Analysis of market efficiency for the Shanghai stock market over time

Wang, Yudong; Liu, Li; Gu, Rongbao; Cao, Jianjun; Wang, Haiyan

doi:10.1016/j.physa.2009.12.039

Cited by 88 publications

(36 citation statements)

References 19 publications

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“…Once bidders submit abnormally low prices, BCRs are increased with time. Thus, the measure of market efficiency in the project-based competition should be modified as Equation (2) Market efficiency has been considered as a subtle concept that is hard to be tested by empirical studies [61]. The proposed measure of the degree of market efficiency is Equation (2), which can function as a comparative basis for simulation-based scenarios analysis and policy evaluation.…”

Section: Measuring the Market Efficiency And Policy Effectivenessmentioning

confidence: 99%

Project-Based Market Competition and Policy Implications for Sustainable Developments in Building and Construction Sectors

Yan

2015

Sustainability

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Building and construction sectors are significant contributors to the global economy, but their energy consumption necessitates greater commitment to sustainable developments. There is therefore a growing demand for green innovation in the form of cleaner production and policies to meet the modern requirements of sustainability. However, the nature in which public work is undertaken is in an environment of project-based market competition, whereby contractors routinely bid for contracts under specific project awarding systems, and variations are accompanied with the unique scope of individual projects before the final goods or services are delivered. A comprehensive understanding of the characteristics and contractors' behavior in systems could help to identify the leverage points of policies. This paper proposes a system dynamics model, with quantitative analysis and simulations, to demonstrate the problems of a system with different project awarding systems and ineffective market performance. The framework of market efficiency and performance measures has been proposed to evaluate the project-based competition mechanism. Managerial policy implications for market efficiency and sustainable developments can thus be systematically discussed and compared through iterative computer simulations and scenario analysis.

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Section: Measuring the Market Efficiency And Policy Effectivenessmentioning

confidence: 99%

Project-Based Market Competition and Policy Implications for Sustainable Developments in Building and Construction Sectors

Yan

2015

Sustainability

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“…Depending on whether H is smaller than, equal to, or larger than 1/2, a system is said to have anti-persistent, short-term, or persistent long-range correlations [36,40]. Deviations of H from 1/2 is strong evidence of inconsistency with the EMH [41][42][43][44][45][46][47][48][49]. Another approach is to use the Lempel-Ziv complexity (LZ) [38,39,50,51].…”

Section: Introductionmentioning

confidence: 99%

Characterizing Complexity Changes in Chinese Stock Markets by Permutation Entropy

Hou

Liu

Gao

et al. 2017

Entropy

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Financial time series analyses have played an important role in developing some of the fundamental economic theories. However, many of the published analyses of financial time series focus on long-term average behavior of a market, and thus shed little light on the temporal evolution of a market, which from time to time may be interrupted by stock crashes and financial crises. Consequently, in terms of complexity science, it is still unknown whether the market complexity during a stock crash decreases or increases. To answer this question, we have examined the temporal variation of permutation entropy (PE) in Chinese stock markets by computing PE from high-frequency composite indies of two stock markets: the Shanghai Stock Exchange (SSE) and the Shenzhen Stock Exchange (SZSE). We have found that PE decreased significantly in two significant time windows, each encompassing a rapid market rise and then a few gigantic stock crashes. One window started in the middle of 2006, long before the 2008 global financial crisis, and continued up to early 2011. The other window was more recent, started in the middle of 2014, and ended in the middle of 2016. Since both windows were at least one year long, and proceeded stock crashes by at least half a year, the decrease in PE can be invaluable warning signs for regulators and investors alike.

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“…Multifractality has been a ''stylized fact'' in financial markets [1][2][3][4][5][6][7][8][9][10][11][12][13]. The efficient market hypothesis (EMH) proposed by Fama [14] indicate the random walk behavior of asset prices and unavailability of well forecasting asset prices in the future.…”

Section: Introductionmentioning

confidence: 99%

“…For commodities, the stronger higher order correlations in price fluctuations resulted in broader multifractal spectra. The evidence in Wang et al [16] also showed that the degree of multifractality could be used to measure the degree of market inefficiency in the Shanghai stock market. Using the multifractal spectrum method, Sun et al [17] investigated the multifractality of the Hong Kong stock market.…”

Section: Introductionmentioning

confidence: 99%

Forecasting volatility in Shanghai and Shenzhen markets based on multifractal analysis

Chen

2011

Physica A: Statistical Mechanics and its Applications

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Analysis of market efficiency for the Shanghai stock market over time

Cited by 88 publications

References 19 publications

Project-Based Market Competition and Policy Implications for Sustainable Developments in Building and Construction Sectors

Project-Based Market Competition and Policy Implications for Sustainable Developments in Building and Construction Sectors

Characterizing Complexity Changes in Chinese Stock Markets by Permutation Entropy

Forecasting volatility in Shanghai and Shenzhen markets based on multifractal analysis

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