Trustia Docs
  • Welcome to Trustia's Documentation
  • Systematic Investing
    • Introduction
    • Guide to launch your strategy
      • Requirements
      • Step 1 - Strategy Configuration
        • Weighting Selection
          • Strategy Selection
          • Minimum and Maximum Allocation Selection
          • Additional Parameters selection
        • Ocurence rebalancement Selection
        • Capital Protection Configuration
          • Enable Capital Protection
          • Floor Percentage Configuration
          • Multiplier configuration
        • Exchange configuration
          • Exchange API Key
          • Invested Amount
        • AI Asset Selector
          • Asset Pool Size
          • Include / Exclude Categories
        • Validate the configuration
      • Step 2 - Assets selection
        • Auto-suggest
        • Add / Select Assets
        • Search Assets
        • Validate Assets selection
      • Step 3 - Backtest & launch
        • Compare your results
        • Global Information
        • Performance
        • Returns metrics
        • Ratios Metrics
        • Volatilities Metrics
        • Value at Risk Metrics
        • Trustia Charts Generator
          • Portfolio Performance
          • Drawdown
          • Weightings
          • Portfolio vs Components
          • Ratios Analysis
          • Efficiency Frontier
          • Historical Volatility
          • Values at Risk
          • Covariance Matrix
          • Correlation Matrix
        • Launch your Strategy
    • Features
      • Innovative Weighting Strategies: A Customized Approach
      • Dynamic Asset Allocation
      • Capital Protection
      • Backtesting
    • Algorithms Models
      • Equal
      • Market Capitalization
      • Maximum Sharpe Ratio
      • Minimum Volatility
      • Efficient Risk
      • Efficient Return
      • Maximum Return / Minimum Volatility
      • Inverse Variance
      • Maximum Diversification
      • Maximum Decorrelation
    • Available Trading Platforms
      • Binance Connect
      • Kucoin Connect
      • Coming Soon DEX / CEX
  • Risk management Framework
    • Capital Protection
    • Risk Measures
      • Average Returns
      • Adjusted Returns
      • Volatility
      • Maximum Drawdown
      • Downside Deviation
      • Ordinary Least Squares Method
    • Values at Risk
      • Historical VaR
      • Variance-Covariance VaR
      • Monte Carlo VaR
    • Ratios
      • Sharpe Ratio
      • Calmar Ratio
      • Treynor Ratio
      • Sortino Ratio
    • Backtesting Framework
      • Features
      • Monte Carlo Simulations
  • Others
    • Release notes
    • Support
      • Known Issues
    • FAQ
  • Connect With Us !
    • Give us your feedback !
    • Twitter
    • Blog
    • LinkedIn
    • Website
Powered by GitBook
On this page

Was this helpful?

  1. Risk management Framework
  2. Values at Risk

Variance-Covariance VaR

Learn more about Variance-Covariance VaR

PreviousHistorical VaRNextMonte Carlo VaR

Last updated 1 year ago

Was this helpful?

The variance-covariance VaR is a method of calculating VaR that is based on the covariance of returns of a portfolio or asset with its average return, as well as an estimate of the volatility of returns. This method assumes that returns follow a normal distribution, which is often the case for many financial assets.

We can calculate the covariance of returns with their average, which measures the linear dependence between returns and their average. We use the VaR formula to estimate the maximum expected loss with a certain level of confidence.

For example, if we want to calculate the 95% VaR of a stock portfolio, we can estimate the average return and volatility of the stocks, as well as their covariance with the average return. We can then use these estimates to calculate the 95% VaR of the portfolio.

The variance-covariance VaR is often used because it is simple to calculate and does not require detailed historical data. However, it may not be suitable for assets that have non-normal return distributions or for periods of market stress where volatility can vary significantly.

More info :

Investopedia
Sign up to our mailing list to receive updates!
Page cover image