Independent research from the International Council for Derivatives Trading. Our papers address the risks, practices, and innovations shaping global derivatives markets
Date: October 2025
Abstract:
Volatility has become the defining variable in modern derivatives markets. It shapes option valuations, influences portfolio performance, and acts as a transmission channel for systemic stress. Yet despite its central role, volatility risk management remains fragmented and inconsistent across institutions. Traders rely heavily on proprietary models, regulators emphasize capital adequacy rather than risk-specific practices, and many participants underestimate the nonlinear dynamics of volatility shocks.
This paper presents an independent framework for managing volatility risk, developed by the International Council for Derivatives Trading. It identifies the major sources of exposure—including level shifts, volatility of volatility, skew, term structure, cross-market correlation, and liquidity spirals—and explains why Greek-based measures such as vega, volga, and vanna are necessary but insufficient. The framework proposes four guiding principles for effective management: transparency in measurement, scenario-based stress testing, dynamic hedging, and independent governance.
Case studies drawn from episodes such as the 1987 market crash, the collapse of Long-Term Capital Management in 1998, the global financial crisis of 2008, the February 2018 “Volmageddon” shock, and the COVID-19 pandemic illustrate how volatility risk has historically destabilized markets. Applications are explored across different market participants, from dealers and hedge funds to institutional investors and retail traders.
The paper concludes that independent standards for volatility risk are urgently needed. By adopting transparent and scenario-driven practices, the industry can improve resilience, enhance governance, and reduce the likelihood that the next volatility shock will trigger unnecessary systemic damage.
Date: September 2025
Abstract:
Liquidity spirals occur when rising volatility, margin requirements, and deleveraging interact in self-reinforcing cycles. In derivatives markets, these dynamics are particularly acute because leverage is high, collateral is procyclical, and liquidity provision depends on dealers whose capacity retreats during stress. What begins as a localized shock can quickly evolve into a systemic crisis as forced sales depress prices, liquidity evaporates, and volatility accelerates.
This paper provides an independent perspective on liquidity spirals, tracing their mechanics and illustrating them through case studies including the 1987 stock market crash, the collapse of Long-Term Capital Management in 1998, the global financial crisis of 2008, the pandemic turmoil of March 2020, and the concentrated failure of Archegos in 2021. Each episode highlights how margining, leverage, and liquidity withdrawal combined to amplify shocks across asset classes.
The analysis demonstrates the shortcomings of traditional risk measures, which ignore liquidity dynamics, and proposes a framework built on four guiding principles: transparency in reporting, scenario-based testing that incorporates liquidity overlays, dynamic risk management that evolves with conditions, and independent governance to enforce discipline. Applications are discussed for market makers, hedge funds, institutional investors, and retail participants, each of whom experiences liquidity spirals differently.
The paper concludes that independent standards are urgently needed to complement regulatory capital rules and firm-level models. By embedding consistent benchmarks for liquidity-adjusted risk measurement and disclosure, the industry can reduce the likelihood that future volatility shocks escalate into systemic crises. The International Council for Derivatives Trading is positioned to advance this agenda by publishing research, setting standards, and integrating these principles into professional education.
Date: November 2025
Abstract:
Artificial intelligence is rapidly transforming derivatives markets, with applications that span volatility forecasting, market making, execution, strategy development, and risk management. By processing vast datasets and identifying complex patterns, AI offers the promise of improved accuracy, greater efficiency, and more adaptive trading strategies. These benefits explain why AI is becoming a structural feature of options and futures markets rather than a passing trend.
At the same time, AI introduces significant risks. The opacity of many models complicates oversight and accountability. Overfitting to historical data makes them fragile in the face of regime shifts and crises. The convergence of strategies across firms raises the danger of herding and synchronized responses to shocks. Data dependency and bias can embed distortions into decision-making, while the speed of automated execution increases the likelihood that market shocks will escalate before human intervention can occur.
This paper provides an independent framework for evaluating AI adoption in derivatives trading. It reviews the main applications and opportunities, analyzes the risks and limitations, and sets out principles for responsible integration. These include transparency in model reporting, scenario-based testing for robustness, dynamic monitoring of performance, independent governance structures, and ethical responsibility for systemic effects.
The conclusion is that AI will reshape derivatives markets, affecting volatility dynamics, liquidity provision, market structure, and the role of human professionals. Whether it becomes a stabilizing foundation or a new source of fragility depends on the standards that guide its adoption. Independent benchmarks are essential to ensure that AI strengthens rather than undermines the resilience of global derivatives markets.
