Explanation:
For illiquid assets, reported returns are often smoothed because they are not traded frequently, which artificially lowers both measured volatility and correlations with other asset classes (leading to an underestimation of systematic risk). This smoothing introduces positive (not negative) autocorrelation in the return series. To correct for the artificially low correlations and systematic risk (beta), one can use enlarged regressions that include lagged market returns (e.g., the Asness, Krail, and Liew method) and sum the coefficients to get a truer measure of the asset's risk profile.
Ultimate access to all questions.
A
Volatility will be artificially high, giving the appearance of high total risk, which can be corrected by taking into account the resulting positive autocorrelation of returns.
B
Correlations with other asset classes will be artificially high, giving the appearance of high systematic risk, which can be corrected using enlarged regressions with additional lags of the market factors and summing the coefficients across lags.
C
Volatility will be artificially low, giving the appearance of low total risk, which can be corrected by taking into account the resulting negative autocorrelation of returns.
D
Correlations with other asset classes will be artificially low, giving the appearance of low systematic risk, which can be corrected using enlarged regressions with additional lags of the market factors and summing the coefficients across lags.
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