scholarly journals Growth enterprise market in Hong Kong

2019 ◽  
Vol 27 (1) ◽  
pp. 19-34
Author(s):  
Trang Nguyen ◽  
Taha Chaiechi ◽  
Lynne Eagle ◽  
David Low
Keyword(s):  
Hong Kong ◽  
Stock Market ◽  
Long Memory ◽  
Structural Breaks ◽  
Global Financial Crisis ◽  
Statistical Significance ◽  
Weak Form ◽  
Content Type ◽  
Growth Enterprise Market ◽  
Hedging Strategies

Purpose Growth enterprise market (GEM) in Hong Kong is acknowledged as one of the world’s most successful examples of small and medium enterprise (SME) stock market. The purpose of this paper is to examine the evolving efficiency and dual long memory in the GEM. This paper also explores the joint impacts of thin trading, structural breaks and inflation on the dual long memory. Design/methodology/approach State-space GARCH-M model, Kalman filter estimation, factor-adjustment techniques and fractionally integrated models: ARFIMA–FIGARCH, ARFIMA–FIAPARCH and ARFIMA–HYGARCH are adopted for the empirical analysis. Findings The results indicate that the GEM is still weak-form inefficient but shows a tendency towards efficiency over time except during the global financial crisis. There also exists a stationary long-memory property in the market return and volatility; however, these long-memory properties weaken in magnitude and/or statistical significance when the joint impacts of the three aforementioned factors were taken into account. Research limitations/implications A forecasts of the hedging model that capture dual long memory could provide investors further insights into risk management of investments in the GEM. Practical implications The findings of this study are relevant to market authorities in improving the GEM market efficiency and investors in modelling hedging strategies for the GEM. Originality/value This study is the first to investigate the evolving efficiency and dual long memory in an SME stock market, and the joint impacts of thin trading, structural breaks and inflation on the dual long memory.

scholarly journals Does switching trading venues create value? Evidence from Hong Kong

2020 ◽  
Vol 27 (2) ◽  
pp. 209-222 ◽  
Author(s):  
Johnny K.H. Kwok
Keyword(s):  
Hong Kong ◽  
Stock Market ◽  
Stock Price ◽  
Abnormal Returns ◽  
Excess Returns ◽  
Trading Activity ◽  
Content Type ◽  
Growth Enterprise Market ◽  
Two Measures ◽  
Hong Kong Stock Market

PurposeThe purpose of this paper is to study whether switching trading venues create value in the Hong Kong stock market.Design/methodology/approachBy using an event study, the paper investigates the abnormal returns (AR) earned by firms in the Growth Enterprise Market (GEM) relating to switching to the Main Board (MB). Two measures, turnover of the stock and Amihud’s (2002) illiquidity ratio, are used to examine the liquidity effects.FindingsThe switch is accompanied by a long-term increase in stock price for low liquidity firms only. High liquidity firms underperform with persistent negative excess returns after switching, while the transient negative excess returns in low liquidity firms reverse gradually. The results further show a significant increase in trading activity for low liquidity firms following the switch, while there is a significant decline in both trading activity and liquidity in firms with high liquidity. The overall results suggest that moving from GEM to the MB is beneficial to low liquidity firms but detrimental to high liquidity firms.Originality/valueThis study is the first to investigate whether moving from GEM to the MB creates value in the Hong Kong stock market.

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.

An artificial neural network augmented GARCH model for Islamic stock market volatility: Do asymmetry and long memory matter?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Walid Chkili ◽  
Manel Hamdi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Stock Market ◽  
Long Memory ◽  
Global Financial Crisis ◽  
Terrorist Attack ◽  
Performance Criteria ◽  
Type Model ◽  
Content Type ◽  
Artificial Neural

Purpose The purpose of this study is to investigate the volatility and forecast accuracy of the Islamic stock market for the period 1999–2017. This period is characterized by the occurrence of several economic and political events such as the September 11, 2001, terrorist attack and the 2007–2008 global financial crisis. Design/methodology/approach This study constructs a new hybrid generalized autoregressive conditional heteroskedasticity (GARCH)-type model based on an artificial neural network (ANN). This model is applied to the daily Dow Jones Islamic Market World Index during the period June 1999–January 2017. Findings The in-sample results show that the volatility of the Islamic stock market can be better described by the fractionally integrated asymmetric power ARCH (FIAPARCH) approach that takes into account asymmetry and long memory features. Considering the out-of-sample analysis, this paper has applied a hybrid forecasting model, which combines the FIAPARCH approach and the ANN. Empirical results reveal that the proposed hybrid model (FIAPARCH-ANN) outperforms all other single models such as GARCH, fractional integrated GARCH and FIAPARCH in terms of all performance criteria used in the study. Practical implications The results have some implications for Islamic investors, portfolio managers and policymakers. These implications are related to the optimal portfolio diversification decision, the hedging strategy choice and the risk management analysis. Originality/value The paper develops a new framework that combines an ANN and FIAPARCH model that introduces two important features of time series, namely, asymmetry and long memory.

Absence of the weekend effect and industry-style portfolios

2019 ◽  
Vol 12 (4) ◽  
pp. 463-475
Author(s):  
Selma Izadi ◽  
Abdullah Noman
Keyword(s):  
New York ◽  
Stock Market ◽  
Structural Breaks ◽  
Stock Exchange ◽  
Structural Break ◽  
Weekend Effect ◽  
Content Type ◽  
Market Portfolio ◽  
The Us ◽  
Using Data

Purpose The existence of the weekend effect has been reported from the 1950s to 1970s in the US stock markets. Recently, Robins and Smith (2016, Critical Finance Review, 5: 417-424) have argued that the weekend effect has disappeared after 1975. Using data on the market portfolio, they document existence of structural break before 1975 and absence of any weekend effects after that date. The purpose of this study is to contribute some new empirical evidences on the weekend effect for the industry-style portfolios in the US stock market using data over 90 years. Design/methodology/approach The authors re-examine persistence or reversal of the weekend effect in the industry portfolios consisting of The New York Stock Exchange (NYSE), The American Stock Exchange (AMEX) and The National Association of Securities Dealers Automated Quotations exchange (NASDAQ) stocks using daily returns from 1926 to 2017. Our results confirm varying dates for structural breaks across industrial portfolios. Findings As for the existence of weekend effects, the authors get mixed results for different portfolios. However, the overall findings provide broad support for the absence of weekend effects in most of the industrial portfolios as reported in Robins and Smith (2016). In addition, structural breaks for other weekdays and days of the week effects for other days have also been documented in the paper. Originality/value As far as the authors are aware, this paper is the first research that analyzes weekend effect for the industry-style portfolios in the US stock market using data over 90 years.

What drives the venture capital investments in China?

2019 ◽  
Vol 13 (3) ◽  
pp. 574-602 ◽  
Author(s):  
Yixi Ning ◽  
Gubo Xu ◽  
Ziwu Long
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Global Financial Crisis ◽  
High Growth ◽  
Investment Strategies ◽  
Stock Market Crash ◽  
Content Type ◽  
Risk Levels ◽  
Aggregate Amount ◽  
A Share

Purpose This study aims to examine the venture capital (VC) industry in China. It has demonstrated a history of high growth with significant variations over time. The authors have examined the trends and determinants of VC investments in China over a 20-year period from 1995 to 2014. They find that the aggregate amount of VC investments, the total number of venture deals and the average amount of venture investments per deal in China are all significantly impacted by macroeconomic conditions (i.e. GDP, export, money supply), technology innovations and financial market indicators (i.e. initial public offerings (IPOs), interest rate, price-to-earnings ratio, etc.). They also find that the 2007 China A-Share stock market crash and the subsequent global financial crisis have motivated VCists in China to adjust their investment strategies and risk levels by allocating more capital to later-stage investments and securing more deals with later-round financings. However, after the 2008 global financial crisis, the China’s venture industry has recovered faster compared to the US counterpart response. Design/methodology/approach The authors first perform trend analysis of VC investments at an aggregate level, by stages of development, and across industry from 1995 to 2014.To test H1 and H2, the authors use multiple regression models with lagged explanatory variables. To test H3, the authors use univariate tests to compare the measures of VC investments at an aggregate level, stage funds ratios, stage deals ratios and financing series ratios during both a five-year and seven-year time windows around the 2007 A-Share stock market crash and the subsequent financial crisis. Findings The development of the VC industry in China has demonstrated a history of high growth with significant variation over time. The authors find that the aggregate amount of VC investments, the total number of venture deals and the average amount of venture investments per deal in China are all significantly impacted by macroeconomic conditions (i.e. GDP, export, money supply), technology innovations and financial market indicators (i.e. IPOs, interest rate, price-to-earnings ratio, etc.). The authors also find that the 2007 China A-Share stock market crash and the subsequent global financial crisis have motivated VCists in China to adjust their investment strategies and risk by allocating more capital to later-stage investments and securing more deals with later-round financings. However, the China VC industry has recovered faster compared to the USA just after the 2008 global financial crisis. Research limitations/implications There are also limitations in the study. The VC data in China in the earlier 1990s might not be very reliable due to the quality of statistics. Therefore, the trend analysis and discussions mainly focus on the time after 2000. Also, the authors cannot find VC financing sequence data for the analysis. Second, there is no doubt that the policy impact from Chinese transforming economic system and government policies on its VC industry is substantial (Su and Wang, 2013). However, they cannot find an appropriate variable to be included in the empirical models to consider this effect. Further study on this area would provide meaningful information. Third, although the authors have done comparison study between the VC industry in China in this study and the VC industry in the US documented in Ning et al. (2015) and discussed some interesting findings, more in-depth research in this area will be very useful. Practical implications The findings have meaningful implications for VCists and start-up companies seeking equity financings in China. VCists should closely monitor macroeconomic and market conditions to make appropriate adjustments to their risk and investment strategies. Entrepreneurs seeking equity financings for their business could also monitor the identified macroeconomic and market indicators, which can help them with their timing and to negotiate a better equity financing deal. VC financing is more likely to succeed when key macroeconomic and market indicators become favorable. Originality/value This paper contributes to the literature by testing the supply and demand theory on the VC market proposed by Poterba (1989) and Gompers and Lerner (1998) from the macroeconomic perspective using 20 years’ VC data from China. The authors also examine how the 2007 A-Share stock market crash and the subsequent financial crisis affected VCists to adjust their risk levels and investment strategies. It provides useful information for international academia and policymakers to understand the quick rise of China VC industry. The authors also find that the macroeconomic drivers of VC industry are somewhat different under different economic systems.

scholarly journals Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?

Agriculture ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 93
Author(s):  
Pavel Kotyza ◽  
Katarzyna Czech ◽  
Michał Wielechowski ◽  
Luboš Smutka ◽  
Petr Procházka
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Financial Market ◽  
Structural Breaks ◽  
Structural Changes ◽  
Global Financial Crisis ◽  
Market Uncertainty ◽  
Volatility Index ◽  
The Global Financial Crisis ◽  
The Relationship

Securitization of the agricultural commodity market has accelerated since the beginning of the 21st century, particularly in the times of financial market uncertainty and crisis. Sugar belongs to the group of important agricultural commodities. The global financial crisis and the COVID-19 pandemic has caused a substantial increase in the stock market volatility. Moreover, the novel coronavirus hit both the sugar market’s supply and demand side, resulting in sugar stock changes. The paper aims to assess potential structural changes in the relationship between sugar prices and the financial market uncertainty in a crisis time. In more detail, using sequential Bai–Perron tests for structural breaks, we check whether the global financial crisis and the COVID-19 pandemic have induced structural breaks in that relationship. Sugar prices are represented by the S&P GSCI Sugar Index, while the S&P 500 option-implied volatility index (VIX) is used to show stock market uncertainty. To investigate the changes in the relationship between sugar prices and stock market uncertainty, a regression model with a sequential Bai–Perron test for structural breaks is applied for the daily data from 2000–2020. We reveal the existence of two structural breaks in the analysed relationship. The first breakpoint was linked to the global financial crisis outbreak, and the second occurred in December 2011. Surprisingly, the COVID-19 pandemic has not induced the statistically significant structural change. Based on the regression model with Bai–Perron structural changes, we show that from 2000 until the beginning of the global financial crisis, the relationship between the sugar prices and the financial market uncertainty was insignificant. The global financial crisis led to a structural change in the relationship. Since August 2008, we observe a significant and negative relationship between the S&P GSCI Sugar Index and the S&P 500 option-implied volatility index (VIX). Sensitivity analysis conducted for the different financial market uncertainty measures, i.e., the S&P 500 Realized Volatility Index confirms our findings.

scholarly journals Changes of China’s agri-food exports to Germany caused by its accession to WTO and the 2008 financial crisis

2015 ◽  
Vol 7 (2) ◽  
pp. 262-279 ◽  
Author(s):  
Zhichao Guo ◽  
Yuanhua Feng ◽  
Thomas Gries
Keyword(s):  
Time Series ◽  
Financial Crisis ◽  
Regression Models ◽  
Structural Breaks ◽  
Global Financial Crisis ◽  
Middle Part ◽  
Change Points ◽  
Content Type ◽  
The World ◽  
Before And After

Purpose – The purpose of this paper is to investigate changes of China’s agri-food exports to Germany caused by China’s accession to WTO and the global financial crisis in a quantitative way. The paper aims to detect structural breaks and compare differences before and after the change points. Design/methodology/approach – The structural breaks detection procedures in this paper can be applied to find out two different types of change points, i.e. in the middle and at the end of one time series. Then time series and regression models are used to compare differences of trade relationship before and after the detected change points. The methods can be employed in any economic series and work well in practice. Findings – The results indicate that structural breaks in 2002 and 2009 are caused by China’s accession to WTO and the financial crisis. Time series and regression models show that the development of China’s exports to Germany in agri-food products has different features in different sub-periods. Before 1999, there is no significant relationship between China’s exports to Germany and Germany’s imports from the world. Between 2002 and 2008 the former depends on the latter very strongly, and China’s exports to Germany developed quickly and stably. It decreased, however suddenly in 2009, caused by the great reduction of Germany’s imports from the world in that year. But China’s market share in Germany still had a small gain. Analysis of two categories in agri-food trade also leads to similar conclusions. Comparing the two events we see rather different patterns even if they both indicate structural breaks in the development of China’s agri-food exports to Germany. Originality/value – This paper partly originally proposes two statistical algorithms for detecting different kinds of structural breaks in the middle part and at the end of a short-time series, respectively.

Does macroeconomic uncertainty really matter in predicting stock market behavior? A comparative study on China and USA

2020 ◽  
Vol 10 (4) ◽  
pp. 393-427 ◽  
Author(s):  
Ghulam Abbas ◽  
Shouyang Wang
Keyword(s):  
Risk Factors ◽  
Financial Crisis ◽  
Stock Market ◽  
Global Financial Crisis ◽  
Content Type ◽  
Macroeconomic Variables ◽  
Macroeconomic Risk ◽  
Stock Market Return ◽  
Macroeconomic Uncertainty ◽  
The Impact

PurposeThe study aims to analyze the interaction between macroeconomic uncertainty and stock market return and volatility for China and USA and tries to draw some invaluable inferences for the investors, portfolio managers and policy analysts.Design/methodology/approachEmpirically the study uses GARCH family models to capture the time-varying volatility of stock market and macroeconomic risk factors by using monthly data ranging from 1995:M7 to 2018:M6. Then, these volatility series are further used in the multivariate VAR model to analyze the feedback interaction between stock market and macroeconomic risk factors for China and USA. The study also incorporates the impact of Asian financial crisis of 1997–1998 and the global financial crisis of 2007–2008 by using dummy variables in the GARCH model analysis.FindingsThe empirical results of GARCH models indicate volatility persistence in the stock markets and the macroeconomic variables of both countries. The study finds relatively weak and inconsistent unidirectional causality for China mainly running from the stock market to the macroeconomic variables; however, the volatility spillover transmission reciprocates when the impact of Asian financial crisis and Global financial crisis is incorporated. For USA, the contemporaneous relationship between stock market and macroeconomic risk factors is quite strong and bidirectional both at first and second moment level.Originality/valueThis study investigates the interaction between stock market and macroeconomic uncertainty for China and USA. The researchers believe that none of the prior studies has made such rigorous comparison of two of the big and diverse economies (China and USA) which are quite contrasting in terms of political, economic and social background. Therefore, this study also tries to test the presumed conception that macroeconomic uncertainty in China may have different impact on the stock market return and volatility than in USA.

scholarly journals Crisis determination and financial contagion: an analysis of the Hong Kong and Tokyo stock markets using an MSBVAR approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Haytem Troug ◽  
Matt Murray
Keyword(s):  
Hong Kong ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
Current Data ◽  
Financial Contagion ◽  
Macroeconomic Factors ◽  
Content Type ◽  
Crisis Period ◽  
Dynamic Relationship ◽  
Using Data

PurposeThe purpose of this paper then, is to add to the existing literature on financial contagion. While a vast amount of the debate has been made using data from the late 1990s, this paper differentiates itself by analysing more current data, centred around the most recent global financial crisis, with specific focus on the stock markets of Hong Kong and Tokyo.Design/methodology/approachEmploying Pearson and Spearman correlation measures, the dynamic relationship of the two markets is determined over tranquil and crisis periods, as specified by an Markov-Switching Bayesian Vector AutoRegression (MSBVAR) model.FindingsThe authors find evidence in support of the existence of financial contagion (defined as an increase in correlation during a crisis period) for all frequencies of data analysed. This contagion is greatest when examining lower-frequency data. Additionally, there is also weaker evidence in some data sub-samples to support “herding” behaviour, whereby higher market correlations persist, following a crisis period.Research limitations/implicationsThe intention of this paper was not to analyse the cause or transmission mechanism of contagion between financial markets. Therefore future studies could extend the methodology used in this paper by including exogenous macroeconomic factors in the MSBVAR model.Originality/valueThe results of this paper serve to explain why the debate of the persistence and in fact existence of financial contagion remains alive. The authors have shown that the frequency of a time series dataset has a significant impact on the level of observed correlation and thus observation of financial contagion.

Market efficiency and the global financial crisis: evidence from developed markets

2018 ◽  
Vol 35 (3) ◽  
pp. 362-385 ◽  
Author(s):  
Omid Sabbaghi ◽  
Navid Sabbaghi
Keyword(s):  
Financial Crisis ◽  
Market Efficiency ◽  
Global Financial Crisis ◽  
Weak Form ◽  
Content Type ◽  
Developed Markets ◽  
The Usa ◽  
Econometric Tests ◽  
The Impact ◽  
Empirical Investigations

Purpose This study aims to provide one of the first empirical investigations of market efficiency for developed markets during the recent global financial crisis. Design/methodology/approach Using the Morgan Stanley Capital International (MSCI) country indices as proxies for national stock markets, the study conducts a battery of econometric tests in assessing weak-form market efficiency for the developed markets. Findings The inferential outcomes are consistent among the different tests. Specifically, the study finds that the majority of developed markets are weak-form efficient while the USA is the sole equity market to be commonly diagnosed as weak-form inefficient across the different tests when using full period data spanning the January 2008-November 2011 period. However, when basing the analysis on one-year subsamples over the identical time period, this study fails to reject weak-form market efficiency for all of the developed markets and presents evidence consistent with the Adaptive Market Hypothesis as described by Urquhart and Hudson (2013). When applying technical analysis for the case of the USA over the full study period, the results indicate that the return predictabilities can be exploited for some horizon of variable length moving average (VMA) trading rules. Originality/value This study provides one of the first empirical investigations of market efficiency for developed markets during the recent global financial crisis using an extended set of econometric tests. The study contributes to the existing body of empirical research that formally assesses the impact of a financial crisis on stock market efficiency and underlines the significance and relevance of examining market efficiency through subsample analysis.

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