V-Lab’s climate risk indicators help users assess the financial implications of climate risks. Investors use the tools to align portfolios with climate goals, price climate risk, and identify opportunities in sustainable investments. Policymakers and regulators apply these indicators for stress testing, disclosure, and scenario planning. The platform supports ESG integration by offering transparent, model-driven climate metrics. Researchers leverage the tools to examine the materiality of climate risk and to inform climate-finance theory. V-Lab updates these metrics regularly as data evolves.

V-Lab’s common volatility risk measures identify aggregate risk factors that drive co-movement across financial markets. These tools help users understand systemic exposures to global shocks and assess the transmission of volatility across asset classes. Investors rely on these models to evaluate diversification effectiveness and design hedging strategies. Regulators use them to monitor market-wide stress and cross-sector contagion. The models decompose volatility into common and idiosyncratic components, providing insights into concentration risk and latent fragility.

By measuring time-varying correlations between asset returns, V-Lab enables users to understand how relationships among assets evolve—especially during periods of market stress. These models support dynamic portfolio construction, stress testing, and scenario analysis. Users can monitor changing correlations across regions, sectors, and asset classes, and better anticipate contagion effects and breakdowns in diversification. Correlation estimates are critical for assessing the stability of hedging strategies and understanding clustering behavior in financial markets. V-Lab’s tools offer both granular and aggregate correlation views, equipping investors, regulators, and academics with insights into co-movement and interdependence in the financial system.

Access real-time analytics, explore our research, or reach out to collaborate with V-Lab.

V-Lab’s fixed income forecasting models provide estimates of interest rates and yield curves. These forecasts are used by investors to manage duration risk, evaluate fixed income strategies, and assess bond valuations under alternative macroeconomic conditions. Policymakers rely on the models to monitor financial conditions and anticipate policy transmission effects. The tools support yield curve construction, forward rate analysis, and inflation risk evaluation. Researchers use the forecasts to test term structure models and study interest rate dynamics across regimes. V-Lab’s fixed income suite bridges academic rigor and practical application for bond market analysis.

V-Lab collaborates with leading institutions, researchers, and practitioners around the world to advance the understanding of financial market dynamics and risks. Our global partnerships enable us to leverage diverse expertise, data sources, and perspectives to enhance the quality and relevance of our research. By working with a network of collaborators, we aim to foster innovation, knowledge sharing, and best practices in financial risk management. Notably, our partnership with the Volatility Institute at NYU Shanghai focuses on research pertinent to Chinese financial markets, fostering international cooperation and knowledge exchange.

Each of these tools is publicly available and continuously updated, reflecting our mission to democratize access to high-quality financial risk analytics. Whether you're an academic exploring new models, a policymaker monitoring systemic exposures, or an investor managing risk, V-Lab provides transparent and actionable data to inform your work.

Our research spans foundational areas in financial econometrics as well as new domains driven by evolving market conditions and policy concerns. Key initiatives include:

V-Lab’s market liquidity measures help users assess the depth, breadth, and resilience of financial markets. These indicators capture how easily and cost-effectively assets can be traded, and how those conditions change in times of stress. Market participants use the tools to monitor bid-ask spreads, trading volumes, and price impact, while regulators and central banks track liquidity as a macroprudential signal. V-Lab’s models are especially valuable during dislocations, when liquidity evaporates and contributes to volatility spikes. These tools support early warning systems, execution strategy design, and policy evaluation.

V-Lab’s long-run Value at Risk (VaR) estimates provide a forward-looking measure of downside risk over extended investment horizons. Unlike short-term VaR, long-run VaR accounts for the persistence of volatility and tail risk accumulation over time. These estimates are particularly valuable for institutional investors, pension funds, and endowments managing long-term liabilities. long-run VaR helps users understand how extreme events may affect portfolios over multi-year periods, supporting better capital planning and stress resilience. It also offers a framework for evaluating regime shifts and structural breaks in volatility.

The Volatility Laboratory is led by a team of dedicated researchers, data scientists, and technologists who are committed to advancing the understanding of financial market dynamics and risks. Our team members bring diverse expertise in financial econometrics, data analytics, and software development, enabling us to develop cutting-edge research and tools that inform decision-making by academics, market participants, and policymakers.

We also acknowledge the invaluable contributions of past team members and collaborators who have played a significant role in our journey.​

V-Lab’s systemic risk measures help users identify vulnerabilities in the financial system and assess the potential impact of shocks. The SRISK model estimates the expected capital shortfall of financial institutions in a crisis scenario, making it a key tool for regulators and macroprudential policymakers. It captures network effects and financial interconnectedness across sectors and geographies. Investors and researchers use SRISK to study systemic fragility, monitor global financial stability, and evaluate the effectiveness of policy interventions. Its public transparency and empirical rigor have made it widely adopted in academic research, financial journalism, and institutional stress testing frameworks.

About us

V-Lab offers volatility forecasts for a wide range of asset classes, including equities, indices, currencies, and commodities. These forecasts help users identify periods of heightened risk, adjust portfolio exposures, and evaluate volatility-targeting strategies. Market participants rely on these insights for risk management, hedging, and derivatives pricing. Researchers use the data to investigate asset dynamics, volatility persistence, and forecasting model performance. The models are updated in real time and are grounded in robust econometric methods, enabling both short-term tactical decisions and long-term planning. By providing consistent and interpretable volatility signals, V-Lab supports both operational risk management and academic inquiry.

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