Value-at-Risk (VaR) is a widely used risk management tool in finance that provides an estimate of the maximum potential loss an investment portfolio or trading position could incur over a specified time horizon at a given confidence level.
The confidence level represents the probability that the actual losses will not exceed the estimated Value-at-Risk. For example, a 95% VaR implies that there is a 5% chance that losses could exceed the estimated value.
Value-at-Risk is a critical tool in the commodity industry that provides a quantitative assessment of potential losses, helping users manage risk, make informed investment decisions, and allocate capital efficiently in a volatile market environment. It plays a crucial role in risk management and regulatory compliance within the industry.
Most appreciated advantages of Value-at-Risk
Quantitative = Objective: VaR provides a quantitative measure of risk, which makes it easy to communicate and compare risk levels across different assets or portfolios. This allows for more objective risk assessment and data-driven decision-making
Risk Aggregation: VaR can be used to aggregate risk across various asset classes and portfolios, providing a holistic view of risk exposure for an entire organization. This is crucial for businesses with diverse risk drivers such as different commodities, logistics, FX, and others
Portfolio Optimization: VaR can be integrated into portfolio optimization techniques, including hedge effectiveness. It aids in constructing portfolios that meet specific risk tolerance levels
Risk Communication: VaR is a valuable tool for communicating risk to both internal stakeholders (senior management, board of directors) and external parties (investors, regulators). It helps stakeholders make informed decisions about risk exposure
Key components of Value-at-Risk
Ability to ingest from a multitude of data sources in various formats, both internal and external.
Handling all data regarding security, quality and normalization.
Support for 4 models:
Parametric Equally Weighted
Parametric EWMA
Monte Carlo EWMA
Historical
On Monte Carlo, support for Options VaR
Support for multiple VaR calculations
Configure each VaR calculation with different parameters for model, lambda, confidence, etc.
Calculate diversification across books and products.
Pre-calculate VaR driver – position, price and CoVaR changes
Automatic generation of VaR portfolios
Calculation of Expected Short-Fall
Support for absolute or relative returns
Drill down across portfolio and to individual positions
Early warning of large price variations
VaR Checker allows recalculation of VaR in Excel
Directly access VaR calculated data using out-the-box API
Why RadarRadar Value-at-Risk?
Integration with Exposure Model: RadarRadar VaR is built on top RR Position & Performance engine, providing perfect integration of exposure modeling, PCAT and valuation engine
Enough with copy/pasting: RR VaR built-in data quality checks and integration with position and PCAT eliminates the needs for error-prone excel pre-treatment of the data
Drill-down, up, and sideways: Integration also means full data navigation capabilities, navigating from VaR numbers not only to sub-portfolios/diversification, but also trade/lot position details and/or return decomposition into futures, basis, differentials, etc.
Built for commodities: RR offer a set of industry-tested VaR models with out-of-box parametrization options to match trading-strategies
What do our clients say?
Substantial margin improvement
Industry’s first automated collaborative data management platform with sophisticated margin management tools.
