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This Author published in this journals
All Journal International Journal of Public Health Science (IJPHS) Journal of Current Research in Blockchain
Wang Yang
Beijing Information Science and Technology University
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Health Professions

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Aerobics research in China: characteristics, hotspots, and evolution visualized Yang, Wang; Zainuddin, Zainal Abidin B
International Journal of Public Health Science (IJPHS) Vol 14, No 2: June 2025
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijphs.v14i2.24889

Abstract

This study utilizes CiteSpace software to visually analyze 679 core journal papers from the CNKI database, exploring the landscape of aerobics research in China. It aims to identify influential authors and institutions while elucidating the evolution of research focus from its early stages to current trends. The primary objective is to explore the characteristics of aerobics research, including hot topics, evolving frontiers, and key developments. By examining titles, keywords, abstracts, and other materials, CiteSpace software provides insights into the scientific knowledge graph, emphasizing influential authors and institutions in aerobics research. The findings reveal a notable shift in focus from early public teaching to current emphasis on competitive aerobics, physical education, and athlete transitions. The research field has expanded to encompass diversified topics, showcasing continuous depth in empirical and theoretical investigations. Three distinct periods are identified in research frontiers: early, middle, and recent stages, each with unique directions and emphases. The study recommends a multi-disciplinary integrated development approach in aerobics research, emphasizing enriched teaching and competition visions, improved regional integration policies, and a comprehensive display of the field’s research and development status. Acknowledging evolving trends and diversification will contribute to a holistic understanding and continued advancement of aerobics research.
Modeling Financial Volatility of S&P 500 ETF Using GARCH and Rolling Window Analysis Yang, Wang; Fan, Chen
Journal of Current Research in Blockchain Vol. 3 No. 1 (2026): Regular Issue March 2026
Publisher : Bright Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jcrb.v3i1.58

Abstract

This study investigates the financial volatility of the SPDR S&P 500 ETF (SPY) using two distinct approaches the Rolling Window Volatility (20-day) and the GARCH (1,1) Approximation to analyze and compare the dynamic behavior of market risk. The analysis utilizes daily SPY price data to compute logarithmic returns and model volatility persistence over time. Descriptive statistics indicate that SPY returns exhibit volatility clustering, leptokurtosis, and negative skewness, implying that extreme market movements occur more frequently than predicted by a normal distribution. Empirical results show that both volatility measures successfully capture the cyclical nature of market risk but differ in responsiveness and interpretability. The rolling window method provides an intuitive and historical view of volatility patterns, while the GARCH (1,1) model captures conditional and time-varying volatility more effectively by incorporating both short-term shocks and long-term persistence. Comparative analysis reveals that GARCH estimates produce smoother and more adaptive volatility dynamics, making them more suitable for forecasting and real-time risk assessment. Overall, the findings confirm that volatility in financial markets is not constant but evolves dynamically in response to new information and investor behavior. The study emphasizes the importance of conditional volatility models in improving the accuracy of risk evaluation, portfolio management, and market forecasting, particularly during periods of heightened uncertainty.
Co-Authors Fan, Chen Zainuddin, Zainal Abidin B