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Stock price fluctuation and the business cycle in the BRICS countries: A nonparametric quantiles causality approach

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  • Shi, Guangping
  • Liu, Xiaoxing

Abstract

Using the newly developed nonparametric quantile causality method, we investigate the causal relationships in the mean and variance between stock price fluctuation and the business cycle for the BRICS countries. The empirical results reveal that the causality in the mean between stock price fluctuation and the business cycle is insignificant across all distributions, apart from Russia; however, the bidirectional causality in the variance covers virtually all quantiles, with some exceptions in the tails for all BRICS countries. Therefore, the investors and economic policy makers could consider the variance of stock price fluctuation and the business cycle and pay special attention to the tail quantiles to improve the efficiency of investment and policy.

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  • Shi, Guangping & Liu, Xiaoxing, 2020. "Stock price fluctuation and the business cycle in the BRICS countries: A nonparametric quantiles causality approach," Finance Research Letters, Elsevier, vol. 33(C).
    • Handle: RePEc:eee:finlet:v:33:y:2020:i:c:s1544612319300753
    DOI: 10.1016/j.frl.2019.06.021
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    Cited by:

    1. Ma, Xinxin & Zong, Xiangyu & Chen, Ximing, 2022. "Economic fitness and economy growth potentiality: Evidence from BRICS and OECD countries," Finance Research Letters, Elsevier, vol. 50(C).

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    More about this item

    Keywords

    Stock price fluctuations; The business cycle; Quantile causality; Volatility;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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