Speculative bubbles in segmented markets: Evidence from Chinese cross-listed stocks

Pavlidis, Efthymios; Vasilopoulos, Konstantinos

doi:10.1016/j.jimonfin.2020.102222

Cited by 9 publications

(9 citation statements)

References 112 publications

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“…Research under the keyword "price discovery" is a hot point for current researchers, where scholars explored the effect of short selling (Chen et al, 2016), market integration (Ghadhab and Hellara, 2016a), exchange rates (Grammig et al, 2005), home market (Frijns et al, 2010), and related stocks (Korczak and Phylaktis, 2010) on the equity prices. The law of one price states that the price of any identical asset should be the same across the markets provided if there is no market segmentation or friction (Pavlidis and Vasilopoulos, 2020). In their study, Esqueda et al (2015) state that the ADR price must be equal to the price of the underlying security after adjusting for the ADR ratio and exchange rate.…”

Section: Keyword Analysismentioning

confidence: 99%

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Mapping the intellectual structure and demystifying the research trend of cross listing: a bibliometric analysis

Batra

Saini

Yadav

et al. 2022

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PurposeThis study aims to conduct a comprehensive bibliometric analysis to determine the intellectual structure of cross-listing studies and suggests a road map for future research in this field.Design/methodology/approachA step-by-step procedure was carried out. With the help of a defined search string, 580 articles from reputed journals have been retrieved from the Scopus database. Bibliographic coupling and keyword analysis were executed to understand the current research scenario and future research directions in this research field. In addition, R Studio combined with VOSviewer was employed to analyse and visualise the data.FindingsThe results provide a deeper insight into publication trends, most prolific countries, institutions and journals in the area of cross-listing. The highest collaboration was observed between the authors in the USA and Canada. Moreover, the results contradict Bradford's and Lotka's laws. A thorough review of the literature identifies five clusters in this domain. Finally, keyword analysis offers a future road map in cross-listing research.Originality/valueResearchers have shown greater interest in cross-listing topics over the past decades. Even though the research volume on this subject is increasing, the current retrospective is still insufficient. To the best of the authors' knowledge, this study is the first to provide valuable insights to practitioners, academicians, and prospective researchers about the intellectual structure of cross-listing and also offers future avenues in this research field through bibliometric analysis.

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Section: Keyword Analysismentioning

confidence: 99%

“…, 2010), and related stocks (Korczak and Phylaktis, 2010) on the equity prices. The law of one price states that the price of any identical asset should be the same across the markets provided if there is no market segmentation or friction (Pavlidis and Vasilopoulos, 2020). In their study, Esqueda et al .…”

Section: Network Analysismentioning

confidence: 99%

Mapping the intellectual structure and demystifying the research trend of cross listing: a bibliometric analysis

Batra

Saini

Yadav

et al. 2022

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“…One of the most widely recognized models allowing for bubbles is the rational expectation asset-pricing model. us, our theoretical framework closely relates to that of Diba and Grossman [35], Gürkaynak [37], and Pavlidis and Vasilopoulos [44]. However, we extend the stylized asset-pricing model to explain why prices tend to show excess volatility in storable commodity markets.…”

Section: Theoretical Modelmentioning

confidence: 92%

Booms and Busts in the Oil Market: Identifying Speculative Bubbles Using a Continuous‐Time Dynamic System

Zhang

2021

Complexity

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The sharp changes in oil prices since 2004 featured a nonlinear data-generating mechanism which displayed bubble-like behavior. A popular view is that such a salient pattern cannot be explained by shifts in economic fundamentals, but was driven by speculative bubbles as a consequence of the increased financialization of oil future markets. Testing this hypothesis, however, is challenging since the fundamental component of the oil price is unobservable. This paper attempts to isolate the contribution of speculative bubbles and fundamentals to the evolution of oil prices by providing a stylized model of commodity pricing. Motivated by our theoretical model, we adopt a continuous-time model with a random and time-varying persistence parameter to empirically investigate the presence of speculative bubbles in daily oil future prices over the period April 1983 to June 2020. We do not find any evidence in favor of speculative bubbles, although we indeed find that oil prices exhibit episodes of unstable behavior after 2004.

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“…The results demonstrated the ability to detect positive and negative bubbles related to known historical events based on the unique periodic rule login index. Pavlidis and Vasilopoulos (2020) proposed a new method to test speculative bubbles in divided capital markets using a community of Chinese companies holding Hong Kong shares. They use two-unit root and regression tests to predict the presence of bubbles in this market.…”

Section: Mf 494mentioning

confidence: 99%

Portfolio optimization in the capital market bubble space, an application of meta-heuristic algorithms

Mohammadi

Khoshouei²,

Chadegani³

2022

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PurposeIn this study, to maximize returns and minimize investment risk, an attempt was made to form an optimal portfolio under conditions where the capital market has a price bubble. According to the purpose, the research was of the applied type, in terms of data, quantitative and postevent, and in terms of the type of analysis, it was of the descriptive-correlation type. Sequence, skewness and kurtosis tests were used to identify the months with bubbles from 2015 to 2021 in the Tehran Stock Exchange. After identifying the bubble courses, artificial bee colony meta-heuristic and invasive weed algorithms were used to optimize the portfolio. The purpose of this paper is to address these issues.Design/methodology/approachThe existence of bubbles in the market, especially in the capital market, can prevent the participation of investors in the capital market process and the correct allocation of financial resources for the economic development of the country. However, due to the goal of investors to achieve a portfolio of high returns with the least amount of risk, there is need to pay attention to these markets increases.FindingsThe results identify 14 periods of price bubbles during the study period. Additionally, stock portfolios with maximum returns and minimum risk were selected for portfolio optimization. According to the results of using meta-heuristic algorithms to optimize the portfolio, in relation to the obtained returns and risk, no significant difference was observed between the returns and risk of periods with price bubbles in each of the two meta-heuristic algorithms. This study can guide investors in identifying bubble courses and forming an optimal portfolio under these conditions.Research limitations/implicationsOne of the limitations of this research is the non-generalizability of the findings to stock exchanges of other countries and other time periods due to the condition of the price bubble, as well as other companies in the stock market due to the restrictions considered for selecting the statistical sample.Originality/valueThis study intends to form an optimal stock portfolio in a situation where the capital market suffers from a price bubble. This study provides an effective and practical solution for investors in the field of stock portfolio optimization.

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Speculative bubbles in segmented markets: Evidence from Chinese cross-listed stocks

Cited by 9 publications

References 112 publications

Mapping the intellectual structure and demystifying the research trend of cross listing: a bibliometric analysis

Mapping the intellectual structure and demystifying the research trend of cross listing: a bibliometric analysis

Booms and Busts in the Oil Market: Identifying Speculative Bubbles Using a Continuous‐Time Dynamic System

Portfolio optimization in the capital market bubble space, an application of meta-heuristic algorithms

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