Given that VaR includes idiosyncratic downside risk at the fund level, this paper examines the cross-sectional relationship between downside risk (VaR) and expected returns in a sample of 1,370 hedge funds that specialize in emerging equity markets. To the best of our knowledge, this paper is the first to investigate the cross-sectional relationship between downside risk and expected return in the context of asset pricing for emerging market hedge funds. Despite many studies specializing in EMHF, to the best of our knowledge, the literature has not yet provided a comprehensive analysis of the cross-sectional relationship between downside risk (measured by VaR) and expected returns in the context.
To the best of our knowledge, this paper is the first on emerging market hedge funds to examine the cross-sectional relationship between downside risk and return in an asset pricing framework while controlling for fund characteristics including fund size and age. Overall, while the results confirm the presence of a downside risk effect on the cross-section of expected EMHF returns, they also suggest that emerging market hedge funds exhibit a different risk/return trade-off compared to their advanced market peers . These restrictions leave us with 1,370 hedge funds in the final sample, including live and defunct funds.
In the case of the parametric VaR estimates, motivated by the comparative analysis in Bali and Gokcan (2004), we use the Cornish and Fisher (1937) extension to the VaR model to account for skewness and fat tails observed in hedge fund returns. , implied by the descriptive statistics in Table 1. In Equation 2, 𝑍(𝛼) is the critical value from the normal distribution for probability (1 − 𝛼), S is the skewness, and K is the excess kurtosis of the return distribution.
Empirical Results
Results of Univariate and Bivariate Sorts .1 Univariate Sorts
The findings for the full sample, however, provide no evidence of a statistically significant return gap between the highest and lowest deciles of downside risk, suggesting that downside risk is not a significant determinant of subsequent returns over the entire sample period. This is in agreement with the finding of Bali et al. 2007) on the insignificant relationship between downside risk and expected returns for a pooled sample of active and inactive hedge funds. This spread is economically significant and suggests that the positive and significant relationship between downside risk and expected returns could be exploited to generate excess returns in the pre-crisis period.
However, the positive relationship between downside risk and expected returns appears to have broken down in the post-crisis period, implied by an insignificant return spread between the high- and low-risk portfolios for this period. Accordingly, one could argue that the negligible downside risk spread observed in the post-crisis period may be due to these funds behaving more in line with their advanced counterparts, resulting in smaller (and negligible) anomaly spreads. Overall, while the results indicate the presence of a positive relationship between downside risk and expected EMHF returns, we see that the positive relationship has disappeared in the post-global crisis period.
To examine the potential interaction between downside risk and other fund-level characteristics and to disentangle one effect from the other, below we present in Tables 4 and 5 the results from bivariate types in which we first rank EMHFs based on age of the fund and then their VaR. Valuations (CF-VaR). This procedure allows us to examine the risk-return relationship after controlling for fund age. The results in Table 4 suggest that the relationship between downside risk and expected EMHF returns is similar across the three age groups, i.e. positive but statistically insignificant, suggesting that fund age is not necessarily a negative determinant of the risk-return relationship.
Sorting funds first by their asset size and then by their measure of downside risk, the findings in Table 6 suggest the presence of a downside risk premium embedded in EMHF returns, particularly for mid- to high-sized pools. While the post-crisis period yields insignificant return spreads in all size groups, consistent with the evidence presented earlier, we observe that mid- to large-cap EMHF portfolios with high downside risk yield significantly higher expected returns compared to those with low downside risk deciles. Interestingly, when looking at the findings in Panel A for the entire sample, we see that there is actually a negative relationship between downside risk and returns within the smallest group of funds, while the relationship is positive for medium and large funds. lt;Approximately insert table 6> here. lt;Approximately insert table 7> here.
Considering the evidence in Bali et al. 2007) that downside risk-return relationships are much stronger in small and young funds, our findings suggest that emerging markets funds exhibit a different risk and return pattern compared to their advanced market counterparts.
Fund level analysis
These are indeed economically significant spreads, suggesting the role of fund size as a determinant of the risk-return ratio in EMHFs. Extending the analysis to CF-VaR-based EMHF portfolios in Table 7, we observe similar findings with the positive risk-return relationship generally holding for emerging market hedge funds, while the relationship is particularly strong for mid- to large-sized funds and especially during the pre-global crisis period. The univariate regressions in Models 1 and 2 provide evidence of significant positive downside risk effect on expected EMHF, consistent for both the parametric and non-parametric VaR estimates.
While the age of the fund has a positive effect, but not statistically significant, while the size has a negative and statistically significant effect on the expected return in the univariate regression analysis (models 3 and 4). We see that the average R2 values in the univariate models are higher for VaR and CF-VaR than those for age and fund size, indicating that downside risk has greater power to extract cross-sectional variation in hedge fund returns. explain the emerging markets. Extending the analysis to a multivariate setting, we see that downside risk remains an important determinant of expected returns, even after controlling for age and size (models 7 and 10), while fund age loses its positive effect after controlling for downside risk.
Similarly, fund size remains a strong determinant of expected returns in multivariate models, suggesting the presence of a size effect in the cross-section of emerging market hedge fund returns. Finally, the significance of downside risk measures as a driver of expected fund returns remains strong during the pre-crisis sub-sample while the post-crisis sub-period lost significance, reported in panels B and C. While the explanatory power of the models is found to be significantly smaller, implied by the low values of R2 especially during the post-crisis period, we see that VaR (CF-VaR) remains a strong driver of EMHF expected returns, consistent with the evidence in Bali et al. . 2007) for advanced market hedge funds.
Conclusion
Overall, while the results confirm the presence of a downward risk effect on the cross-section of expected EMHF returns, they also suggest that emerging market hedge funds exhibit a different risk/return pattern compared to their advanced market counterparts. Given that emerging market hedge funds are largely understudied due to the limited opportunities to employ dynamic trading strategies (Fung and Hsieh. Note: Panels A and B present the average monthly returns of EMHF portfolios sorted by their non-parametric VaR and parametric VaR (ie CF-VaR) estimates, respectively, across the total sample of both live and defunct funds.
The return dispersion is the average return difference between the highest (decile 10) and the lowest (decile 1) VaR portfolios together with the Newey and West (1987) adjusted t-statistics (in brackets) for our pooled sample. Panel A: EMHFs sorted by age Panel B: EMHFs sorted by size Decile Age (in months) Return (%) Decile Ln (Assets) Return. Note: Panels A and B present average monthly returns for EMHF portfolios sorted by age and size (i.e., log assets), respectively.
The difference in average return between decile 10 and decile 1 is also given, along with Newey and West's (1987) adjusted t -statistics (in parentheses) for our pooled sample. Note: Panels A and B present the average monthly returns for active and inactive EMHF portfolios, sorted by their non-parametric VaR estimates for the full period, the pre-crisis period and the post-crisis period, respectively. The return spread is the difference in mean return between the highest (decile 10) and lowest (decile 1) VaR portfolios together with Newey and West's (1987) adjusted t-statistics (in parentheses) for live and inactive funds.
The average return differential between Decile 10 and Decile 1 along with the Newey and West (1987) adjusted t-statistics (in parentheses) for our live funds are also reported. Note: This table presents the average monthly decomposed EMHR return, sorted first by Age and then VaR. The average return differential between Decile 10 and Decile 1 along with the Newey and West (1987) adjusted t-statistics (in parentheses) for our decoupled funds are also reported.
Note: Panels A and B present average monthly returns for existing and defunct EMHF portfolios sorted by age over the entire pre-crisis and post-crisis periods. The average return difference between December 10 and December 1 is also reported along with the Newey and West (1987) adjusted t-statistics (in brackets) for our existing and defunct funds. Cross-sectional regressions of legacy and defunct hedge fund returns by downside risk, firm size, and age.
Note: This table shows the time series averages of the slope coefficients obtained from the monthly Fama and MacBeth (1973) regressions for live (Panel A) & defunct (Panel B) emerging market hedge funds over the entire pre-crisis and post-crisis periods.
