HACking at Non-Linearity: Evidence from Stocks and Bonds
Author(s)
J. Bianchi, Robert
E. Drew, Michael
E. Clements, Adam
Griffith University Author(s)
Year published
2008
Metadata
Show full item recordAbstract
The implicit assumption of linearity is an important element in empirical finance. This study presents a hypothesis testing approach which examines the linear behaviour of the conditional mean between stock and bond returns. Conventional tests detect spurious non-linearity in the conditional mean caused by heteroskedasticity and/or autocorrelation. This study re-states these tests in a heteroskedasticity and autocorrelation consistent (HAC) framework and we find that stock and bond returns are indeed linear-in-the-mean in both univariate and bivariate settings. This study contends that previous research has detected ...
View more >The implicit assumption of linearity is an important element in empirical finance. This study presents a hypothesis testing approach which examines the linear behaviour of the conditional mean between stock and bond returns. Conventional tests detect spurious non-linearity in the conditional mean caused by heteroskedasticity and/or autocorrelation. This study re-states these tests in a heteroskedasticity and autocorrelation consistent (HAC) framework and we find that stock and bond returns are indeed linear-in-the-mean in both univariate and bivariate settings. This study contends that previous research has detected spurious non-linearity due to size distortions caused by heteroskedasticity and autocorrelation, rather than the presence of a genuine non-linear relationship between stock and bond returns.
View less >
View more >The implicit assumption of linearity is an important element in empirical finance. This study presents a hypothesis testing approach which examines the linear behaviour of the conditional mean between stock and bond returns. Conventional tests detect spurious non-linearity in the conditional mean caused by heteroskedasticity and/or autocorrelation. This study re-states these tests in a heteroskedasticity and autocorrelation consistent (HAC) framework and we find that stock and bond returns are indeed linear-in-the-mean in both univariate and bivariate settings. This study contends that previous research has detected spurious non-linearity due to size distortions caused by heteroskedasticity and autocorrelation, rather than the presence of a genuine non-linear relationship between stock and bond returns.
View less >
Conference Title
16th Annual Conference on Pacific Basin Finance Economics Accounting Management (PBFEAM)