI Generated Financial Market Simulations and Analysis
Uncover what traditional models miss: the deeper market structure, tail risks, and non-linear correlations in financial markets.
AI Generated Financial Market Simulations and Analysis
AI Generated Financial Market Simulations and Analysis
Uncover what traditional models miss: the deeper market structure, tail risks, and non-linear correlations in financial markets.
Uncover what traditional models miss: the deeper market structure, tail risks, and non-linear correlations in financial markets.
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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Backtest Strategies on Unlimited, Unseen Market Scenarios
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Backtest Strategies on Unlimited, Unseen Market Scenarios
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Conduct Flexible Stress Tests Tailored to Your Market View
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Conduct Flexible Stress Tests Tailored to Your Market View
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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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Reduce Hedging Tracking Error on Fixed Income Portfolios
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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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Capture Regime Dependent and Non-Linear Correlations Between Assets
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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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Improve the Accuracy of Value at Risk and Volatility Forecasts
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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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Uncover Complex Cross-Curve Dynamics for Improved Macro Positioning
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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
Mariana Barona, Co-Founder and CEO
Multiple years at Goldman Sachs Asset Management
First class graduate from the University of Cambridge
Multiple years at Goldman Sachs Asset Management
First class graduate from the University of Cambridge
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
Thomas French, Founding Engineer
PhD in Artifical Intelligence from the University of Edinburgh
10+ years experience scaling synthetic data/AI startups
PhD in Artificial Intelligence from the University of Edinburgh
10+ years experience scaling synthetic data startups
PhD in Artifical Intelligence from the University of Edinburgh
10+ years experience scaling synthetic data/AI startups
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.