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Monetary environments and stock returns: International evidence based on the quantile regression technique

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  • Chevapatrakul, Thanaset

Abstract

This paper investigates the impact of the local and the US monetary policy environments on stock returns at the different locations on the return distributions. Using data for stock returns and interest rates of 30 countries, the quantile regression technique is employed to estimate the sensitivity of the returns to monetary policy at the different points on the return distributions. The results suggest that higher returns are associated with expansionary monetary policy. Furthermore, some of the stock markets in the sample are found to react to the local, but not the US monetary environments at the lower quantiles while the response at the higher quantiles appears to be sensitive to the US, but not the local monetary conditions. These findings are further supported by the slope equality tests, discussed in Koenker & Bassett (1982), and the analysis of weighted absolute residuals (ANOWAR), proposed by Chen, Ying, Zhang, & Zhao (2008).

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  • Chevapatrakul, Thanaset, 2015. "Monetary environments and stock returns: International evidence based on the quantile regression technique," International Review of Financial Analysis, Elsevier, vol. 38(C), pages 83-108.
    • Handle: RePEc:eee:finana:v:38:y:2015:i:c:p:83-108
    DOI: 10.1016/j.irfa.2015.01.013
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    Cited by:

    1. Chevapatrakul, Thanaset & Xu, Zhongxiang & Yao, Kai, 2019. "The impact of tail risk on stock market returns: The role of market sentiment," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 289-301.
    2. Raza, Syed Ali & Sharif, Arshian & Kumar, Satish & Ahmed, Maiyra, 2023. "Connectedness between monetary policy uncertainty and sectoral stock market returns: Evidence from asymmetric TVP-VAR approach," International Review of Financial Analysis, Elsevier, vol. 90(C).
    3. Al-Nasseri, Alya & Menla Ali, Faek & Tucker, Allan, 2021. "Investor sentiment and the dispersion of stock returns: Evidence based on the social network of investors," International Review of Financial Analysis, Elsevier, vol. 78(C).
    4. Guo, Peng & Zhu, Huiming & You, Wanhai, 2018. "Asymmetric dependence between economic policy uncertainty and stock market returns in G7 and BRIC: A quantile regression approach," Finance Research Letters, Elsevier, vol. 25(C), pages 251-258.
    5. Stephanos Papadamou & Νikolaos A. Kyriazis & Panayiotis G. Tzeremes, 2020. "US non-linear causal effects on global equity indices in Normal times versus unconventional eras," International Economics and Economic Policy, Springer, vol. 17(2), pages 381-407, May.
    6. Mohammad Enamul Hoque & Mohd Azlan Shah Zaidi & M. Kabir Hassan, 2021. "Geopolitical Uncertainties and Malaysian Stock Market Returns: Do Market Conditions Matter?," Mathematics, MDPI, vol. 9(19), pages 1-16, September.

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    More about this item

    Keywords

    Quantile regression; Monetary policy; Stock markets;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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