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Research Article Open access CC BY 4.0

Testing for the Mean Reversion of Chinese Coal Stock Prices

Gaolu Zou

Advances in Research · pp. 1–10 · Published 30 May 2017

10.9734/AIR/2017/33557

Abstract

Aims: The main purpose of this paper is to test if prices of coal firm stocks in the Chinese A-Share market fluctuate around a long-term trend. Study Design: Existence of a unit root implies that a macroeconomic variable is non stationary and a shock to the market may have imposed a permeant effect on the long-run trend. The variable will not be mean-reverting. To improve the test robustness, conventional unit root tests must be conducted in line with structural break tests. A comparison of the unit roots of stock prices of two coal producing and processing firms in China’s Shanxi Province may lead us to conclude whether the market is trend-reverting. Place and Duration of Study: The study used stock prices of two coal-related firms that come from Shanxi Province, China. The Shanxi Coking Co., Ltd registers in Lingfeng. The Shanxi Xishan Coal and Electricity Power Co., Ltd registers in Taiyuan. Data was the monthly prices. The data period was from August 1996 to July 2014 for the Shanxi Coking, and from July 2000 to October 2015 for the Shanxi Xishan Coal and Electricity Power. Methodology: The paper conducted a unit root test applying regular ADF and PP techniques. Also, it carried out a structural break test using the Perron test and the Zivot-Andrews test (Model C). Results: Tests suggest that prices of two coal stocks are stationary series and these two series contain a shift between 2007 and 2008. The coal stock market may be weak-form efficient. Conclusion: Dramatic coal price fluctuations in China have not produced an enduring effect on prices of the coal stocks examined in the study. The coal-electricity price linkage could account for the trend reversion of coal firm stock prices.  Investors could profit to some extent from trading on coal equities. However, the paper suggests more and panel unit root tests for coal stock prices.

A-Share market break date coal firm long memory permanent effect stock price

References (40)

  1. 1 Co-Integration and Error Correction: Representation, Estimation, and Testing [DOI]
  2. 2 Distribution of the Estimators for Autoregressive Time Series with a Unit Root [DOI]
  3. 3 Testing for a unit root in time series regression [DOI]
  4. 4 A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix [DOI]
  5. 5 EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* [DOI]
  6. 6 Distribution of the Estimators for Autoregressive Time Series With a Unit Root [DOI]
  7. 7 The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis [DOI]
  8. 8 Spurious regressions in econometrics [DOI]
  9. 9 Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis [DOI]
  10. 10 Efficient Tests for an Autoregressive Unit Root [DOI]
  11. 11 LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power [DOI]
  12. 12 AN INTRODUCTION TO LONG‐MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING [DOI]
  13. 13 A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the ‘business cycle’ [DOI]
  14. 14 Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis [DOI]
  15. 15 Efficient Capital Markets: II [DOI]
  16. 16 Testing for a Unit Root in a Time Series With a Changing Mean [DOI]
  17. 17 Long memory and persistence in aggregate output [DOI]
  18. 18 Unit Root Tests in ARMA Models with Data-Dependent Methods for the Selection of the Truncation Lag [DOI]
  19. 19 On Unit-Root Tests When the Alternative Is a Trend-Break Stationary Process [DOI]
  20. 20 The dynamics of crude oil price differentials [DOI]
  21. 21 Long memory in energy futures prices [DOI]
  22. 22 Is South Korea's stock market efficient? [DOI]
  23. 23 Market-driven coal prices and state-administered electricity prices in China [DOI]
  24. 24 Re-examining the Turkish stock market efficiency: Evidence from nonlinear unit root tests [DOI]
  25. 25 Share market efficiency: tests using daily data for Australia and New Zealand [DOI]
  26. 26 What is behind the increase in oil prices? Analyzing oil consumption and supply relationship with oil price [DOI]
  27. 27 Testing for Unit Roots in Seasonal Time Series [DOI]
  28. 28 Fractional integration and mean reversion in stock prices [DOI]
  29. 29 Is South Korea's stock market efficient? Evidence from a nonlinear unit root test [DOI]
  30. 30 Efficiency tests of the UK financial futures markets and the impact of electronic trading systems [DOI]
  31. 31 Impact analysis of China's coal-electricity price linkage mechanism: Results from a game model [DOI]
  32. 32 Some Practical Applications of the Efficient-Market Concept [DOI]
  33. 33 Price Discovery from the Chinese A-Share Market: Trend Break Tests Using the Perron Mixed Model C [DOI]
  34. 34 A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix [DOI]
  35. 35 Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?
  36. 36 Recursive and Sequential Tests of the Unit Root and Trend Break Hypothesis: Theory and International Evidence [DOI]
  37. 37 Permanent and Transitory Components in Macroeconomic Fluctuations [DOI]
  38. 38 Trends and Random Walks in Macroeconomic Time Series: Further Evidence From a New Approach
  39. 39 USE_OF_ROCKDUST_FOR_ENHANCING_DURABILITY_OF_CONCRETE
  40. 40 Nonrenewable Resource Prices: Deterministic or Stochastic Trends? [DOI]

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