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Answer: Use regressions with additional lags of the market factors and sum the coefficients across lags.
D is correct. Artificially low asset class correlations leading to the appearance of low systematic risk is a bias faced by hedge funds with illiquid holdings that use monthly valuation data. One way to correct for this is to use enlarged regressions with additional lags of the market factors and to sum the coefficients across lags. This approach helps to better capture the underlying risk dynamics and relationships between market factors and the hedge fund's returns, thus providing a more accurate representation of the systematic risk.
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When evaluating the risk associated with hedge funds that invest in illiquid assets using monthly data, one must be aware of certain biases that may arise and skew the perceived risk profile. Specifically, such hedge funds might appear to exhibit minimal systematic risk due to these biases. What is an appropriate technique to mitigate this problem?
A
Account for negative serial correlation of returns by first differencing the data when extrapolating risk to longer time horizons.
B
Account for positive serial correlation of returns by aggregating the data.
C
Use regressions with fewer lags of the market factors and sum the coefficients across lags.
D
Use regressions with additional lags of the market factors and sum the coefficients across lags.
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