مقاله انگلیسی رایگان در مورد مدل سازی و پیش‌بینی نوسانات بازار سهام شاخص کامپوزیت – الزویر 2018

 

مشخصات مقاله
ترجمه عنوان مقاله مدل سازی و پیش‌بینی نوسانات بازار سهام شاخص کامپوزیت SSE با استفاده از مدل‌های GARCH
عنوان انگلیسی مقاله Modelling and forecasting the stock market volatility of SSE Composite Index using GARCH models
انتشار مقاله سال 2018
تعداد صفحات مقاله انگلیسی  36 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه الزویر
نوع نگارش مقاله
مقاله پژوهشی (Research article)
مقاله بیس این مقاله بیس میباشد
نمایه (index) scopus – master journals – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
4.639 در سال 2017
شاخص H_index 85 در سال 2018
شاخص SJR 0.844 در سال 2018
رشته های مرتبط مهندسی کامپیوتر – اقتصاد
گرایش های مرتبط مهندسی نرم افزار – اقتصاد مالی
نوع ارائه مقاله
ژورنال
مجله / کنفرانس سیستم های کامپیوتری نسل آینده – Future Generation Computer Systems
دانشگاه School of Accounting & Finance, Xiamen University Tan Kah Kee College, Zhangzhou Fujian, 363100, China
کلمات کلیدی مدل سازی، پیش بینی، بازار سهام، شاخص کامپوزیت SSE، مدل GARCH، قیمت سهام، هدایت متقابل
کلمات کلیدی انگلیسی Modelling, Forecasting, Stock market, SSE Composite Index, GARCH models, Stock price, Mutual conduction
شناسه دیجیتال – doi
https://doi.org/10.1016/j.future.2017.08.033
کد محصول E11645
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Outline
Highlights
Abstract
Keywords
1. Introduction
2. Literature review
3. Methodology
4. Empirical analysis
5. Summary
6. Conclusions and suggestions
Acknowledgements
References
Vitae

بخشی از متن مقاله:

Abstract

The stock market is constantly changing with uncertainties. Rapid dissemination of information and fast capital flow will lead to fluctuations of stock price, and the undulating price will affect the market in return. This is a process of mutual influence and mutual conduction. China’s stock market, which pertains to an emerging market, has been acutely volatile since the very beginning, and often appear radical ups and downs. This paper selects the SSE Composite Index as research object, through the application of GARCH type models to conduct empirical analysis, carving the features of this index from an econometric perspective. And on basis of the status quo of the volatility of SSE Composite Index, it offers some suggestions.

The result shows that from the time series point of view, the SSE Composite Index possesses significant properties of time-varying and clustering. Series distribution of it presents leptokurtosis with significant ARCH and GARCH effects. Moreover, by comparing the fitting and forecast performance of GARCH (1, 1) (symmetric) and TARCH (1, 1) and EGARCH (1, 1) (asymmetric), it can be concluded that EGARCH (1, 1) outperforms the others. Besides, China’s securities market should strengthen its system construction, reduce excessive government intervention and advocate rational investment philosophy.

Introduction

Background

Since the Shanghai Stock Exchange was formally established in 1990, China’s stock market has gone through a development journey of 27 years. Whereas it is now still of no high level of normalization in terms of supervision or institution, and with a strong volatility. The unstable stock market, unscientific investments and occasional event of malignant investment make the whole market full of highrisk, and propose sever challenges to institutions and individuals (Zhang, Luo and Tang, 2012). Many foreign institutional investors approved by the CSRC (China Securities Regulatory Commission) have joined the ranks of investors. Owing to the uncertainty and high-speed international capital flows, the environment of financing and investments has become increasingly complicated. China’s securities market is experiencing a period of both opportunities and risks (Fang, 2010). In this case, an accurate description of how the stock price fluctuates and how to determine the future rate of return of the stock market has become a hot issue in the academia and the investment community. Therefore, the study of volatility has significant theoretical significance and applicable value.

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