Virtual Volatility for Drift Forecast Uncertainty and Portfolio Analysis

Summary

The document introduces virtual volatility as a measure of uncertainty in forecasts of the drift component of a random walk. It also presents the measure as a way to examine the stochastic behavior of a portfolio, with a reported example in which it helped identify a mean-reversion effect. The proposed uses therefore span both forecast uncertainty and portfolio analysis.

The text briefly raises a possible role for virtual volatility in investor asset allocation. It does not provide the formula, data, portfolio construction details, or evidence needed to assess how the measure is estimated or how robust the example is. No comparison with other uncertainty measures or allocation methods is described, so the practical value and generality of the proposal cannot be judged from this document alone.

Key ideas

• Virtual volatility is proposed as a measure of uncertainty in forecasts of random-walk drift.
• The measure is also presented as a tool for examining portfolio stochastic behavior.
• An example reportedly uses the measure to identify a mean-reversion effect in a portfolio.
• The document suggests that virtual volatility may inform asset allocation, but gives no implementation details.

Tags

# Virtual volatility


# Virtual volatility









We introduce the concept of virtual volatility. This simple but new measure shows how to quantify the uncertainty in the forecast of the drift component of a random walk. The virtual volatility also is a useful tool in understanding the stochastic process for a given portfolio. In particular, and as an example, we were able to identify mean reversion effect in our portfolio. Finally, we briefly discuss the potential practical effect of the virtual volatility on an investor asset allocation strategy.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.