Designing stress scenarios for liquidity events
A short guide to building plausible liquidity scenarios and mapping mitigations to cashflow stress outcomes.
Insights — Practical notes on financial risk assessment
The Gentleharborview Insights page shares focused articles, short research notes and guidance aimed at risk teams, finance leads and decision makers. We prioritise practical material: concise explanations of quantitative measures like Value at Risk (VaR), case-based scenario design, liquidity stress testing templates, and governance checklists that can be adopted with modest effort. Each post emphasises assumptions, typical pitfalls, and clear next steps so readers can adapt ideas to their own context. Our objective is to help organisations translate technical analysis into operational decisions: prioritised remediations, control design and capital or hedging strategies that align with measurable risk appetite and business objectives.
Featured insight: Making VaR operational
Value at Risk is widely used to summarise market exposure but it is also commonly misapplied when naive assumptions or poor data bias results. In this note we explain a pragmatic way to operationalise VaR for scenario planning and capital assessment. Start by clearly specifying the time horizon, confidence level and the data window; document any adjustments for liquidity, limit violations and non-linear payoffs. Use back-testing and sensitivity analysis to highlight structural model weaknesses; combine probabilistic numbers with scenario overlays that reflect macro shocks or concentration risk. Present results as ranges and decision triggers rather than single point estimates. Link VaR outputs to contingency actions: pre-agreed hedging thresholds, liquidity buffers and governance escalation. By making assumptions explicit and pairing VaR with qualitative scenarios, boards and management can convert abstract metrics into prioritised mitigations that align with tolerance for loss and capital objectives.
Research & methodologies: bridging models and decisions
Our short research notes focus on usable methods: scenario design workshops that surface plausible stress events, liquidity stress testing templates that map cashflow shocks to contingency actions, simple Monte Carlo examples for portfolio managers, and checklists for independent model validation. Each note describes inputs, typical pitfalls, and a short, executable checklist so teams can test ideas quickly. We emphasise replicability: provide clear documentation of assumptions, data sources and validation steps so results are defensible in internal governance reviews and regulatory conversations. Where a quantitative model is used, we recommend parallel qualitative reviews and governance sign-off to capture behavioural and process risks that numeric outputs may miss. The aim is to make analytical work actionable: models should generate trigger points, remediation priorities and monitoring indicators that connect directly to resource allocation and risk appetite decisions.
Recent posts
Backtesting: what boards should ask
Checklist for board members and CROs to evaluate the rigour of backtests and model assumptions.
Operational resilience: a focused review
Key steps to identify control gaps and turn findings into prioritised remediation plans with owners and timelines.