Contagion Phenomena with Applications in Finance by Serge Darolles, Christian Gourieroux

By Serge Darolles, Christian Gourieroux

Much learn into monetary contagion and systematic hazards has been stimulated by way of the discovering that cross-market correlations (resp. coexceedances) among asset returns elevate considerably in the course of drawback sessions. is that this elevate because of an exogenous surprise universal to all markets (interdependence) or because of particular types of transmission of shocks among markets (contagion)? Darolles and Gourieroux clarify that an try and show contagion and causality in a static framework can be flawed due to identity difficulties; they supply a extra unique definition of the thought of concern to reinforce the answer inside of a dynamic framework. This e-book covers the traditional perform for outlining shocks in SVAR versions, impulse reaction features, identitification matters, static and dynamic versions, resulting in the demanding situations of size of systematic threat and contagion, with interpretations of hedge fund survival and marketplace liquidity risks

  • Features the traditional perform of defining shocks to types that can assist you to outline impulse reaction and dynamic consequences
  • Shows that id of shocks will be solved in a dynamic framework, even inside of a linear perspective
  • Helps you to use the types to portfolio administration, hazard tracking, and the research of monetary stability

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For instance, we get an observationally equivalent model by changing C into CQ and Ft into Q−1 Ft , where Q is any invertible (K, K) matrix. Thus, the latent factors can be identified up to a linear invertible transformation. 11] V (vt ) = IdK . 1] is a vector autoregressive (VAR) model with partial observability. This model admits a state space representation. More precisely, let us introduce the state variable Zt = (Yt , Ft ) . 11], we have: State equation: Zt = ΨZt−1 + wt , where Ψ= C BA 0 A , wt = ut + Bvt vt , V (wt ) = Ω + BB B B IdK .

17] 4 This is the information of the economic agent. Ex-post, it will differ from the information of the econometrician equal to (yt , yt−1 , . ). 36 Contagion Phenomena with Applications in Finance where the root of the moving average (MA) polynomial is (1 − βθ)/θ = 1/θ − β. 9). 9. The invertibility region. This figure displays with a continuous line the couples (θ, β) satisfying the unitary condition: 1/θ − β = 1. f. of ηi,t . Note, however, that: 1) The errors to be shocked are some components of η, since these errors may have an economic interpretation.

G. [GOU 15a] and [GOU 15b]). When these consistent methods are applied to economic and financial series, we often obtain ˆ matrices with eigenvalues whose modulus is estimated Φ larger than 1. How can we explain the presence of non-causal linear features in these series? To understand this stylized fact, it is important to consider an alternative interpretation of a two-sided moving average process. Let us consider the one-dimensional case n = 1. 11] can be written as: +∞ yt = ητ at−τ . 20] τ =−∞ Thus, the path of process (Yt ) is a combination of baseline paths Zτ (t) = at−τ , τ = −∞, .

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