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Fig. 6 | Financial Innovation

Fig. 6

From: Tracking market and non-traditional sources of risks in procyclical and countercyclical hedge fund strategies under extreme scenarios: a nonlinear VAR approach

Fig. 6

Local projection of illiquidity shocks on the beta of the general index, growth and fixed income strategies over the subprime crisis with cv_igamma not instrumented. 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 by the EGARCH (Nelson 1991) method (cv_igamma). The impulse response functions corresponding to the linear LP are built using the Jordà’s (2004, 2005, 2009) algorithm provided by Eren Ocakverdi, consultant at Yapy Kredi. The local projection of a beta strategy is performed over the subprime crisis (2007Q3–2009Q4). We also provide the linear VAR estimated over the whole sample period selected as benchmark. The confidence interval of the LP impulses, computed at the threshold of 95%, is in dotted lines. As explained in the paper, our model comprises six endogenous shocks, placed in the following order to perform the Cholesky factorization (Sims 1980) required to build structural shocks: GDP growth, term spread, credit spread, beta (own shock), i_gamma, and cv_igamma. As usual, these variables are ordered by increasing level of endogeneity. This order relies on the conventional information criteria: Akaike and Schwartz criteri

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