Generalized Impulse Response Analysis Research Articles

Price Discovery, Causality and Forecasting in the Freight Futures Market

This paper investigates the causal relationship between futures and spot prices in the freight futures market. Being a thinly traded market whose underlying asset is a service, sets it apart from other markets investigated so far in the literature. Causality tests, generalised impulse response analysis and forecasting performance evaluation indicate that futures prices tend to discover new information more rapidly than spot prices, which is in line with the empirical evidence from other markets. Sub-period results, corresponding to revisions in the composition of the underlying index, show that the price discovery role of futures prices has strengthened as a result of the more homogeneous composition of the index in the recent years. This also indicates that the restructuring of the underlying index in November 1999, to reflect trade flows which are homogeneous in terms of commodities and cargo sizes, may have a beneficial impact on the market. Finally, the information incorporated into futures prices, when formulated as a VECM, produces more accurate forecasts of the spot prices than the VAR, ARIMA and random-walk models, over several steps ahead.

A Comment on 'The Information Content of Earnings and Prices: A Simultaneous Equations Approach' by W.H. Beaver, M.L. McAnally, and C.H. Stinson (1997)

We comment on a recent paper by Beaver, McAnally and Stinson (1997), drawing attention to the fact that their method ignores some recent developments in time-series econometrics. We apply a bi-variate vector autoregression framework to price and earnings data of listed US companies and the S&P 500 index to capture the dynamics of this system of equations. Although some series are I(1), cointegration does not exist and consequently we are unable to estimate a vector error correction model. However, by applying generalised variance decomposition and generalised impulse response analysis, we conclude that evidence favours a linkage from prices to earnings.

Generalized impulse response analysis in linear multivariate models

Building on Koop, [Koop et al. (1996) Impulse response analysis in nonlinear multivariate models. Journal of Econometrics 74, 119–147] we propose the `generalized' impulse response analysis for unrestricted vector autoregressive (VAR) and cointegrated VAR models. Unlike the traditional impulse response analysis, our approach does not require orthogonalization of shocks and is invariant to the ordering of the variables in the VAR. The approach is also used in the construction of order-invariant forecast error variance decompositions.