Fig. 12

Response of hedge fund beta to a moderate and strong negative and positive illiquidity shocks in low and high regimes for the general index and the fixed income and growth strategies. Notes: Liquidity shocks are measured by the main series of Pástor and Stambaugh (2003)—i.e., the innovation in aggregate liquidity (i_gamma)—and its conditional variance as computed with the EGARCH (Nelson 1991) method (cv_igamma). The plots correspond to the impulse response functions of strategies’ betas to liquidity shocks. They are built with the Balke (2000) nonlinear impulse response function algorithm using the generalized impulse response function to identify the structural shocks (Koop et al. 1996; Pesaran and Shin 1997, 1998). For each strategy, we have two kinds of shocks: positive and negative shocks of liquidity, and moderate and strong shocks of liquidity, corresponding to one and two standard deviations of the value of the shocks, respectively, for a total of four impulse response functions by regime for each strategy. Moreover, Balke (2000) considers two categories of regimes separated by an optimal threshold value: a low and a high regime. The significance of the threshold values is evaluated with Wald tests. We use real GDP growth to compute the threshold value separating the regimes