مقاله انگلیسی رایگان در مورد نوسانات قیمت سهام در بورس و بازار مبادلاتی – امرالد ۲۰۱۸

emerald

 

مشخصات مقاله
ترجمه عنوان مقاله پیش بینی نوسانات قیمت سهام بر اساس دیدگاه اطلاعات آماری در بورس و بازار مبادلاتی
عنوان انگلیسی مقاله Forecast of stock price fluctuation based on the perspective of volume information in stock and exchange market
انتشار مقاله سال ۲۰۱۸
تعداد صفحات مقاله انگلیسی ۲۰ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه امرالد
نوع نگارش مقاله
مقاله پژوهشی (Research article)
مقاله بیس این مقاله بیس میباشد
نمایه (index) scopus – master journals
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
شاخص H_index ۶ در سال ۲۰۱۸
شاخص SJR ۰٫۲۴۵ در سال ۲۰۱۸
رشته های مرتبط اقتصاد
گرایش های مرتبط اقتصاد پولی و اقتصاد مالی
نوع ارائه مقاله
ژورنال
مجله / کنفرانس بررسی بین المللی مالی چین – China Finance Review International
دانشگاه Jilin University – Changchun – China
کلمات کلیدی حجم بازار بورس، الگوریتم SMC، رابطه قیمت-حجم سهام، مدل SV-VOL
کلمات کلیدی انگلیسی Exchange market volume, SMC algorithm, Stock price-volume relationship, SV-VOL model
شناسه دیجیتال – doi
https://doi.org/10.1108/CFRI-08-2017-0184
کد محصول E9393
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فهرست مطالب مقاله:
Abstract
۱ Introduction
۲ Theoretical correlation between volume and stock price fluctuation and presentation of research hypothesis
۳ Empirical test proving the superiorities of volume information for stock price volatility
۴ Conclusions
References

بخشی از متن مقاله:
Abstract

Purpose – In the process of discussing the relationship between volume and price in the stock market, the purpose of this paper is to consider how to take the flow of foreign capital into consideration, to determine whether the inclusion of volume information really contributes to the prediction of the volatility of the stock price. Design/methodology/approach – By comparing the relative advantages and disadvantages of the two main non-parametric methods mainstream, and taking the characteristics of the time series of the volume into consideration, the stochastic volatility with Volume (SV-VOL) model based on the APF-LW simulation method is used in the end, to explore and implement a more efficient estimation algorithm. And the volume is incorporated into the model for submersible quantization, by which the problem of insufficient use of volume information in previous research has been solved, which means that the development of the SV model is realized. Findings – Through the Sequential Monte Carlo (SMC) algorithm, the effective estimation of the SV-VOL model is realized by programming. It is found that the stock market volume information is helpful to the prediction of the volatility of the stock price. The exchange market volume information affects the stock returns and the price-volume relationship, which is achieved indirectly through the net capital into stock market. The current exchange devaluation and fluctuation are not conducive to the restoration and recovery of the stock market. Research limitations/implications – It is still in the exploratory stage that whether the inclusion of volume information really contributes to the prediction of the volatility of the stock price, and how to incorporate the exchange market volume information. This paper tries to determine the information weight of the exchange market volume according to the direct and indirect channels from the perspective of causality. The relevant practices and conclusions need to be tested and perfected. Practical implications – Previous studies have neglected the influence of the information contained in the exchange market volume on the volatility of stock prices. To a certain extent, this research makes a useful supplement to the existing research, especially in the aspects of research problems, research paradigms, research methods and research conclusion. Originality/value – SV model with volume information can not only effectively solve the inefficiency of information use problem contained in volume in traditional practice, but also further improve the estimation accuracy of the model by introducing the exchange market volume information into the model through weighted processing, which is a useful supplement to the existing literature. The SMC algorithm realized by programming is helpful to the further advancement and development of non-parametric algorithms. And this paper has made a useful attempt to determine the weight of the exchange market volume information, and some useful conclusions are drawn.

Introduction

The managed floating exchange rate system has been put into action in China since July 21, 2005. Facing the abnormal fluctuation (represented by abrupt appearance and disappearance of circuit-breaker mechanism) in the stock market at the beginning of 2016 and under the background that RMB has showed the depreciation trend upon being added to SDR, it is essential to delve deeper into the issue whether the stock market fluctuation is buffered to some extent as a result of capital control for its restriction of capital flight, or aggravated for the gambling operation of the foregoing capital in the stock market. When exploring the stock price-volume relationship in the stock market, this dissertation makes tentative efforts to take the intention or strength of capital flight into consideration. In the foreign exchange market, capital flight will lead to the supply demand change of RMB and eventually demonstrate as an important factor of exchange rate fluctuation. Based on the analytical framework of stock price-volume relationship, the spot inquiry of financial institutions can represent more directly the intention and strength of capital flight in the foreign exchange market. With this, the spot inquiry volume of foreign exchange, as the direct representation, ranks to be a more targeted, direct and effective proxy variable compared with the exchange rate volatility. Therefore, this dissertation attempts to judge the forecast function of volume on stock price fluctuation by integrating foreign exchange volume information into the analytical framework of stock price-volume relationship, and to identify the external effect of capital control on stock market volatility, so as to provide experience reference for the existing policy adjustment in Chinese stock and foreign exchange market by virtue of research design and conclusions.

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