scholarly journals Research on the Prediction of A-Share “High Stock Dividend” Phenomenon—A Feature Adaptive Improved Multi-Layers Ensemble Model

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 416
Author(s):  
Yi Fu ◽  
Bingwen Li ◽  
Jinshi Zhao ◽  
Qianwen Bi

Since the “high stock dividend” of A-share companies in China often leads to the short-term stock price increase, this phenomenon’s prediction has been widely concerned by academia and industry. In this study, a new multi-layer stacking ensemble algorithm is proposed. Unlike the classic stacking ensemble algorithm that focused on the differentiation of base models, this paper used the equal weight comprehensive feature evaluation method to select features before predicting the base model and used a genetic algorithm to match the optimal feature subset for each base model. After the base model’s output prediction, the LightGBM (LGB) model was added to the algorithm as a secondary information extraction layer. Finally, the algorithm inputs the extracted information into the Logistic Regression (LR) model to complete the prediction of the “high stock dividend” phenomenon. Using the A-share market data from 2010 to 2019 for simulation and evaluation, the proposed model improves the AUC (Area Under Curve) and F1 score by 0.173 and 0.303, respectively, compared to the baseline model. The prediction results shed light on event-driven investment strategies.

2020 ◽  
pp. 0148558X2098021
Author(s):  
Nan-Ting Kuo ◽  
Cheng-Few Lee

This study explores the value of the tax deferral option. By examining ex-day stock-price-change ratios for taxable stock dividends in Taiwan, we find that the tax deferral option is valuable to investors. For a $1 taxable stock dividend, the tax deferral option produces 33.9 ¢ in tax savings, which suggests a tax deferral parameter of 11.3%. We also find that stocks with the tax deferral option have higher trading volumes around ex-days than those without this option, and that higher investor-level tax rates lead to higher value of the tax deferral option. We contribute to the literature by cleanly determining the value of the tax deferral option; our result is not confounded by the restart option.


2019 ◽  
Vol 13 (3) ◽  
pp. 574-602 ◽  
Author(s):  
Yixi Ning ◽  
Gubo Xu ◽  
Ziwu Long

Purpose This study aims to examine the venture capital (VC) industry in China. It has demonstrated a history of high growth with significant variations over time. The authors have examined the trends and determinants of VC investments in China over a 20-year period from 1995 to 2014. They find that the aggregate amount of VC investments, the total number of venture deals and the average amount of venture investments per deal in China are all significantly impacted by macroeconomic conditions (i.e. GDP, export, money supply), technology innovations and financial market indicators (i.e. initial public offerings (IPOs), interest rate, price-to-earnings ratio, etc.). They also find that the 2007 China A-Share stock market crash and the subsequent global financial crisis have motivated VCists in China to adjust their investment strategies and risk levels by allocating more capital to later-stage investments and securing more deals with later-round financings. However, after the 2008 global financial crisis, the China’s venture industry has recovered faster compared to the US counterpart response. Design/methodology/approach The authors first perform trend analysis of VC investments at an aggregate level, by stages of development, and across industry from 1995 to 2014.To test H1 and H2, the authors use multiple regression models with lagged explanatory variables. To test H3, the authors use univariate tests to compare the measures of VC investments at an aggregate level, stage funds ratios, stage deals ratios and financing series ratios during both a five-year and seven-year time windows around the 2007 A-Share stock market crash and the subsequent financial crisis. Findings The development of the VC industry in China has demonstrated a history of high growth with significant variation over time. The authors find that the aggregate amount of VC investments, the total number of venture deals and the average amount of venture investments per deal in China are all significantly impacted by macroeconomic conditions (i.e. GDP, export, money supply), technology innovations and financial market indicators (i.e. IPOs, interest rate, price-to-earnings ratio, etc.). The authors also find that the 2007 China A-Share stock market crash and the subsequent global financial crisis have motivated VCists in China to adjust their investment strategies and risk by allocating more capital to later-stage investments and securing more deals with later-round financings. However, the China VC industry has recovered faster compared to the USA just after the 2008 global financial crisis. Research limitations/implications There are also limitations in the study. The VC data in China in the earlier 1990s might not be very reliable due to the quality of statistics. Therefore, the trend analysis and discussions mainly focus on the time after 2000. Also, the authors cannot find VC financing sequence data for the analysis. Second, there is no doubt that the policy impact from Chinese transforming economic system and government policies on its VC industry is substantial (Su and Wang, 2013). However, they cannot find an appropriate variable to be included in the empirical models to consider this effect. Further study on this area would provide meaningful information. Third, although the authors have done comparison study between the VC industry in China in this study and the VC industry in the US documented in Ning et al. (2015) and discussed some interesting findings, more in-depth research in this area will be very useful. Practical implications The findings have meaningful implications for VCists and start-up companies seeking equity financings in China. VCists should closely monitor macroeconomic and market conditions to make appropriate adjustments to their risk and investment strategies. Entrepreneurs seeking equity financings for their business could also monitor the identified macroeconomic and market indicators, which can help them with their timing and to negotiate a better equity financing deal. VC financing is more likely to succeed when key macroeconomic and market indicators become favorable. Originality/value This paper contributes to the literature by testing the supply and demand theory on the VC market proposed by Poterba (1989) and Gompers and Lerner (1998) from the macroeconomic perspective using 20 years’ VC data from China. The authors also examine how the 2007 A-Share stock market crash and the subsequent financial crisis affected VCists to adjust their risk levels and investment strategies. It provides useful information for international academia and policymakers to understand the quick rise of China VC industry. The authors also find that the macroeconomic drivers of VC industry are somewhat different under different economic systems.


Author(s):  
Howard Moskowitz ◽  
Edgar Baum ◽  
Stephen D Rappaport ◽  
Attila Gere

Respondents estimated the price of a share of stock for a company, based upon a set of short vignettes, one estimate for each vignette. The vignettes comprised 2-4 elements-statements selected from four groups: WHO presents the information, the companys VALUES, how the presenter shows ALIGNMENT with company values, and how CUSTOMERS respond. The linkage between expected dollar value of the stock and message was highest for the element talking about positive customer reviews. The respondents divide into two groups or mind-sets, based upon their patterns of response to the elements. Mind-Set 1 estimates stock price based on messages communicating good governance. Mind-Set 2 estimates stock price based on messages communicating customer intimacy and excitement.


PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249900
Author(s):  
Xiaohua Zhou ◽  
Jinshi Wan ◽  
Yi Yang ◽  
Xiangyu Gan

This paper expands the previous research on management equity incentives (MEIs) and stock price crash risk by distinguishing between the "gold watch" region and the "golden handcuff" regions in MEIs. By using an estimation of the gold watch region and the golden handcuff regions based on 6,675 annual observations of China’s A-share listed companies, the stock price crash risk is found to be negatively correlated with MEIs in the golden handcuff regions (0–10%, 30%-100%) and is positively correlated with MEIs in the gold watch region (10%-30%). A further investigation of the mediating effects of peer effects on MEIs and the stock price crash risk reveals that peer effects have a partial mediation effect at the level of peer managers’ shareholding and mediate the relationship between MEIs and the stock price crash risk.


Author(s):  
Inta Bruna ◽  
Inta Millere

The valuation of an entity in off-exchange transactions involves the use of different techniques. Nevertheless, none of them guarantees the most accurate result. Therefore, it is very difficult to choose one evaluation method. Both investors, corporate managers, financial professionals, portfolio managers, and securities analysts should have a basic understanding of the process of evaluating companies. To that end, professionals recommend evaluating a company’s financial reports to detect its financial position and solvency. According to the methods of financial analysis, working capital is one of the solvency ratios, which describes the value of resources that remain after the company’s current liabilities have been bared. The research study is aimed at determining the impact of changes in working capital on the valuation of a company. In order to achieve the aim and confirm or deny the hypothesis, the methodological basis for the research study was developed, necessary information was collected, calculations were performed using data from companies listed on Nasdaq OMX Riga, and the obtained results were analysed. Literature review and economic and statistical analysis, including the SPSS method for assessing the effects of working capital and stock price, were used in the research.


1994 ◽  
Vol 2 (1) ◽  
pp. 43-59 ◽  
Author(s):  
Manjeet S. Dhatt ◽  
Yong H. Kim ◽  
Sandip Mukherji

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Binghui Wu ◽  
Yuanman Cai ◽  
Mengjiao Zhang

This paper uses the partial least squares method to construct the investor sentiment index in Chinese stock market. The Shanghai Stock Exchange 180 Index and the Shenzhen Stock Exchange 100 Index are used as samples. From the perspectives of holistic sentiment and heterogeneous sentiment, this paper studies the impact of investor sentiment on stock price crash risk. The results show that investor sentiment can significantly affect stock price crash risk in Shanghai and Shenzhen A-share markets, especially in the Shenzhen A-share market no matter from which perspective. And investor pessimism has a greater impact on stock price crash risk in the Shenzhen A-share market from the perspective of heterogeneous sentiment. Compared with the available researches, this paper makes two contributions: (i) the comparative analysis is adopted to discuss the differences between Shanghai and Shenzhen A-share markets, abandoning the research approach that takes the two markets as a whole in existing literature, and (ii) this paper not only studies the impact of investor holistic sentiment on stock price crash risk from a macro perspective, but also adds a more micro heterogeneous sentiment and conducts a comparative analysis.


Author(s):  
Weiyi Xia ◽  
Zhouyang Ren ◽  
Hui Li ◽  
Bo Hu

AbstractFluctuation evaluation is an important task in promoting the accommodation of photovoltaic (PV) power generation. This paper proposes an evaluation method to quantify the power fluctuation of PV plants. This consists of an index system and a ranking method based on the RankBoost algorithm. Eleven indices are devised and included in the index system to fully cover diverse fluctuation features. By handling missing and invalid data effectively, the ranking method fuses multiple indices automatically and provides a systematic and comprehensive comparison of power fluctuation. Simulation results based on power data from six PV plants indicate that the evaluation list obtained by the RankBoost ranking method is better represented and more comprehensive than that derived by the equal weight method.


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