摘要：
This paper uses the downside realized semi variance to measure the downside risk and then the HAR-DR, HAR-DR-V and HAR-DR-DV models on the basis of the HAR-RV model are built. Finally, by comparing the three models' prediction ability for downside risk in the stock spot market and futures market, we test whether the trading volume and downside trading volume of the two markets can be used to predict the downside risk. And we also study the differences under different samples and different models. The results indicate that trading volume and downside trading volume have different prediction effects for the downside risk in different periods. The trading volume and downside trading volume exhibit much forecasting power in the futures market. However, they show little forecasting power in the spot market.
摘要：
<jats:p>The extreme return and extreme volatility have great influences on the
investor sentiment in stock market. However, few researchers have taken the
phenomenon into consideration. In this paper, we first distinguish the
extreme situations from non-extreme situations. Then we use the ordinary
generalized least squares and quantile regression methods to estimate a
linear regression model by applying the standardized AAII, the return and
volatility of SP 500. The results indicate that, except for extremely
negative return, other return sequences can cause great changes in investor
sentiment, and non-extreme return plays a leading role in affecting the
overall American investor sentiment. Extremely positive (negative) return can
rapidly improve (further reduce) the level of investor sentiment when
investors encounter extremely pessimistic situations. The impact gradually
decreases with improvement of the sentiment until the situation turns
optimistic. In addition, we find that extreme and non-extreme volatility
cannot a_ect the overall investor sentiment.</jats:p>
作者机构：
[文凤华; 龚旭; 杨鑫] Business School, Central South University, Changsha, China;[杨晓光; 黄创霞] Key Laboratory of Management Decision and Information Systems, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China;[杨晓光; 黄创霞] School of Economics, Changsha University of Science and Technology, Changsha, China
摘要：
This paper, using the singular spectrum analysis (SSA), decomposes the stock price into terms of the trend, the market fluctuation, and the noise with different economic features over different time horizons, and then introduce these features into the support vector machine (SVM) to make price predictions. The empirical evidence shows that, compared with the SVM without these price features, the combination predictive methods-the EEMD-SVM and the SSA-SVM, which combine the price features into the SVMs perform better, with the best prediction to the SSA-SVM. (C) 2014 Published by Elsevier B.V. Open access under CC BY-NC-ND license.
摘要：
In order to research the situation of the stock market extreme gains and extreme volatility how to have great influence on investor sentiment. This article selects the S&P 500 weekly closing price of American market and extracts yield and volatility sequences. Linear regression model is established on the basis of the difference between extreme and not extreme case to study the emotional change brought by extreme income and extreme volatility. The empirical results show: Except for the extreme negative earnings, other yield sequence can significantly stir up investor's mood, among which the not extreme gains place the first in causing the investor's emotional change in the United States; Extreme positive yield have more significant effect on investor sentiment than extreme negative yield; Volatility cannot affect all investor's sentiment effectively and steadily, thus it has limited explanation on investor sentiment.
作者机构：
[He, Ting] Changsha Univ Sci & Technol, Sch Econ & Management, Changsha 410076, Hunan, Peoples R China.;[Wen, Fenghua] Cent S Univ, Sch Business, Changsha 410083, Peoples R China.
会议名称：
International Conference on Industrial Engineering and Management Science (ICIEMS)
会议时间：
SEP 28-29, 2013
会议地点：
Shanghai, PEOPLES R CHINA
会议主办单位：
[He, Ting] Changsha Univ Sci & Technol, Sch Econ & Management, Changsha 410076, Hunan, Peoples R China.^[Wen, Fenghua] Cent S Univ, Sch Business, Changsha 410083, Peoples R China.
会议论文集名称：
Proceedings of 2013 International Conference on Industrial Engineering and Management Science(ICIEMS 2013)
摘要：
Dividend policy is the important content of modern company financial activity. Under the framework of behavioral corporate finance, this paper firstly through principal component analysis to synthesiz
作者机构：
[Ma, Xin] Changsha Univ Sci & Technol, Coll Econ & Management, Changsha 410076, Hunan, Peoples R China.;[Wen, Fenghua] Cent S Univ, Coll Business, Changsha, Hunan 410083, Peoples R China.
会议名称：
International Conference on Industrial Engineering and Management Science (ICIEMS)
会议时间：
SEP 28-29, 2013
会议地点：
Shanghai, PEOPLES R CHINA
会议主办单位：
[Ma, Xin] Changsha Univ Sci & Technol, Coll Econ & Management, Changsha 410076, Hunan, Peoples R China.^[Wen, Fenghua] Cent S Univ, Coll Business, Changsha, Hunan 410083, Peoples R China.
会议论文集名称：
Proceedings of 2013 International Conference on Industrial Engineering and Management Science(ICIEMS 2013)
摘要：
From the perspective of earning quality, financial characteristics and market microstructure, this paper tend to compose new information asymmetry index by utilizing the method of principal component
摘要：
This paper builds a GARCHC-M model to explore the effect of the gain or loss on investors’ risk attitudes on the basis of the previous studies of time-varying risk compensation. Then we introduce the risk attitude in GARCHS model's skewness equation and develop a GARCHCS-M model to study its effect on the return skewness. The data of composite indexes of stocks whose market values rank the top ten among the global stock exchanges in 2011 are used to make an empirical study. Results show that investors’ risk attitudes are affected by current gains or losses and investors risk aversion improves with increasing gains and decreases with increasing losses. At the same time, investors’ risk attitudes affect skewness of return distribution; their risk aversion decrease the return skewness while risk seeking increase the return skewness.
期刊：
Applied Mathematics and Computation,2012年218(15):7747-7758 ISSN：0096-3003
通讯作者：
Zhang, Guo-Wei
作者机构：
[Wang, Zhi-Gang; Zhang, Guo-Wei] Anyang Normal Univ, Sch Math & Stat, Anyang 455002, Henan, Peoples R China.;[Wen, Feng-Hua] Changsha Univ Sci & Technol, Sch Econometr & Management, Changsha 410114, Hunan, Peoples R China.
通讯机构：
[Zhang, Guo-Wei] A;Anyang Normal Univ, Sch Math & Stat, Anyang 455002, Henan, Peoples R China.
关键词：
Analytic functions;Differential subordination;Hadamard product (or convolution);Srivastava-Khairnar-More integral operator
摘要：
In the present paper, we derive various properties and characteristics of the Srivastava-Khairnar-More integral operator. Such results as inclusion relationships, integral preserving properties, inequality properties, convolution properties, subordination and superordination properties, and sandwich-type results are obtained. Relevant connections of the results presented here with those obtained in earlier works are also pointed out. Crown Copyright (c) 2012 Published by Elsevier Inc. All rights reserved.
通讯机构：
[Shaw, David] U;Univ Calgary, Haskayne Sch Business, Scurfield Hall,2500 Univ Dr NW, Calgary, AB T2N 1N4, Canada.
关键词：
Fractals;Chaos;R/S Analysis Method;Reconstruction of Phase Space
摘要：
The Hurst exponent derived by the R/S analysis method of Shanghai stock market's logarithmic return series is about 0.6298. This shows that the Shanghai stock market exhibits fractal features, and a long memory cycle of about one-and-a-half years. With the reconstruction of phase space, the Shanghai Stock attractor dimension converges to 1.335, which means that the Shanghai stock market has chaotic features, and constructing a dynamic system of the Shanghai stock market needs at least two variables. The findings from the principal component analysis support the conclusion of the existence of chaotic features of the Shanghai stock market. The fractal and chaotic features of the Shanghai stock market reveal the nonlinear properties of the Chinese stock market, and the nonlinearity perspective will be more conducive to the formulation of countermeasures for the development of the Chinese stock market.
摘要：
Beside the influence of information flow on stock price volatility, to study whether disposition effect, a kind of investor's different decision-making behavior, also has some important influence on stock price volatility, this paper introduces capital gains overhang to GARCH-V model and establishes GARCH-V-G Model, chooses stock index on developed market and emerging market respectively as samples and makes a comparative empirical study. The results show the capital gains overhang is negatively related to price fluctuation on stock markets, which means investors with capital gains weaken the price volatility while with capital losses intensify the volatility. Moreover, the capital gains overhang can explain to some extent the persistence of stock price volatility, and the disposition effect shown by investors on emerging markets can explain better and affect greater the continual volatility than that on developed markets.
