nep-ets New Economics Papers
on Econometric Time Series
Issue of 2017‒03‒12
two papers chosen by
Yong Yin
SUNY at Buffalo

  1. Detecting Co-Movements in Noncausal Time Series By Cubadda, Gianluca; Hecq, Alain; Telg, Sean
  2. Volatility Spillover and Multivariate Volatility Impulse Response Analysis of GFC News Events By Allen, D.E.; McAleer, M.J.; Powell, R.J.; Singh, A.K.

  1. By: Cubadda, Gianluca; Hecq, Alain; Telg, Sean
    Abstract: This paper introduces the notion of common noncausal features and proposes tools for detecting the presence of co-movements in economic and financial time series subject to phenomena such as asymmetric cycles and speculative bubbles. For purely causal or noncausal vector autoregressive models with more than one lag, the presence of a reduced rank structure allows to identify causal from noncausal systems using the usual Gaussian likelihood framework. This result cannot be extended to mixed causal-noncausal models, and an approximate maximum likelihood estimator assuming non-Gaussian disturbances is needed for this case. We find common bubbles in both commodity prices and price indicators.
    Keywords: mixed causal-noncausal process, common features, vector autoregressive models, commodity prices, common bubbles.
    JEL: C12 C32 E32
    Date: 2017–03–02
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:77254&r=ets
  2. By: Allen, D.E.; McAleer, M.J.; Powell, R.J.; Singh, A.K.
    Abstract: This paper applies two measures to assess spillovers across markets: the Diebold Yilmaz (2012) Spillover Index and the Hafner and Herwartz (2006) analysis of multivariate GARCH models using volatility impulse response analysis. We use two sets of data, daily realized volatility estimates taken from the Oxford Man RV library, running from the beginning of 2000 to October 2016, for the S&P500 and the FTSE, plus ten years of daily returns series for the New York Stock Exchange Index and the FTSE 100 index, from 3 January 2005 to 31 January 2015. Both data sets capture both the Global Financial Crisis (GFC) and the subsequent European Sovereign Debt Crisis (ESDC). The spillover index captures the transmission of volatility to and from markets, plus net spillovers. The key difference between the measures is that the spillover index captures an average of spillovers over a period, whilst volatility impulse responses (VIRF) have to be calibrated to conditional volatility estimated at a particular point in time. The VIRF provide information about the impact of independent shocks on volatility. In the latter analysis, we explore the impact of three different shocks, the onset of the GFC, which we date as 9 August 2007 (GFC1). It took a year for the financial crisis to come to a head, but it did so on 15 September 2008, (GFC2). The third shock is 9 May 2010. Our modelling includes leverage and asymmetric effects undertaken in the context of a multivariate GARCH model, which are then analysed using both BEKK and diagonal BEKK (DBEKK) models. A key result is that the impact of negative shocks is larger, in terms of the effects on variances and covariances, but shorter in duration, in this case a difference between three and six months.
    Keywords: Spillover Index, Volatility Impulse Response Functions (VIRF), BEKK, DBEKK, Asymmetry, GFC, ESDC
    JEL: C22 C32 C58 G32
    Date: 2016–01–01
    URL: http://d.repec.org/n?u=RePEc:ems:eureir:98037&r=ets

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