This paper is concerned with the existence of mild solutions for a class of impulsive fractional partial semilinear differential equations. Some errors in Mophou (2010)
2 are corrected, and some ...previous results are generalized.
With the outbreak of COVID-19 in Wuhan, aggressive countermeasures have been taken, including the implementation of the unprecedented lockdown of the city, which will necessarily cause huge economic ...losses for the city of Wuhan. In this paper, we attempt to uncover the interactions between epidemic prevention and control measures and economic-social development by estimating the health loss and meso-economic loss from a human-oriented perspective. We implemented a compartmental model for the transmission dynamics and health burden assessment to evaluate the health losses, then estimated the direct and indirect economic losses of industries using the Input-Output model. Based on these estimates, the first monthly health losses and meso-economic losses caused by the lockdown was assessed. The overall policy effect of the lockdown policy in Wuhan was also investigated. The health loss and meso-economic losses are used to evaluate the health burden and loss of residents’ mental health, the direct economic loss of several worst-hit industries, and the indirect economic loss of all industries, respectively. Our findings reveal that the health burden caused by this pandemic is estimated to be 4.4899 billion yuan (CNY), and the loss of residents’ mental health is evaluated to be 114.545 billion yuan, the direct economic losses in transport, logistics, and warehousing, postal service, food, and beverage service industries reach 21.6094 billion yuan, and the monthly indirect economic losses of all industries are 36.39661994 billion yuan caused by the lockdown. The total monthly economic losses during the lockdown reach 177.0413 billion yuan. However, the lockdown policy has been considered to reduce COVID-19 infections by >180 thousand, which saves about 20 thousand lives, as well as nearly 30 billion yuan on medical costs. Therefore, the lockdown policy in Wuhan has obvious long-term benefits on the society and the total economic losses will be at a controllable level if effective measures are taken to combat COVID-19.
•We apply the method of rolling sample testing and the GARCH model to investigate the day–of–the–week anomalies in stock returns of 28 indices in major emerging and developed stock markets in the ...world.•We find out that the day–of–the–week effects exist in both emerging and developed stock markets.•We propose a single number to quantify the calendar effects performance.•The conclusions based on both t–values and the calendar effect performance ratios are consistent.
This paper applies the method of rolling sample test and the GARCH model to investigate the day-of-the-week anomalies in stock returns of main indices in 28 markets from 25 countries over the world. We propose the calendar effect performance ratio to measure the significance of day-of-the-week anomalies in this paper. Our study demonstrates that the Monday anomalies are prominent in SZC11meanings of symbols are given in Table 1 in the Appendices, DOW, MERVAL, WIG20, FTSEMIB and STI index; the Tuesday anomalies are prominent in SPX, SPXT; the Wednesday anomalies are prominent in MEXBOL, JCI, DAX, SMI, AS51, NKY and NZSE50FG; the Thursday anomalies are prominent in SMEC, PX and PCOMP; the Friday anomalies are prominent in IBOV, IPSA, RTSI$, XU100, SENSEX, FBMKLCI, IBEX, and HSI index. We also investigate calendar effects for 6 stock market indices measured in US dollars and still find the calendar effect phenomena for these selected indices when they are in US dollars. The findings in this paper will be valuable to both the academia and practitioners.
In this paper, we use Conditional Value-at-Risk (CVaR) to measure risk and adopt the methodology of nonparametric estimation to explore the mean–CVaR portfolio selection problem. First, we obtain the ...estimated calculation formula of CVaR by using the nonparametric estimation of the density of the loss function, and formulate two nonparametric mean–CVaR portfolio selection models based on two methods of bandwidth selection. Second, in both cases when short-selling is allowed and forbidden, we prove that the two nonparametric mean–CVaR models are convex optimization problems. Third, we show that when CVaR is solved for, the corresponding VaR can also be obtained as a by-product. Finally, we present a numerical example with Monte Carlo simulations to demonstrate the usefulness and effectiveness of our results, and compare our nonparametric method with the popular linear programming method.
Accurate stock price prediction has an important role in stock investment. Because stock price data are characterized by high frequency, nonlinearity, and long memory, predicting stock prices ...precisely is challenging. Various forecasting methods have been proposed, from classical time series methods to machine-learning-based methods, such as random forest (RF), recurrent neural network (RNN), convolutional neural network (CNN), Long Short-Term Memory (LSTM) neural networks and their variants, etc. Each method can reach a certain level of accuracy but also has its limitations. In this paper, a CNN-BiLSTM-Attention-based model is proposed to boost the accuracy of predicting stock prices and indices. First, the temporal features of sequence data are extracted using a convolutional neural network (CNN) and bi-directional long and short-term memory (BiLSTM) network. Then, an attention mechanism is introduced to fit weight assignments to the information features automatically; and finally, the final prediction results are output through the dense layer. The proposed method was first used to predict the price of the Chinese stock index—the CSI300 index and was found to be more accurate than any of the other three methods—LSTM, CNN-LSTM, CNN-LSTM-Attention. In order to investigate whether the proposed model is robustly effective in predicting stock indices, three other stock indices in China and eight international stock indices were selected to test, and the robust effectiveness of the CNN-BiLSTM-Attention model in predicting stock prices was confirmed. Comparing this method with the LSTM, CNN-LSTM, and CNN-LSTM-Attention models, it is found that the accuracy of stock price prediction is highest using the CNN-BiLSTM-Attention model in almost all cases.
According to the United Nations World Tourism Organization, tourism promotes sustainable economic development. Ensuring tourism safety is an essential prerequisite for its sustainable development. In ...this paper, based on the three evaluation index systems for tourism safety early warning and the collected sample data, we establish three projection pursuit dynamic cluster (PPDC) models by applying group search optimization, a type of swarm intelligence algorithm. Based on case studies, it is confirmed that the results derived from the PPDC models are consistent with the expert judgments. The importance of the evaluation indicators can be sorted and classified according to the obtained optimal projection pursuit vector coefficients, and the tourism risks of the destinations can be ranked according to the sample projection values. Among the three aspects influencing tourism safety in case one, the stability of the tourism destination has the most significant impact, followed by the frequency of disasters. Of the ten evaluation indicators, the frequency of epidemic disease affects tourism safety the most, and the unemployment ratio affects it the second most. Overall, the PPDC model can be adopted for tourism safety early warning with high-dimensional non-linear and non-normal distribution data modeling, as it overcomes the “curse of dimensionality” and the limitations associated with small sample sizes.
This paper aims to measure the impacts of environmental policy uncertainty on green innovation and explore the transmission channel that is less understood in past scientific works. In this paper, we ...use a newspaper-based sentiment mining approach to establish an index of environmental policy uncertainty in China and implement web crawlers and text analysis techniques to construct a network public opinion index of the Chinese financial market. Then, we explore the relationships between environmental policy uncertainty, network public opinion, and green innovation through the time-varying parameter structural vector autoregressive with stochastic volatility (TVP-VAR-SV) model. The transmission channels of environmental policy uncertainty to green innovation are depicted by selecting different timing of policy release. Our empirical study results show that the fluctuations of environmental policy uncertainty, network public opinion, and green innovation have time-varying characteristics. Furthermore, the findings reveal interactions among the three variables: 1) The environmental policy uncertainty can influence green innovation through network public opinion. 2) The environmental policy uncertainty has both inhibited and promoted effects on network public opinion and green innovation. 3) There are differences in the direction and the degree of impulse responses among the above three variables in the context of uncertainty shocks. Besides, managerial relevance and policy implications are also provided for decision-makers facing sustainable development challenges.
This paper considers an uncertain exit time multi-period mean–variance portfolio selection problem with endogenous liabilities in a Markov jump market, where assets and liabilities of the balance ...sheet are simultaneously optimized. The random returns of assets and liabilities depend on the states of the financial market. By applying the Lagrange duality method, the Khatri–Rao matrix product technique and the dynamic programming approach, the explicit expressions for the mean–variance efficient strategy and efficient frontier are derived. In addition, the optimal balance sheet structures in both cases with and without boundary constraints are studied. Moreover, some degenerate cases are discussed, and some results in the literature are recovered as degenerate cases under our setting. Furthermore, a numerical example based on real data from the Chinese stock market is provided to illustrate the results obtained in this paper, and some interesting findings are presented.
The rational allocation and utilization of key corporate resources is the key to the success of collaborative innovation projects. Finding an optimal strategy for the allocation and utilization of ...key resources is of great significance for promoting the smooth progress of cooperative both innovation parties and increasing project returns. Therefore, from the perspective of the repeated games of the project participants, this article studies the optimal allocation and utilization of key resources of the enterprise in collaborative innovation projects. In this study, nine scenarios and eighteen strategic combinations of resources allocation and utilization by collaborative innovation partners are explored. Explicit expressions for the components of sixteen equilibrium points in terms of parameters are derived. Among these equilibrium points, four stable solutions are determined. These stable solutions correspond to the optimal strategies for enterprises allocating key resources and A&R parties to use these resources in different scenarios, and these strategies enable partners to maximize their interests. On this basis, some suggestions are put forward to promote cooperation and improve project performance.
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