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Answer: 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.
The correct answer is D. Illiquid assets, such as convertible bonds, are traded infrequently. Risk measures based on monthly returns can give a misleading picture of risk because the closing net asset value (NAV) does not reflect recent transaction prices. This creates two types of biases: First, correlations with other asset classes will be artificially lowered, giving the appearance of low systematic risk. This can be corrected using enlarged regressions with additional lags of the market factors and summing the coefficients across lags. Second, volatility will be artificially lowered, giving the appearance of low total risk. Such illiquidity, however, will show up in positive serial autocorrelation in returns. Biases in volatility measures can be corrected by taking this autocorrelation into account when extrapolating risk to longer horizons. Option A is incorrect because volatility will be artificially lowered, making it appear that total risk is low. Option B is incorrect because correlations with other asset classes will be artificially lowered. Option C is incorrect because the illiquidity will exhibit itself through positive serial autocorrelation in returns.
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As an investor deeply analyzing a hedge fund that focuses on illiquid assets, you have obtained monthly return data from this fund. Given the nature of illiquid assets, you are concerned that the return data may be distorted, potentially misrepresenting the true risk profile of the fund. What would be an appropriate measure or evaluation method for the investor to use in order to obtain an accurate assessment of the fund's risk characteristics?
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.