Transmission of shocks between Chinese financial market and oil market

2019 ◽  
Vol 15 (2) ◽  
pp. 262-286 ◽  
Author(s):  
Mouna Abdelhedi ◽  
Mouna Boujelbène-Abbes
Keyword(s):  
Stock Market ◽  
Wavelet Decomposition ◽  
Price Index ◽  
Garch Model ◽  
Continuous Wavelet ◽  
Volatility Spillover ◽  
Chinese Stock Market ◽  
Decomposition Technique ◽  
Content Type ◽  
Oil Market

Purpose The purpose of this paper is to empirically investigate the volatility spillover between the Chinese stock market, investor’s sentiment and oil market, specifically during the 2014‒2016 turmoil period. Design/methodology/approach This study used the daily and monthly China market price index, oil-price index and composite index of Chinese investor’s sentiment. The authors first use the DCC GARCH model in order to study the correlation between variables. Second, the authors use a continuous wavelet decomposition technique so as to capture both time- and frequency-varying features of co-movement variables. Finally, the authors examine the spillover effects by estimating the BEKK GARCH model. Findings The wavelet coherency results indicate a substantial co-movement between oil and Chinese stock markets in the periods of high volatility. BEKK GARCH model outcomes confirm this relation and report the noteworthy bidirectional transmission of volatility between oil market shocks and the Chinese investor’s sentiment, chiefly in the crisis period. These results support the behavioral theory of contagion and highlight that the Chinese investor’s sentiment is a channel through which shocks are transmitted between the oil and Chinese equity markets. Thus, these results are important for Chinese authorities that should monitor the investor’s sentiment to better control the interaction between financial and real markets. Originality/value This study makes three major contributions to the existing literature. First, it pays attention to the recent 2015 Chinese stock market bumble. Second, it has gone some way toward enhancing our understanding of the volatility spillover between the investor’s sentiment, investor’s sentiment variation, oil prices and stock market returns (variables of interest) during oil and stock market crises. Third, it uses the continuous wavelet decomposition technique since it reveals the linkage between variables of interest at different time horizons.

Volatility spillover from the Chinese stock market to E7 and G7 stock markets

2019 ◽  
Vol 46 (1) ◽  
pp. 90-105 ◽  
Author(s):  
Berna Kirkulak Uludag ◽  
Muzammil Khurshid
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Volatility Spillover ◽  
Chinese Stock Market ◽  
G7 Countries ◽  
Content Type ◽  
Government Interventions ◽  
Vector Autoregressive ◽  
Optimal Weights ◽  
Hedge Ratios

PurposeThe purpose of this paper is to examine volatility spillover from the Chinese stock market to E7 and G7 stock markets. Using the estimated results, the authors also analyze the optimal weights and optimal hedge ratios for the portfolios including stocks from E7 and G7 countries.Design/methodology/approachThe authors employed generalized vector autoregressive-generalized autoregressive conditional heteroskedasticity approach, developed by Ling and McAleer (2003), in order to analyze daily data on the national stock indices. Considering the late establishment of some E7 stock markets, the sampling covers the period from 1995 through 2015.FindingsThe findings indicate significant volatility spillover from the Chinese stock market to E7 and G7 stock markets. In particular, the Chinese stocks highly co-move with the stocks of countries within a same geographical region. While the highest volatility spillover occurs between China and India among E7 countries, the highest volatility spillover occurs between China and Japan among G7 countries. Furthermore, the examination of optimal weights and hedge ratios suggest that investors should hold more stocks from G7 countries than E7 countries for their portfolios.Originality/valueTo the best of the authors’ knowledge, this is the first study which investigates the volatility spillover in the stock markets of G7 and E7 countries. Moreover, the current study contributes particularly to the existing limited literature on the Chinese stock market. Since the Chinese stock market is not fully integrated to other markets and it is subject to intense government interventions, there is a widely accepted belief that the contagion effects from the Chinese stock market to other stock markets are not influential. This view discourages and limits the prospect studies. However, the findings of this paper refute this view and indicate significant interaction among the Chinese stock market and E7 and G7 stock markets.

The dependence structure in volatility between Shanghai and Shenzhen stock market in China

2016 ◽  
Vol 6 (3) ◽  
pp. 264-283 ◽  
Author(s):  
Mingyuan Guo ◽  
Xu Wang
Keyword(s):  
Stock Market ◽  
High Frequency ◽  
Estimation Method ◽  
Garch Model ◽  
Price Volatility ◽  
Market Volatility ◽  
High Frequency Data ◽  
Dependence Structure ◽  
Frequency Data ◽  
Content Type

Purpose – The purpose of this paper is to analyse the dependence structure in volatility between Shanghai and Shenzhen stock market in China based on high-frequency data. Design/methodology/approach – Using a multiplicative error model (hereinafter MEM) to describe the margins in volatility of China’s Shanghai and Shenzhen stock market, this study adopts static and time-varying copulas, respectively, estimated by maximum likelihood estimation method to describe the dependence structure in volatility between Shanghai and Shenzhen stock market in China. Findings – This paper has identified the asymmetrical dependence structure in financial market volatility more precisely. Gumbel copula could best fit the empirical distribution as it can capture the relatively high dependence degree in the upper tail part corresponding to the period of volatile price fluctuation in both static and dynamic view. Originality/value – Previous scholars mostly use GARCH model to describe the margins for price volatility. As MEM can efficiently characterize the volatility estimators, this paper uses MEM to model the margins for the market volatility directly based on high-frequency data, and proposes a proper distribution for the innovation in the marginal models. Then we could use copula-MEM other than copula-GARCH model to study on the dependence structure in volatility between Shanghai and Shenzhen stock market in China from a microstructural perspective.

Financial flexibility, managerial efficiency and firm life cycle on firm performance

2019 ◽  
Vol 16 (2) ◽  
pp. 168-180
Author(s):  
Heng-Yu Chang ◽  
Chun-Ai Ma
Keyword(s):  
Life Cycle ◽  
Firm Performance ◽  
Stock Market ◽  
Life Cycles ◽  
Mature Stage ◽  
Chinese Stock Market ◽  
Financial Flexibility ◽  
Content Type ◽  
Listed Firms ◽  
Managerial Efficiency

Purpose As the capital market in China is still developing, several constraints on a Chinese-listed firm’s financing strategy have a direct impact on its financial flexibility. The purpose of this paper is to reconstruct traditional financial flexibility index (FFI) derived from the western context, provide empirical evidence within eastern context by modified FFI and examine how the managerial efficiency of Chinese-listed firms is demonstrated with modified FFI to escort corporate life cycle hypothesis. Design/methodology/approach By tailored FFI to fit the contemporary operations of Chinese-listed firms, this study investigates how managerial efficiency varies across different life stages to demonstrate the moderating power in the firm performance of financially flexible firm. Findings It is found that financially flexible firms in the Chinese stock market generally experience good firm performance, yet the managerial efficiency could gradually be diminishing at their mature stage even firms’ financial flexibility remains consistent with the agency theory. This paper sheds light on the necessity to reexamine the components in financial flexibility based on the eastern context, and provides avenue to further understand the managerial behavior of Chinese listed firms when considering firm life cycles. Research limitations/implications Although it is difficult for this current study to offer the precise weights on each factor in calculating financial flexibility, the judgment matrix method is adopted to at least provide reliable estimates in accordance with Chinese business contexts with less than 10 percent errors in contrast to the actual weights. Practical implications This modified FFI is particularly suitable for Chinese-listed firms under certain unique financial reporting regulations by adjusting a number of weights and factors. This study may help practitioners understand the managerial conduct of publicly listed firms in China. Originality/value The paper constructs a modified FFI with Chinese stock market characteristics embedded, and provides insightful evidence to explain the new pecking order theory by considering the life cycle stage of Chinese-listed companies.

The optimal thermal causal path analysis on the relationship between international crude oil price and stock market

Kybernetes ◽  
2018 ◽  
Vol 47 (6) ◽  
pp. 1242-1261 ◽  
Author(s):  
Can Zhong Yao ◽  
Peng Cheng Kuang ◽  
Ji Nan Lin
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Stock Markets ◽  
Oil Prices ◽  
Oil Price ◽  
Chinese Stock Market ◽  
Crude Oil Price ◽  
Content Type ◽  
Crude Oil Prices ◽  
Causal Path

Purpose The purpose of this study is to reveal the lead–lag structure between international crude oil price and stock markets. Design/methodology/approach The methods used for this study are as follows: empirical mode decomposition; shift-window-based Pearson coefficient and thermal causal path method. Findings The fluctuation characteristic of Chinese stock market before 2010 is very similar to international crude oil prices. After 2010, their fluctuation patterns are significantly different from each other. The two stock markets significantly led international crude oil prices, revealing varying lead–lag orders among stock markets. During 2000 and 2004, the stock markets significantly led international crude oil prices but they are less distinct from the lead–lag orders. After 2004, the effects changed so that the leading effect of Shanghai composite index remains no longer significant, and after 2012, S&P index just significantly lagged behind the international crude oil prices. Originality/value China and the US stock markets develop different pattens to handle the crude oil prices fluctuation after finance crisis in 1998.

Stock prices' long memory in China and the United States

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhengxun Tan ◽  
Yao Fu ◽  
Hong Cheng ◽  
Juan Liu
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Long Memory ◽  
Stock Markets ◽  
Information Disclosure ◽  
Structural Breaks ◽  
Efficient Market Hypothesis ◽  
The United States ◽  
Chinese Stock Market ◽  
Content Type

PurposeThis study aims to examine the long memory as well as the effect of structural breaks in the US and the Chinese stock markets. More importantly, it further explores possible causes of the differences in long memory between these two stock markets.Design/methodology/approachThe authors employ various methods to estimate the memory parameters, including the modified R/S, averaged periodogram, Lagrange multiplier, local Whittle and exact local Whittle estimations.FindingsChina's two stock markets exhibit long memory, whereas the two US markets do not. Furthermore, long memory is robust in Chinese markets even when we test break-adjusted data. The Chinese stock market does not meet the efficient market hypothesis (EMHs), including the efficiency of information disclosure, regulations and supervision, investors' behavior, and trading mechanisms. Therefore, its stock prices' sluggish response to information leads to momentum effects and long memory.Originality/valueThe authors elaborately illustrate how long memory develops by analyzing not only stock market indices but also typical individual stocks in both the emerging China and the developed US, which diversifies the EMH with wider international stylized facts and findings when compared with previous literature. A couple of tests conducted to analyze structural break effects and spurious long memory demonstrate the reliability of the results. The authors’ findings have significant implications for investors and policymakers worldwide.

Is disposition related to momentum in Chinese market?

2015 ◽  
Vol 41 (6) ◽  
pp. 600-614 ◽  
Author(s):  
Liu Liu Kong ◽  
Min Bai ◽  
Peiming Wang
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Disposition Effect ◽  
Chinese Stock Market ◽  
Momentum Effect ◽  
Chinese Market ◽  
Firm Level ◽  
Content Type ◽  
Level Data ◽  
The Relationship

Purpose – The purpose of this paper is to examine whether the framework of Prospect Theory and Mental Accounting proposed by Grinblatt and Han (2005) can be applied to analyzing the relationship between the disposition effect and momentum in the Chinese stock market. Design/methodology/approach – The paper applies the methodology proposed by Grinblatt and Han (2005). Findings – Using firm-level data, with a sample period from January 1998 to June 2013, the authors find evidence that the momentum effect in the Chinese stock market is not driven by the disposition effect, contradicting the findings of Grinblatt and Han (2005) concerning the US stock market. The discrepancies in the findings between the Chinese and US stock markets are robust and independent of sample periods. Research limitations/implications – The findings suggest that Grinblatt and Han’s model may not be applicable to the Chinese stock market. This is possibly because of the regulatory differences between the two stock markets and cross-national variation in investor behavior; in particular, the short-selling prohibition in the Chinese stock market and greater reference point adaptation to unrealized gains/losses among Chinese compared to Americans. Originality/value – This study provides evidence of the inapplicability of Grinblatt and Han’s model for the Chinese stock market, and shows the differences in the relationship between disposition effect and momentum between the Chinese and US stock markets.

Does investor personality moderate the relationship between information sources and trading behavior? Evidence from Chinese stock market

2017 ◽  
Vol 43 (5) ◽  
pp. 545-566 ◽  
Author(s):  
Muhammad Zubair Tauni ◽  
Zia-ur-Rehman Rao ◽  
Hong-Xing Fang ◽  
Minghao Gao
Keyword(s):  
Stock Market ◽  
Personality Traits ◽  
Chinese Stock Market ◽  
Sources Of Information ◽  
Trading Behavior ◽  
Content Type ◽  
Trading Frequency ◽  
Word Of Mouth Communication ◽  
The Impact ◽  
The Relationship

Purpose The purpose of this paper is to investigate the impact of the key sources of information, namely, financial advice, word-of-mouth communication and specialized press, on trading behavior of Chinese stock investors. The study also analyzed if the association between the key sources of information and trading behavior is influenced by investor personality. Design/methodology/approach The authors adopted the Big Five personality framework and examined the survey results of individual stock investors (n=541) in China. Personality traits of investors were measured by the NEO-Five Factor Inventory (Costa and McCrae, 1989). The authors performed probit regression analysis to evaluate the moderating influence of investor personality traits on the association between sources of information and stock trading behavior. Findings The results of the study confirm the previous findings that the key sources of information used by investors as a foundation of their financial choices have a significant influence on their trading behavior. The study also provides empirical evidence that investor personality traits moderate the relationship between the key sources of information and trading behavior. Financial advisors tend to increase the frequency of trading in investors with openness, extraversion, neuroticism and agreeableness personality traits, and tend to decrease the intensity of trading in investors with conscientiousness trait. On the other hand, financial information acquired from word-of-mouth communication is more likely to enhance trading frequency in extraverted and agreeable investors, and is more likely to reduce trading frequency in investors with openness, conscientiousness and neuroticism traits. Finally, the use of specialized press leads to more adjustment in portfolios of the investors with openness and conscientiousness traits than those with other personality traits. An alternative mediated model was not supported. Originality/value This research contributes to information search literature and behavioral finance literature and provides empirical evidence that the psychological characteristics of investors are significant predictors of the variations in information-trading link. The study offers new theoretical insights of investors’ behavior due to the characteristics of Chinese stock market which are unique from other stock markets in the world. To the authors’ best knowledge, no previous study has been conducted so far in Chinese stock market to explore variations with regards to the impact of the key sources of information on trading behavior by the Big Five investor personality and this paper seeks to fill this gap.

An application of the information-adjusted noise model to the Shenzhen stock market

2016 ◽  
Vol 12 (1) ◽  
pp. 71-91 ◽  
Author(s):  
Xiaoming Xu ◽  
Vikash Ramiah ◽  
Imad Moosa ◽  
Sinclair Davidson
Keyword(s):  
Stock Market ◽  
Noise Model ◽  
Chinese Stock Market ◽  
Content Type ◽  
Asset Pricing Model ◽  
Noise Trader ◽  
Pricing Errors ◽  
Trading Activities ◽  
The Relationship ◽  
Information Pricing

Purpose – The purpose of this paper is to: first, test if information-adjusted noise model (IANM) can be applied in China; second, quantify noise trader risk, overreaction, underreaction and information pricing errors in that market; and third, explain the relationship between noise trader risk and return. Design/methodology/approach – The authors use a behavioural asset pricing model (BAPM), CAPM, the information-adjusted noise model and model proposed by Ramiah and Davidson (2010). Findings – The findings show that noise traders are active 99.7 per cent of the time on the Shenzhen A-share market. Furthermore, our results suggest that the Shenzhen market overreacts 41 per cent of the time, underreacts 18 per cent of the time and information pricing errors occur 40 per cent of the time. Originality/value – Various methods have been applied to the Chinese stock market in an effort to measure noise trading activities and all of them failed to account for information arrival. Our study uses a superior and alternative model to detect noise trader risk, overreaction and underreaction in China.

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