scholarly journals Simulation and Statistical Analysis of Market Return Fluctuation by Zipf Method

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
Yalong Guo ◽  
Jun Wang
Keyword(s):  
Statistical Analysis ◽  
Stock Markets ◽  
Stock Price ◽  
Composite Index ◽  
Price Model ◽  
Financial Model ◽  
Stock Indices ◽  
Global Stock Markets ◽  
Global Stock ◽  
Different Time Scales

We investigate the fluctuation behaviors of financial stock markets by Zipf analysis. In the present paper, the empirical research is made to describe ensembles and specifics of stock price returns for global stock indices, and the corresponding Zipf distributions are given. First we study the fluctuation behavior of global stock markets by(m,k)-Zipf method. Then we consider a dynamic stock price model, and we analyze the absolute frequencies and the relative frequencies for this financial model. Further, the Zipf distributions of returns for SSE Composite Index are studied for different time scales.

scholarly journals Regularities in stock markets

2020 ◽  
Vol 31 (10) ◽  
pp. 2050145
Author(s):  
Abhin Kakkad ◽  
Harsh Vasoya ◽  
Arnab K. Ray
Keyword(s):  
Stock Markets ◽  
Asymptotic Convergence ◽  
Daily Growth ◽  
Monthly Average ◽  
Stock Indices ◽  
Self Similar ◽  
The Mean ◽  
Global Stock Markets ◽  
Stock Values ◽  
Global Stock

From the stock markets of six countries with high GDP, we study the stock indices, S&P 500 (NYSE, USA), SSE Composite (SSE, China), Nikkei (TSE, Japan), DAX (FSE, Germany), FTSE 100 (LSE, Britain) and NIFTY (NSE, India). The daily mean growth of the stock values is exponential. The daily price fluctuations about the mean growth are Gaussian, but with a nonzero asymptotic convergence. The growth of the monthly average of stock values is statistically self-similar to their daily growth. The monthly fluctuations of the price follow a Wiener process, with a decline of the volatility. The mean growth of the daily volume of trade is exponential. These observations are globally applicable and underline regularities across global stock markets.

scholarly journals PENGARUH PASAR SAHAM DUNIA TERHADAP PASAR SAHAM INDONESIA

ETIKONOMI ◽  
2012 ◽  
Vol 11 (2) ◽  
Author(s):  
Elvin Adityara
Keyword(s):  
Stock Market ◽  
Granger Causality ◽  
Stock Markets ◽  
Stock Price ◽  
Price Indices ◽  
Global Stock Markets ◽  
Global Stock

This research was intended to analyze the causality of the global stock markets to Indonesian stock market. The variables of this research were used stock price indices from nine countries. This research using Granger Causality and VAR from 2004 up to 2010. USA, Japan, and England were selected because those countries had strong economics. The results, there are causality Granger among the global stock markets to Indonesian stock market.The global stock markets that has bi-directional causality were Australian stock market, England stock market, Singapore stock market, and Philipine stock market. Meanwhile, the global stock markets that has uni-directional causality were Japan stock market, USA stock market, Hongkong stock market, and Malaysia stock market.DOI: 10.15408/etk.v11i2.1887

Winter Is Coming: Repercussions of a New COVID-19 Wave in Global Stock Markets

2020 ◽  
Author(s):  
Panagiotis Lazaris ◽  
Anastasios Petropoulos ◽  
Vasileios Siakoulis ◽  
Evangelos Stavroulakis ◽  
Nikos Vlachogiannakis ◽  
...  
Keyword(s):  
Stock Markets ◽  
Global Stock Markets ◽  
Global Stock

COVID-19 and overconfidence bias: the case of developed, emerging and frontier markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vijay Kumar Shrotryia ◽  
Himanshi Kalra
Keyword(s):  
Stock Markets ◽  
Impulse Response Functions ◽  
Economic Activities ◽  
Content Type ◽  
Long Run ◽  
Governance Practices ◽  
Global Stock Markets ◽  
Developed Stock Markets ◽  
Overconfidence Bias ◽  
Global Stock

PurposeThe main purpose of the present study is to delve into the overconfidence bias in global stock markets during both pre COVID-19 and COVID-19 phases.Design/methodology/approachThe present study makes use of daily adjusted closing prices and volume of the broad market indices of 46 global stock markets over a period ranging from July 2015 till June 2020. The sample period is split into pre COVID-19 and COVID-19 phases. In order to test the overconfidence fallacy in the chosen stock markets, bivariate market-wide vector auto regression (VAR) models and impulse response functions (IRFs) have been employed in both phases.FindingsA highly significant contemporaneous relationship between market return and volume appears to be more pronounced in the Japanese, US, Chinese and Vietnamese stock markets in the pre COVID-19 era for the relevant coefficients are positive and highly significant for most lags. Coming to the period of turbulence, the present study discovers strong overconfident behavior in the Chinese, Taiwanese, Turkish, Jordanian and Vietnamese stock markets during COVID-19 phase.Practical implicationsA stark finding is that none of the developed stock markets reveal strong overconfidence bias during pandemic, suggesting a loss or decline in the investors' confidence. Therefore, the regulators should try to regain the investors' trust and confidence in the markets by ensuring honest, fair and transparent practices. The money managers should reduce the transaction cost to encourage trading and educate investors to hold a well-diversified portfolio to mitigate risk in the long run. The governments may launch recovery packages focusing on sustaining and improving economic activities. Finally, a better investment culture may be built by the corporate houses through good corporate governance practices to regain lost trust.Originality/valueThe present study appears to be the very first attempt to gauge overconfidence bias in the wake of a recent COVID-19 pandemic.

COVID-19 Vaccines: Saving Lives and the Global Stock Markets

2021 ◽  
Author(s):  
Kam Fong Chan ◽  
Zhuo Chen ◽  
Yuanji Wen ◽  
Tong Xu
Keyword(s):  
Stock Markets ◽  
Global Stock Markets ◽  
Global Stock
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