Volatility relationship between stock performance and real output

Abstract

This paper investigates the interaction between stock index returns and the real output growth for five countries. This study focuses on the second moment relationship using various forms of the bivariate generalized autoregressive conditional heteroscedastic models (BGARCH). This study shows that interactivity between stock returns and growth rates are robust at the second order. The results imply that high volatility in the stock market is likely to be followed by increased volatility in the output sector and periods of high volatility in real output is likely to be followed by increased volatility in the stock market.

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

“…Additionally, our findings are in line to Binswanger (2001) who finds a significant feedback (i.e causality) between stock market volatility and the business cycle in Canada. On the other hand, the absence of a significant relationship in Japan in nearly all sample periods we consider is consistent with the previous literature (see, Ahn and Lee, 2006;and Binswagner, 2001). One possible explanation for this could be that unlike the economies of the other countries we consider, the Japanese economy has experienced more periods of recession which were also longer in duration compared to the expansionary phases.…”

“…Similar findings for Canada are reported in Biswanger (2001). Moreover, our results for Japan are in line with Ahn and Lee (2006) who find no significant relationship, and…”

“…Our findings regarding bidirectional linear causality in the UK are slightly stronger than the ones in Errunza and Hogan (1998) and Morelli (2002) who report no causality between stock market volatility and macroeconomic factors for the UK. Finally, there are several studies which report similar findings for the US using different data periods and empirical settings (Schwert, 1989;Lee, 1992;Campbell et al, 2001;Ahn and Lee, 2006;Bloom et al, 2009;Rahman, 2009;Fornari and Mele, 2013).…”

Empirical Study of China Stock Market and Economic Growth Based on VAR Model

“…The maximum lag phrase of the model is originally assumed to be 2. Test (2). The concomitance probability tested by the program is 0.009, which agrees with the original hypothesis, that is to say, 2 is adopted for the lag phrase.…”

Predictive content of the stock market for output revisited

“…The possible next steps are to apply nonlinear methods (Henry et al, 2004) and to analyse the second moments (Ahn and Lee, 2006). Table 3.…”