# QUIETRISK

## Description

Using the Mahalanobis distance, this risk model characterizes the degree of unusualness in a cross section of asset returns and partitions the historical data into periods of financial turbulence and quiescence. Turbulent periods are usually marked by large asset movements (volatility) and/or unusual changes in correlations (e.g. when non-correlated assets become correlated) and considered statistical outliers. Conversely, quiescent periods are market by subdued asset movements (lower volatility) and/or lower correlation surprises and are considered statistical inliers.

The risk model is useful for stress testing and constructing robust portfolios.

{% hint style="info" %}
This risk model is also available in the Windham Portfolio Advisor. For a deeper dive into the model, please see <https://wpahelp.windhamlabs.com/expected-risk/quiet-and-turbulent-risk>
{% endhint %}

## Syntax

The following describes the function signature for use in Microsoft Excel's formula bar.

```excel-formula
=QUIETRISK(type, assetReturns, threshold, dataPeriodicity)
```

### Input(s)

| Argument            | Description                                                                                                                                                                                                                                                                                                                                                                                              |
| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **type**            | <p>Required. Enumeration string to specify calculation type:</p><p>   "risk", "sigma", or "stdev"</p><p>   "correlation", "corr", or "rho"</p><p>   "covariance", "covar", or "cov"</p>                                                                                                                                                                                                                  |
| **assetReturns**    | Required. Time series or matrix of asset returns.                                                                                                                                                                                                                                                                                                                                                        |
| **threshold**       | Required. Probability threshold of quiet periods (0.00 - 1.00). This threshold is the converted into the equivalent chi-squared,$$\chi\_{N}^2$$, score. Under a multivariate normal assumption, the cutoff can be interpreted as an approximation of the percentage of the sub-sample of inliers (quiet). This approximation may vary depending on the underlying characteristics of the empirical data. |
| **dataPeriodicity** | <p>Optional. Periodicity of the data, used for annualization. If you do not enter the argument, it defaults to 1.</p><p>e.g. Daily = 255, Monthly = 12, Yearly = 1, Quarterly = 4.</p>                                                                                                                                                                                                                   |

### Output(s)

Depending on the specified output *type*, the function will return the respective vector of risk estimates (annualized standard deviations), correlation matrix, or a covariance matrix.

## Example

![](/files/-ML9nbPdbg6SDVajlh8J)

{% file src="/files/-ML9nw7N3O1nehODTWjB" %}
Example Workbook
{% endfile %}

The following video describes the conceptual application of the methodology.

{% embed url="<https://windhamcapital.wistia.com/medias/ti6fqxaqxf>" %}


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