bluuebunny/crossref_metadata_2025 huggingface dataset:
REDUÇÃO DA MORTALIDADE INFANTIL
Authors: Nunes Duarte Tatyana , Cosme Rodrigues Vanuza , De Assis Dantas Ianny , Fernandes Barbosa Itatiaia , Lopes Goes Sibele , Lima de Menezes Maria das Candeia
Published: October 2022

O município de Jaguaribe teve um aumento da taxa de mortalidade infantil de 17,86 em 2016 para 22,17 em 2020, diferente da tendência da redução do Brasil e do Ceará. A maioria dos óbitos eram por causas evitáveis fazendo-se necessárias estratégias sustentáveis para sua redução. Assim objetiva-se reduzir a mortalidade infantil em Jaguaribe em 2021. Foram realizadas várias estratégias entre as quais menciona-se:  O monitoramento das gestantes, capacitação da equipe multidisciplinar, implementação de fluxos para pré-natal e parto de alto risco, fortalecimento da busca ativa e visita domiciliar, regulação de gestantes em tempo oportuno e implantação da Comissão de Óbito materno, infantil e fetal no município.  Em 2021 aconteceram 02 óbitos infantis no município, o que representa uma taxa de 4,84, menor taxa registrada nos últimos 10 anos. Percebe-se o envolvimento de todos os profissionais de saúde dos pontos de atenção da rede de saúde atuando com objetivo comum.
TRATAMENTO HOMEOPÁTICO COMO ABORDAGEM PARA DIABETES E HIPERTENSÃO
Authors: Moura Brandão Isabel Cristina , Vasconcelos Evaldo Eufrásio , Furlani Emílio Carlos , Barros Ana Fabrina Bezerra
Published: October 2022

Este artigo objetiva apresentar a experiência de um município cearense quanto ao tratamento homeopático, como nova abordagem para casos de diabetes e hipertensão, com vistas à redução no impacto dos indicadores municipal das doenças e melhoria da qualidade de vida dos usuários. Foi conduzido com a utilização do critério de inclusão: morar na área da equipe, ser hipertenso e/ou diabético; e para critério de exclusão: desinteresse em fazer o tratamento homeopático. Resultou na equipe de Caiçara uma população com o menor percentual de diabéticos e hipertensos do município. No período final desta prática (agosto a novembro de 2021), identificou-se 4,44% desta população com diabetes e 7,91% com hipertensão, além de ser a que menos utiliza medicamentos para essas patologias. Conclui-se que nessa população foi possível observar evidentes vantagens no tratamento, melhores resultados nos indicadores de saúde, como também redução no consumo de medicamentos convencionais para tratamento de diabetes e hipertensão.
Carbon pricing factors: Perspective from demand and supply sides
Authors: Sun Liwen
Published: October 2022

Currently, global warming became a world focus as its potential impacts on all human beings. To prevent the damages of greenhouse gas emissions, the carbon market established and operated for several years. In this paper, due to an important financial reality that the carbon market should be regarded as a common financial market, this paper briefly reviews the pricing factors of the novel carbon asset to benefit the market when it is time to price the carbon asset. And finally, this paper points out the potential future investigations.
A Study of Optimal Portfolio of Gold and Bitcoin Based on Risk and Return
Authors: Zhang Yan , Zhang Hongwei , Ma Yu
Published: October 2022

Recently, Digital money is booming, and bitcoin shows potential in the field of investment as a representative of digital currency. According to modern portfolio theory, most of the investors are absolute risk-averter, and a diversified portfolio can effectively reduce the risk. So investors usually combine bitcoin with other assets to reduce non-systemic risks. Therefore, it is of great importance to formulate a feasible portfolio that can make steady returns for investors. For this reason, we build models to find suitable strategy to quantify the proportion of assets invested so that investors can make optimal investment decisions. We measure the return, risk, and efficiency of risk model’s portfolio by sharpe ratio. And based on DEA method, the multi-stage portfolio with V-type transaction cost is evaluated by comparing the portfolio from risk model with the portfolio by applying DEA method, and finally we prove that the strategy is the optimal one. Finally, the advantages and disadvantages of this model are analyzed and summarized.
In depth analysis of Fisher model and explore its limitation
Authors: Yan Ruichen
Published: October 2022

This paper shows how people develop the concept of time value of money or the interest rate in the financial market model, how to derive individual savings decisions from corporate investment decisions, and why the net present value rule applies to decision-making. Specifically analyze the relationship between capital market line and Fisher model. And based on the Chinese stock market to further study the Fisher model and show its role.
Using linear regression model to investigate the relationship between people's average expenditure on food consumption and GDP per capita in China under pandemic across cities
Authors: Zhang Zhuoyu
Published: October 2022

The Food and Beverage (F&B) industry in China has always been a hot industry and it has experienced a continuing rise in revenue across years before the pandemic hits China’s cities. Given the large scale of the industry, its performance is closely related to people’s everyday lives. However, ever since China entered the pandemic and placed restrictions on citizens’ mobility, significant drops in the revenue have been seen in the F&B industry. A considerable number of physical restaurants had to close, and people’s food consumption has been largely affected. Moreover, in view of the different population size of provinces, it is also important to analyse the relationship between average expenditure on food consumption and GDP per capita across time.  Therefore, it is important to analyse the factors related to the F&B industry and to understand the extent of damage on the F&B industry by the pandemic. In this paper, we recognized the large extent of damage and measured it using the linear regression model, after proving the strong linear correlation between F&B industry revenue and the GDP of the city. We also analysed the linear relationship between average expenditure on food consumption and GDP per capita. The Analysis of Covariance Test is used to measure the closeness of this relationship between the years 2019 and 2020. Due to the complexity of the F&B industry, we considered another possible factor; the average age of the workforce, and introduced the multiple linear regression model.
The impact of COVID-19 on Fresh food e-commerce in China
Authors: Zhong Wenrui
Published: October 2022

The COVID-19 pandemic has brought about varieties of changes in human beings’ lifestyles, including shaping consumer’s behavior. In this paper, fresh food industry was taken as an example to test whether there is a significant change in fresh food e-commerce under the epidemic from the perspective of the whole industry. Afterwards, from the perspective of consumers, structural equation model was used to analyze the influencing factors and paths of such a change. On this basis, this paper can not only effectively analyze the trend of fresh e-commerce, but also put forward suggestions for the fresh industry to attract consumers more efficiently. These results shed light on guiding further exploration of the impact of COVID-19 on different industries.
Carbon financial price forecasting based on VMD noise reduction and improved DELM optimized by the WDO algorithm
Authors: Fan Jingying , Chen Jiayin , Li Haoxuan
Published: October 2022

Carbon price forecasting can help stabilize the carbon pricing mechanism and reduce carbon market risks. This paper firstly uses the closing price of the Guangzhou carbon exchange to predict carbon prices. Secondly, this paper constructs model based on a wind-driven algorithm (WDO) and deep extreme learning machine (DELM), compared with the results of a backpropagation neural network (BP). The prediction results are reliable, with a 49.81% decrease in mean square error (MSE), which shows that the validity of the hybrid VMD-DELM approach is verified.
Development and application of investment prediction model based on gold and bitcoin
Authors: Wang Xuanwu , Zheng Sirun
Published: October 2022

How to predict the change trend of asset prices in the future and decide different operation modes in advance to obtain the maximum benefits is the concern of investors. Taking gold and bitcoin as examples, this paper develops an appropriate mathematical model that uses only the past daily price stream to help traders determine whether to buy, hold or sell assets in their portfolio every day. At the same time, the robustness of the model is analyzed by robustness. The study found that holding US $1000 on September 11, 2016 will eventually maximize profits on September 10, 2021.
Measurement and Influencing Factors Analysis of Regional Carbon Finance Development Level in China Based on ANN-RBF
Authors: Liu Zhaojun , Ma Yongqin
Published: October 2022

The green development of carbon finance contributes to the rapid realization of the "double carbon strategy" goal. This paper uses the analytic hierarchy process-coefficient of variation (AHP-CVM) coupling method to measure the level of carbon finance development in China’s provinces from 2018 to 2020, and uses the artificial neural network-radial basis function (ANN-RBF) method to analyze the influence of different factors on the level of carbon finance development. The results show that the development of regional carbon finance in China is affected by the new coronavirus. However, the overall trend is still rising, and there are differences in the development level of carbon finance between regions. From the perspective of influencing factors, carbon loan intensity, the proportion of added value of financial industry, the proportion of scientific research funds and the contribution rate of scientific and technological progress contribute greatly to the development of carbon finance, among which the intensity of carbon loans has the most prominent influence.
Research on trading strategies based on time series - taking gold and bitcoin as examples
Authors: Zheng Feiyang , Chi Hao
Published: October 2022

In response to the problem of how to optimally invest in gold and bitcoin, this paper establishes a daily trading strategy model, and uses a large amount of price data to conduct in-depth research on how to conduct optimal transactions to obtain maximum value. Based on the daily prices of gold and bitcoin within 5 years, we first build an ARIMA time series forecast model, and use MATLAB programming to solve the forecast results to get the next day's gold and bitcoin prices. Using this prediction result, we established a daily trading strategy model, and used recursion to find the daily trading strategy and the gains obtained in turn. The application of the model will help financial practitioners to analyze and guide the investment of related products.
Research on the Optimal Asset Allocation Decision of Chinese Retirees from the Perspective of Health
Authors: Li Busheng , Li Qi , Wu Yidan , Chen Haiyue , Zhang Zehang
Published: October 2022

This paper constructs an optimal asset allocation decision model for retirees based on the characterization of the CRRA utility function and health stock, and uses the Ramsey equation to obtain the optimal intertemporal asset allocation under steady-state conditions. Combining with the actual situation of Chinese retirees, the theoretical model is numerically simulated and analyzed. The results show that different health shock intensities lead to different asset allocation decisions. Based on the research results, this paper puts forward relevant suggestions on how to make optimal asset allocation decisions for retirees and how the government formulates social policies to cope with the aging society.
Empirical Evidence Based on Geographic Regression Discontinuity Analysis of Housing in Guangzhou School District
Authors: Ouyang Yulu , Sun Keyue
Published: October 2022

In recent years, the "school district housing boom" has become a general concern as it disrupted the housing market, undermining educational equity and class mobility. In view of the real problem of housing premium in school districts, this paper selects the housing data of primary school districts in Guangzhou as a research sample, quantifies it and discusses the impact of education supply on it, so as to provide references and suggestions for subsequent policy introduction. The main research conclusions of this paper are as follows: There is a premium for housing in Guangzhou’s school districts. After excluding the influence of location and physical factors, it is calculated that the housing price from Longdong School District to Yongping School District has increased by about 42.3%.
Analysis and Research on Internal Factors of Stock Price Fluctuation of Chinese Listed Companies Based on ANN-BRF Model
Authors: Chang Yilin , Wang Mingyuan , Yu Zejie
Published: October 2022

Affected by the new corona epidemic, China ' s stock market fluctuates frequently, and stock price fluctuations lead to obstacles to corporate financing, which is not conducive to establishing a good corporate image. In order to provide ideas for enterprises to stabilize the stock price, this paper establishes the influence of internal financial factors on the stock price fluctuation of listed companies based on the artificial neural network-radial basis function (ANN-RBF) model. Based on grounded theory, this paper constructs an index system of stock price fluctuation factors, including 14 indicators from four aspects from the perspective of internal enterprises. Based on the financial data of the Lingnan Pharmaceutical Industry from 2008 to the third quarter of 2021, this paper integrates the financial index system into ANN to explore the impact of corporate financial indicators on stock prices. The results show that net asset growth rate (0.87), retained earnings (0.68) and speed ratio (0.929) are the leading financial indicators affecting stock prices. In addition, this paper helps to study the accuracy of RBF neural network in predicting stock prices of listed companies.
Stock market price prediction model based on grey prediction and ARIMA
Authors: Yang Ruoqi , Deng Yichao , Zhong Qiao , Zong Shouxin
Published: October 2022

Nowadays more and more people like to invest in volatile assets, and it is the goal of every market trader to maximize the total return by developing a reasonable investment strategy. We first predicted the daily value of gold and bitcoin for five years based on known data, we built two models, one is Improved Metabolic Gray Model (Abbreviated as IGM), the other is Time Series Model ARIMA. The application of the model helps investors make investment decisions and improve economic returns.
Investor Sentiment and Stock Returns during the COVID-19 Pandemic: Evidence from Chinese Stock Market
Authors: Liang Weiqi , Sui Jiang , Tian Yufei
Published: October 2022

After decades of development, China's stock market is now at a critical stage of scale expansion. However, China's stock market is dominated by retail investors. Such an immature market is vulnerable to investor sentiment. Based on the current realistic background, this paper studies the relationship between investor sentiment and stock returns in The Chinese market and forecasts the development trend of the future market. This paper firstly combs the literature on investor sentiment at home and abroad and adopts the classical research method of investor sentiment index & principal component analysis. The investor sentiment index was constructed using weekly data of the Shanghai composite index from 2020 to 2021. Select the turnover rate, China SSE 50ETF turnover ratio, closed-end fund discount, Teng Fall Index (TFL) and financing net buying turnover ratio of these five variables to construct. Finally, the multiple linear regression is used to analyze the relationship between investor sentiment and returns. We find that the yield of Shanghai composite index is positively correlated with investor sentiment, which will affect the return of stock market. The significance of this conclusion lies in that it can help to understand the interaction between investor behavior and market activities after the COVID-19 and help to test whether the use of investor sentiment indicators can provide guidance for investors' decisions.
The prediction of financial market based on BP neural network is used to maximize the income of investment
Authors: Xu Tianyi , Meng Yanlong , Bai Yukun
Published: October 2022

In the financial market, investors often buy and sell volatile assets to maximize returns. We can use statistical and mathematical tools, mathematical models and computer technology to trade and get excess return ratio. Firstly, we established a price prediction model based on BP neural network, trained the network through the trading prices of bitcoin and gold before 2016, and then predicted the price of the next day every day from September 11, 2016 to September 10, 2021. Through the comparison with the real value and the horizontal comparison of other models, the prediction effect of this model is good. Then, the programming model is used to maximize the benefits in the next day as the objective function, and the constraints are that the amount after the transaction cannot be negative and there is no gold trading in part of the time. Considering the risk in the final transaction model, the planning model is established to find the optimal investment scheme at this time. Finally, the daily investment plan and the final total value are $3886.8.
A Dual Collaborative Governance based on SFIC Model: a Case Study of the Chinese Film and Television Industry
Authors: Zhou Cuifang
Published: October 2022

The Chinese film and television industry is witnessing the changing relationships  of  its  governance between government and other stakeholders. Understanding the stakeholders and their interactions is critical to an improvement in the performance of collaborative governance regimes. This paper proposes an institutional framework which emphasizes the important role of industry associations as an aid to the government in terms of improving media governance performance. Based on the SFIC collaborative model, we develop a model for a better media governance in the Chinese film and television industry with a design of the five dimensions: starting conditions, catalytic leadership, system design, synergistic process and synergistic effect. By analyzing the governance patterns in the Chinese film and television industry, this paper provides valuable insights into the regulations on Chinese media industries.
Development of Daily Trading Strategies Based on A Quantitative Trading Decision Model
Authors: Shi Guangde , Gao Jingkai , Li Ruibin , Shi Jun
Published: October 2022

Quantitative trading decision models have a key influence on financial investment. Firstly, this study established an LSTM model by using long-term and short-term memory networks and predicted the future prices of gold and bitcoin investment products. Then, according to the time range of gold and bitcoin assets, three types of transactions were determined: cross, non-cross, and inclusion relationship, and the daily trading strategies were determined by the greedy model established by a greedy algorithm. Then, the Sharpe Ratio of the nonparametric method was used to measure the risk of the developed decision model and evaluate the accuracy of the model. Finally, starting from the stock market fluctuation and macro-mobilization, the sensitivity of the decision model under different transaction costs was tested by increasing or decreasing the percentage of transaction costs (0.5%, 1%, 1.5%, and 2%, respectively). Research informs investors on how to invest for the best returns.
Portfolio Construction Based on Bigdata Analysis in Terms of Minimum Variance Model
Authors: Guo Ziyu
Published: October 2022

Contemporarily, A-share market keeps being in a trough, hence investors (especially the retail investors) seek ways to expand profit and reduce loss when speculating in stock market, but sometimes fail because of the lack of knowledge in investment. To remedy this problem, this paper introduces a complete process from the concepts of bigdata analysis to figure out investment decisions, including evaluating single stocks and choosing stocks to construct portfolios. The objectives of portfolio construction used in this paper are minimum variance and maximum Sharpe Ratio. The whole article presents an example of making investment decisions in A-share market. In the particular situation, two best portfolios which minimizes variance and maximizes Sharpe Ratio respectively are constructed among the training of abundant data capacity. It is also observed that with different goal of investment the best choice for investors could be greatly different. Investment strategy given in this paper may be helpful for investors, which offers a guideline for constructing portfolio under some objectives.
Portfolio Analysis of Stocks in Diverse Industries
Authors: Zhang Kaidong
Published: October 2022

Portfolio optimization is a key issue in the current financial field. This paper aims to analyze the asset allocation of technology, financial services, industry, consumer defense and health. This paper selects ten representative company stocks from these five industries, then calculates the characteristic data and randomly assigns weights to them. Then, it uses the formulas of the two most effective models at present - Markowitz model and single index model to calculate the return, standard deviation and sharp ratio respectively, and randomly simulates a large number of data. Then it calculates the CAL curves under the two models, calculates the minimum variance frontier, efficient frontier and inefficient frontier under the five constraints that may be encountered in the actual investment, and draws the corresponding graphs. Finally, it finds out the differences and connections of figures under different constraints and makes a preliminary comparison between the effects of the two models. The results show that: first, there are slight differences in the results of the portfolio solved by the two models; Secondly, the two models can jointly reflect the portfolio characteristics under different constraints. These findings are useful for relevant investors who build portfolios in different industries.
Asset Forecasting Analysis Based on ARIMA Model and BP Neural Network
Authors: Yang Hanyin
Published: October 2022

This paper forecasts the trend of the asset based on historical prices. First, through the establishment of exponential smoothing method, ????????????????????, BP neural network and other models, the trader invest in three assets: gold, bitcoin and cash in USB. The thesis is based on historical price to predict the trend of assets, determine whether traders should purchase, hold or sell and what percentage of the asset, and evaluate its future value. This paper first predicts the future returns and volatility of the two assets. In the initial forecast, the exponential smoothing method and ???????????????????? model are used to predict premiums and future returns. BP neural network is used to predict the future earnings in the middle and late forecast. First, for the first 60 days, we sit tight and wait for the data to accumulate. After 60 days, by looking back at historical data and setting appropriate technical indicators, the secondary trend curve and risk exposure curve of gold and Bitcoin can be obtained respectively. Once we have the curves, the commission, expected rate of return, and volatility of the two markets are combined, we will set up a scoring system to score the daily trading feasibility. Finally, we simulate the transaction, allocate the investment share, get the asset accumulation curve, and complete the decision.
Pricing analysis of Dong Wu Su Yuan Industry based on the pricing model of public REITs
Authors: Xu Yangchen
Published: October 2022

Given that infrastructure public REITs in China are still in the early stage of development, this paper firstly reviews their current status from relevant sources and briefly describes their definitions, development status and main characteristics. The option-adjusted spread method based on Monte Carlo simulation is chosen as the pricing model. The term adjusted spread method needs to consider the interest rate term structure, so the CIR model is used as the interest rate term structure model for interest rate forecasting, and the three CIR parameter values obtained by fitting are brought into the CIR model using Monte Carlo method simulation to obtain 1000 forward interest rate paths, and the spot interest rate is obtained according to the forward interest rate curve path, and the spot interest rate is used to combine with the option adjusted spread OAS to discount the 1000 present values. The average value of the 1000 present values is the pricing result. Comparing the pricing result with the market value, it is found that the two are basically equal. This shows that the option-adjusted spread method based on Monte Carlo simulation can evaluate the value of public REITs more scientifically and reasonably.
Portfolio Design Based on Bigdata Analysis and Sharpe Ratio Optimal model
Authors: Piao Zhirong , Wu Guohua , Zhou Lu
Published: October 2022

Sharpe ratio is a classic index that can comprehensively consider both return and risk. At the same time, it is only used to investigate the asset of the final venture capital portfolio. Therefore, Sharpe ratio is an important research topic in the financial field. This paper is based on big data analysis and minimum variance model. Thereinto, the companies selected in these five industries are AVIC Electrical Systems Co., Ltd., Archer Daniels Midland Company, Bank of America Corporation, Eastman Chemical Company and China XD Plastics Company Limited. Sharpe ratio is a representation of unit risk and return on investment. The greater the Sharpe ratio, the higher the unit risk return of this portfolio. Secondly, the data we use comes from Yahoo Finance, in which we select the year from 2015 to 2021, because the data of these seven years are more accurate. Meanwhile, the tool we use is RStudio, because RStudio is very excellent in graphics and charts. According to the analysis, these results indicate that one can find the portfolio with the highest risk return rate in these seven years. These results shed light on portfolio design based on bigdata analysis in terms of optimal approaches.
The Comparsion of Stock Return Prediction for Random Forest, Ordinary Least Square, and XGBoost
Authors: Wang Junsheng
Published: October 2022

With the stock market growing larger and the violent fluctuation becoming more frequent after the COVID-19 pandemic broke out, investors and researchers urgently need a method to predict the behavior of the stock market accurately. This research is determined to find out the performance of random forest (RF), XGBoost and ordinary least square (OLS) models in terms of predicting the return of given subjects. This research uses tushare to collect data and Jupyter Notebook to run the models. Libraries such as numpy, pandas, scikit-learn, and stockstats are also used in this paper. According to the analysis, XGBoost and RF model outperformed OLS model in all three subjects and the difference between RF and XGBoost model is subtle. Meanwhile, the results also revealed that the choice of subjects may affect the performance of model. Finally, only technical indicators were included in the process of model setup and this may negatively impact the results. These results shed light on the performance difference of the three models and lay a foundation for future high-efficiency hybrid models.
Walt Disney Company 2021 Strategy and Stock Price Analysis
Authors: Niu Hao
Published: October 2022

This article analyses Walt Disney Company's business strategy and stock price. Disney is currently the second largest media and entertainment firm in the world, behind Comcast, and the outbreak of Covid-19 in 2020 has had a constant impact on Disney's corporate growth. We need to investigate Disney's performance as well as strategy throughout this unique period. I utilised Porter five-force analysis, SWOT analysis, and PESTLE analysis to determine and illustrate Disney's strategy. Next, I individually reviewed the financial reports of Disney and its competitors. I divided Disney into two parts, the DMED department compared with Netflix, the DPEP department compared with Universal, and then Disney compared with Comcast as a whole. Furthermore, I analysed and compared Disney's price-earnings ratio and enterprise value ratio to those of Netflix, NBCUniversal, and Comcast, respectively. Finally, I analysed Disney's stock price and projected the company's free cash flow over the next five years. The analysis reveals that Disney will have good business ability in the future and generate revenue in the future. I hope to provide some enlightenment to stakeholders.
Principle, Methodology and Application for Data Cleaning techniques
Authors: Jin Zhexu
Published: October 2022

Con-temporarily, information data has become the cornerstone of every company’s decision-making. In a vast flow of information, choosing the right data is the first step in developing successful predictions. After the determinations of the requirements, analysis purpose and prediction direction, outlier processing, missing value processing and repeated value processing are usually encountered. This paper introduces the limitations, advantages and disadvantages of different methods in application in detail. At the same time, this paper introduces some interpolation methods based on mathematical statistics, such as thermal interpolation, Lagrange interpolation and Newton interpolation. At the same time, it also provides the normal distribution processing method which is better in dealing with outlier problems, and the popular K-nearest neighbor algorithm. Finally, it illustrates the logic diagram of data cleaning in the data preparation stage. Overall, these results offer a guideline for selecting the appropriate treatment in the corresponding situation during data cleaning process.
Analysis of factors Affecting the Development of Fast-Food Industry Based on Machine Learning Methods
Authors: Ji Songpeng , Zhao Yueran
Published: October 2022

Fast food industry is one of the fastest-growing businesses in the world. In this paper, we analyze the development situation of KFC in the Yangtze River delta area (Jiang Su, Zhe Jiang, and Shanghai). According to the analysis of specific data related to the distribution of shops and sales data, we aimed to create the proper strategy for its future development in this zone. We analyze the connection between the number of KFC shops and different classes of cities. We also analyze the relationship between population density and KFC shop distribution by a case. Especially, we use PCA (Principal component analysis) to find the most important influence factors, and the experimental results show that GDP, population with the unit of million, the output value of the second industry are the three key factors affecting the number of KFC outlets. Finally, we analyze the typical features of the Yangtze River delta area.
Asian Options in a Market with High Volatility: Perspective and Evidence from Zoom and Peloton
Authors: Yin Yuxin , Zhang Zejun
Published: October 2022

Contemporarily, uncertainties strongly affect the stock market, especially for the options market that fluctuates dramatically. On this basis, Asian options have become a favorable option for investors due to their low-risk characteristic. In this paper, two recently highly volatile assets, Zoom (ZM) and Peloton (PTON), were selected as investigation targets underlying Asian options. Specifically, both the Black-Scholes method and Monte-Carlo method were applied to price the Asian options for ZM and PTON. Based on calculations with the Black-Scholes formula and simulation with the Monte-Carlo method, we demonstrated that the prices of Asian options are approximately half of the corresponding Vanilla options. Besides, the expected returns are also nearly half of the corresponding Vanilla options. Moreover, according to the comparison between the calculations and simulation, the Black-Scholes formula eventually goes inaccurate while the strike price goes large or less than the original price. However, if the Monte-Carlo method is applied with enough times of simulations, the price of the Asian option will be reflected accurately. Overall, the Asian option is indeed a better choice for prudent investors in a highly volatile market.
The feasibility of arbitrage between TESLA and cryptocurrency
Authors: Gong Yiwen , Zhang Mingtao , Zhang Xiaoyuan
Published: October 2022

As cryptocurrencies become the target of many investors, it is speculated that there may be a correlation between the trading prices of cryptocurrencies and other assets (e.g., TESLA and BITCOIN). On this basis, we try to build an arbitrage model among the TESLA, BITCOIN, and DOGECOIN to validate the feasibility by simulations using their trading data for 5 years. After conducting the Augmented Dickey-Fuller test, Co-integration test, etc., TESLA and BITCOIN are best correlated that co-integrated over a relatively long period. Within the range of co-integration, we construct the arbitrage model and design the transaction signals by setting a certain threshold. Subsequently, backtestings are carried out accordingly, where different spreads as trading thresholds lead to different results with large differences in returns. These results shed light on the decision on arbitrage investments for cryptocurrencies and other assets.
Equity Incentives and Stock Price Crash Risk: Evidence from China
Authors: Chen Yitong , Jiang Chenxi , Liu Tianyue
Published: October 2022

The impact of equity incentive on stock price crash risk has been investigated in this paper. We solve these problems by u-sing computer tools. We use Stata to analyze the relationship bet-ween these two variables in Chinese Market, and a variety of rig-orous model calculation to obtain the results of the study. Accordi-ng to the results, equity incentive in China is positively associated with stock prick crash risk. Based on a series of robustness tests, including alternative measures and multi-fixed effects model anal-ysis, the relationship remained positive. Furthermore, it is found that the impact of equity incentive on the stock price crash risk is more pronounced in large and high institution ownership compan-ies. According to our research, companies need to control the ext-ent of equity incentives. These results shed light for the relations-hip between equity incentives and stock price crash risk is positiv-e, especially when the size of company is huge enough…….
Investment Portfolio's Efficiency Evaluation for Markowitz Model and the Index Model
Authors: Xiong Tianying , He Ruhai , Zhu Yichen , Wang Haotian
Published: October 2022

In the financial market, the investment portfolio is always a popular topic that investors are interested in and look forward to exploring as well. Since it does affect the expected return and risk of their investment. In this paper, focusing on two of the main models that are Markowitz model and the index model. The paper also collect data from the stock market to analyze different models under different constraints that have their own practical meaning. The result of 5 constraints is concluded below by conducting an efficient frontier and quick ratio.  And it finds out that the index model simplified the calculation of variance matrix but assumption under the Markowitz model is more sustainable in reality. The initial result suggests that both models have their advantages and shortcomings, suggesting it is hard to determine which one is more favorable. However, after further discussion between models. the study found that as long as the original data is accurate, Markowitz model gives better results than index model. If investors want to attain very accurate data, Markowitz model is the best choice. In this paper, the research on the two models of investment portfolios can be a consideration when people are choosing their portfolios. It can be used to create a higher return portfolio as well as a lower risk one, which brings people more thoughts on investing portfolios in promoting the finance market in sense.
Comparisons to Investment Portfolios under Markowitz Model and Index Model based on US’s Stock Market
Authors: Guan Jinying , He Jiawei , Peng Sisi , Xue Tiantian
Published: October 2022

In order to construct an investment portfolio, it is crucial to select risky assets and arrange the weights to each asset. This article selects 6 stocks to compose the portfolio and compare their performances under 5 constraints that are always considered in real life by using Markowitz Model and Index Model. These two models would produce different investment portfolios as they take different factors of stock into account. By calculating the maximal return rate determined by Sharpe ratio, and the minimal risk rate determined by standard deviation, comparing the two models and conclude which model is more suitable under each constraint. According to the results, Markowitz model proves that under certain constraints, investors' portfolio selection can be simplified to balance two factors, namely, the expected return and variance of the portfolio. In the case of Index Model, the conclusion is more general and regular. The results would play a significant role in determining the stocks’ future performance and help investors constructing their portfolios under different constraints.
Research on the investment strategy of new energy vehicle industry based on multi-factor stock selection
Authors: Cui Fenglin , Li Beizhu , Liu Yingchen
Published: October 2022

With the development of the Chinese stock market and the continuous improvement of financial engineering technology, quantitative investment represented by the multi-factor stock selection strategy has been developing and growing in the Chinese stock market. This paper takes the quarterly data of the China Securities New Energy Vehicle Index from January 2017 to March 2021 as the research object, uses the Fama-Macbeth test to select factors, and constructs the regression equation based on the regression method. The regression equation is used to predict the stock return rate of the next quarter through the factor data of each quarter in 2020. The top 7 stocks with returns are selected to construct the investment portfolio in the way of equal-weighted capital allocation, and the investment portfolio is updated quarterly. Through the empirical test, this paper mainly draws the following three conclusions: First, the driving factors of stock return in the new energy vehicle industry mainly include the ratio of long-term debt to working capital (LTDWC), total profit growth rate (TPG), price/earnings to growth ratio (PEG), and equity turnover ratio (ET); secondly, the portfolio return based on the stock selection model in this paper is higher than the average level of the industry, and the investment return obtained is stable, suitable for investment targets; third, the new energy vehicle industry is in a period of rapid development, and the portfolio return rate is higher than the average level of A-share market. Therefore, it has huge potential investment value. This paper provides suggestions and solutions for investors' stock investment in the new energy vehicle industry.
Portfolio Establishment for Asset Allocation based on the Empirical Study
Authors: Wang Qinxin , Tang Yuxin , Jin Yanyan , Lai Yutong , Wang Runyin , He Yihua
Published: October 2022

The purpose of this study is to use Markowitz model and Single-factor index model to determine the optimal portfolio of S&P 500 and 6 stocks from 3 industries under 5 different constraints. The research is looked at stock prices on a daily basis from January 2000 to December 2020 and all data were obtained from secondary sources or non-participatory observation methods. Then this paper also considers the sensitive analysis to investigate the different impacts of factors. The sensitivity analysis tool used in this study was the Solver Table. Through calculation, the optimal portfolio ratio, minimum risk point, maximum Sharpe ratio, effective frontier, minimum return frontier and maximum variance frontier for each constraint under different models are obtained. In this process, it has been found that Single-factor Index model is simpler and more practical than Markowitz model. This paper provides inspiration for individual investors and financial institutions that Index model is more convenient to use in real life and likewise help them to make investment decisions.
Optimal Portfolio under Five Constraints in the Markowitz Model and the Index Model
Authors: Liu Shirui
Published: October 2022

Investing in stocks is an inseparable part of modern life. Besides, choosing a good investment portfolio with high return and respectively low risk is the demand and desire of most modern investors. This paper tries to obtain an optimal investment portfolio to provide accurate and professional investment suggestions to the potential investors through the Markowitz Model and the Index Model under five different constraints. It has been considered several aspects to analyse the results: minimum variance portfolio, maximal Sharpe Ratio, etc. Some findings are given, including that the options of investment portfolio available under no constraint are larger compared to portfolios without permission of short-selling and investing SPX. Besides, the influence of the former is more significant than that of the latter; and then, the corresponding impact of different constraints ---is discussed through efficient frontiers. Additionally, comparing the Sharpe Ratio under two different models, it can be found that the Markowitz Model is a better option.
Comparison Analysis of Arima and Z-test for Forecasting the Maximum Return Based on the Pair Trading Strategy
Authors: Fu Hao , Yang Yaxuan , Zhu Liangzi
Published: October 2022

The stock market trends are of great challenge. Even some of the mutual market's strategies, such as traditional pair trading strategy may still be risky and are likely to suffer an unbearable loss due to an unreasonable stop mechanism. In this paper, a novel approach of pair trading strategy – using the logarithmic return to generate pairs and those deviations to construct trading signals. In addition, two methods that ARIMA and Z-TEST used to construct trading signals are compared according to their corresponding cumulative returns. In part one, the ARIMA model has been used to identify whether there is a constant predictive power and how trading signals should be generated to obtain the highest returns. Therefore, a stationary test has been done, and an optimal threshold has been selected. In part two, the Z-test has been used to distribute the preceding data, and the best threshold to construct trading signals has been found in the same mechanism with that process of ARIMA. As a result, the Z-test method shows a better return than that of the ARIMA model, which could be caused by a more stable forecasting accuracy from the distribution. To conclude, this novel approach is efficacious to lower the risks from unanticipated extreme cases and unwise designs on stopping signals. Furthermore, the Z-test method for signals construction is more stable and profitable than the ARIMA. The research greatly maximizes profits in stock markets by selecting the best model and an optimal threshold that models should be applied.
Performance Analysis for Portfolio Construction and Stock Price Prediction of Social Media Platforms
Authors: Lin Xintong , Tan Xuepu , Yang Xuening
Published: October 2022

The stock price prediction and portfolio construction are very important in the application of quantified investments. Risk control and stock price prediction are two challenge problems that we want to solve. In this paper, two main steps are processed to quantify the risk and predict the stock price. Especially, the first step is portfolio optimization, which is based on the Mean-Variance method. The second step is the stock price prediction, which is designed based on the Arima-based method. The results show that the stock “TWTR” and the stock “WB” have the above 90% ratio of the stock combination, which shows that the “Twitter” and “Weibo” social media corporations have a higher expected return with a lower risk. In addition, the best ARIMA model used to fit our data will be the one with parameters p=4, d=0, q=3. Our research has great significance in the application of quantified investments.
The Impact of Two-Way FDI on the urban-rural Income Gap Based on Broad Least-Squares Analysis
Authors: Xu Xiaoke
Published: October 2022

With the continuous promotion of China's opening up to the outside world, the gap between the urban and rural residents in China has been greatly affected. To study the influence mechanism of two-way FDI on the income gap between the urban and rural residents and to study the influence mechanism of two-way FDI on the income gap between the urban and rural residents, this paper selects panel data on the income gap between the urban and rural residents in 31 provinces of China from 2009-2018 from the International Bureau of Statistics, the People's Bank of China and the Ministry of Commerce, construct a generalized least squares model, uses STATA software, and conducts an empirical study. The research results show that the development of two-way FDI has a significant effect on reducing the income gap between the urban and rural residents. Based on the above findings, this paper puts forward the following suggestions. (1) Promote stable domestic economic growth to lay the foundation for narrowing the gap between urban and rural residents. (2) Develop high-quality foreign trade and promote labor mobility outside the secondary and tertiary industries. (3) Improve China's financial market and enhance financial efficiency. (4) Promote technological innovation and upgrade industrial structure.
Investment Analysis of Drinks and Soft Drinks Firms: The Weighted Ratio Analysis in Modeling in Excel
Authors: Zhang Mengxiang
Published: October 2022

Financial innovation, Information System and technology application today has become the most popular topic in financial analysis. Professional researchers and data analysts working in the financial and economic area actually applied various modeling tools to make estimation and evaluation for the firm’s financial performance. Data analysis and ratio analysis are traditional tool in financial analysis, but also provide new ideas and models in the evaluation of the stock performance. The application of the modeling in weighted ratio analysis in excel would help investors and other stakeholders to understand how the firms are ranked based upon their financial performance. The soft drink industry develops quickly after the industrial revolution and becomes a large quick consumption market in the modern world. The cost management in modern production lines in this market increases the competition and product differentiation.  This paper, it is aimed at investigating the performance of the drink and soft drink corporations to provide investment analysis. According to the empirical analysis, the capital structure, cost and revenue management, profitability and growth are the main consideration for investors to make a decision. In this study, Coke Cola, Pepsi and Monster Beverage Corporation are the three main target firms. Their five-year profitability performance is examined based on the ratio of P/E, EPS growth and Sales/Assets. In terms of the weighted ranking process, Coke Cola is ranked with the highest weighted score to show strong growth and profit-generating. The report has certain limitations such as time horizon limitation and sampling scale limitation of firm number and ratio number. It provides the further opportunity to make a wider investigation and some useful insights for investment and strategy. Overall, these results shed light on guiding further exploration of investment analysis for the soft drink industry.