A Comparison of the Statistical Properties of Financial Variables in the USA, UK and Germany over the Business Cycle

Abstract

This paper presents business cycle stylized facts for the US, UK and German economies. We examine whether ¢nancial variables (interest rates, stock market price indices, dividend yields and monetary aggregates) predict economic activity over the business cycle, and we investigate the nature of any non-linearities in these variables. Leading indicator properties are examined using cross-correlations for both the values of the variables and their volatilities. Our results imply that the most reliable leading indicator across the three countries is the interest rate term structure, although other variables also appear to be useful for speci¢c countries. The volatilities of ¢nancial variables may also contain predictive information for production growth as well as production volatility. Non-linearities are uncovered for all ¢nancial series, especially in terms of autoregressive conditional heteroscedasticity e¡ects. Strong evidence of mean non-linearity is also found for many ¢nancial series and this can be associated with business cycle asymmetries in the mean. This is the case for a number of American and British ¢nancial variables, especially interest rates, but the corresponding evidence for Germany is con¢ned largely to the real long-term rate of interest.

Stock market volatility and business cycle: Evidence from linear and nonlinear causality tests

“…Nevertheless, this is still a topic which remains largely unstudied since the literature generally places more weight on measuring, modelling and forecasting volatility rather than exploring the links with its underlying determinants (Diebold and Yilmaz, 2010). On the other hand, there are even fewer studies that consider the opposite direction and employ stock market volatility to predict real economic activity (e.g., Andreou et al, 2000;Fornari and Mele, 2013). However, understanding the dynamics and behaviour of stock market volatility and examining its potential spillover effects on real economic activity and vice versa is a matter of utmost significance for two reasons.…”

The Properties of Cycles in South African Financial Variables and Their Relation to the Business Cycle

“…However, for those series (including yields and spreads) that are not strongly trending only classical cycles are identified. This pragmatic approach corresponds to the approach by Osborn et al (2005) and Andreou et al (2000).…”

“…While it is relatively simple to assess the co-movement between two series using cross-correlations (see for example Andreou et al, 2000), this technique requires stationary time series. However, macroeconomic time series are commonly nonstationary due to the presence of stochastic trends.…”

“…This study, focusing on South African financial time series, follows the variables proposed by Sarantis and Lin (1999) and Andreou et al (2000). (i) Using the inflation rate of the current period to generate ex post real rates.…”

“…In the literature, the correlation statistic is used to gauge pro-or counter-cyclicality. For example, Andreou et al (2000) use cross-correlations to establish the cyclicality of financial variables relative to industrial production in the United Kingdom. As previously demonstrated, the concordance statistic offers several improvements on the correlation statistic, while it can be interpreted in a similar fashion.…”