The effect of asymmetries on stock index return value-at-risk estimates

It is widely accepted that equity return volatility increases more following negative shocks rather than positive shocks. However, much of value-at-risk (VaR) analysis relies on the assumption that returns are normally distributed (a symmetric distribution). This article considers the effect of asymmetries on the evaluation and accuracy of VaR by comparing estimates based on various models

Cointegration analysis with state space models

Abstract: This paper presents and exemplifies results developed for cointegration analysis with state space models by Bauer and Wagner in a series of papers. Unit root processes, cointegration and polynomial cointegration are defined. Based upon these definitions the major part of the paper discusses how state space models, which are equivalent to VARMA models, can be fruitfully employed for cointegration analysis. By means of detailing the cases most relevant for empirical applications, the I(1), MFI(1) and I(2) cases, a canonical representation is developed and thereafter some available statistical results are briefly mentioned.

Variance Spillover and Skewness in Financial Asset Returns

Bond and stock returns have been observed in the literature to exhibit unconditional skewness and temporal persistence in conditional skewness. We demonstrate that observed persistence in conditional third central moments can be due to the spillover of conditional variance dynamics. The confounding of true skewness and a variance spillover effect is problematic for financial modeling. Using market data, we empirically demonstrate that a simple standardization approach removes the variance-induced skewness persistence. An important implication is that more parsimonious return and asset pricing models result if skewness persistence need not be modeled. Copyright 2006 by the Eastern Finance Association.

An application of the Black–Litterman model with EGARCH-M-derived views for international portfolio management

This paper provides an application of the Black–Litterman methodology to portfolio management in a global setting. The novel feature of this paper relative to the extant literature on Black–Litterman methodology is that we use GARCH-derived views as an input into the Black–Litterman model. The returns on our portfolio surpass those of portfolios that rely on market equilibrium weights or Markowitz-optimal allocations. We thereby illustrate how the Black–Litterman model can be put to work in designing global investment strategies. Copyright Swiss Society for Financial Market Research 2007Black–Litterman, GARCH, Global portfolio management, G11, G15,