Description
Multiply correlation by volatilities for covariance, then by both scales.
Risk and sensitivity terms depend on return units, horizon and model structure. A covariance contribution or local price approximation describes only part of a portfolio or instrument's risk and does not establish a safe investment.
Multiply correlation by volatilities for covariance, then by both scales.
When to use this tool
Use Asset Correlation Covariance Unit Crosswalk when you need one explicit risk or sensitivity term.
How to use the tool and how it works
- Enter correlation, firstVolatility, secondVolatility, firstScale, secondScale. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read covariance, scaledCovariance. Use the output convention below.
Require correlation in [-1, 1], nonnegative volatilities and positive scales. Multiply correlation by volatilities for covariance, then by both scales.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| correlation | Dimensionless supplied correlation, not estimated from raw observations. | Required. Finite number; minimum -1; maximum 1. |
| firstVolatility | First Volatility | Required. Finite number; minimum 0. |
| secondVolatility | Second Volatility | Required. Finite number; minimum 0. |
| firstScale | First Scale | Required. Finite number; strictly above 0. |
| secondScale | Second Scale | Required. Finite number; strictly above 0. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| covariance | Covariance | Required. Finite number. |
| scaledCovariance | Scaled Covariance | Required. Finite number. |
{
"input": {
"correlation": 0.5,
"firstVolatility": 0.2,
"secondVolatility": 0.3,
"firstScale": 100,
"secondScale": 100
},
"output": {
"covariance": 0.03,
"scaledCovariance": 300
}
}Limitations and assumptions
- Volatilities share a horizon and numeric return convention; covariance has product units. No data correlation or complete positive-semidefinite covariance matrix is estimated.
- Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
- Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.
Alternative or Complementary methods
Use the complete portfolio or instrument model, including covariance consistency, nonlinear effects and scenario analysis. Verify scaling and estimation assumptions before interpreting a partial term as total risk.
References
Similar or alternative tools
- Portfolio Variance One Covariance Term
Multiply both weights by covariance, with factor one for sameAsset and two otherwise.
- Sharpe Risk Free Frequency Consistency Term
Convert annual effective rate through expm1(log1p(rate)/periods); subtract from period return and divide by period volatility, then multiply by sqrt(periods) for annualized Sharpe.