SkySparc Value at Risk (VaR)

Gain full transparency and control over data inputs and calculations

Want to calculate your covariance matrix for VaR flexibly and cost-effectively?

SkySparc has developed a Value at Risk (VaR) solution that enables clients to flexibly and cost-effectively estimate the covariance matrix required for tracking VaR for their portfolios of financial instruments. By using SkySparc VaR solution, clients no longer need to purchase costly VaR data externally.

Solution overview

Based on the setup of the treasury management system (TMS), the SkySparc VaR solution automatically fetches market rates from the TMS, and calculates volatilities and correlations using one of two models:

  • Exponentially Weighted Moving Average (EWMA).
  • Simple Moving Average (SMA).

Calculated volatilities and correlations are then imported into the TMS, which produces the VaR figures that risk managers can use for further analysis.

  • Tight integration with the TMS delivers improved performance for extraction and writing back of risk management data.
  • Full transparency and control for risk managers over the data inputs and calculation processes, with the ability to run ad hoc calculations outside the regular schedule.

Configuration

Relevant configurations to allow users to select currencies and yields either manually or automatically will be set up in the TMS.

Execution

The standard way to trigger the execution is via an activity in the TMS ticket-based management system.

We knew SkySparc for solutions that work seamlessly with our treasury management system and for quality support,...SkySparc VaR Solution seemed like a great fit for our new need.

Treasury Risk Manager, Global Corporate

Workflow

Step 1
Read VaR mapping
Step 2
Read FX/IR rates
Step 3
Calculate returns
Step 4
Calculate Covariance matrix (EWMA)
Step 5
Calculate Volatility vector
Step 6
Calculate Correlation matrix
Step 7
Save Volatilities
Step 8
Save Correlations

Case study

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European telecom firm

Streamlined and cost-effective risk calculations

Read case study ›