HACking at Non-linearity: Evidence from Stocks and Bonds

Robert J Bianchi (), Adam Clements and Michael E. Drew ()
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Robert J Bianchi: School of Economics and Finance, Queensland University of Technology

No 244, School of Economics and Finance Discussion Papers and Working Papers Series from School of Economics and Finance, Queensland University of Technology

Abstract: 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 may have detected spurious non-linearity due to size distortions caused by heteroskedasticity and autocorrelation, rather than the presence of genuine non-linearity.

Keywords: linearity; nonlinear; heteroskedasticity-robust tests; autocorrelation-robust tests (search for similar items in EconPapers)
JEL-codes: G00 G12 G14 (search for similar items in EconPapers)
Date: 2009-01-27
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