bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of relationship between quantity and price of Yamana Gold Company based on Granger test
Authors: Wang Yitong
Published: March 2023

Contemporarily, investigation focuses on the inherit connection between the stock market prices and trading quantity has been a general trend regarding to the quantitative financing forecasting. The relevant research conclusions have also been widely used in the field of financial economy. For the sake of explaining the correlation between the two series, this paper takes Yamana Gold Company as the object. In terms of descriptive statistical analysis and empirical analysis method as well as the Eviews software, this study analyzes the stock price and trading volume of the target from December 1, 2003 to May 5, 2022. According to the analysis, the trading volume is the Granger on account of the return rate, while the return rate is not. By investigating the relationship between volume and price, they can deeply grasp the operation of the stock market and lay a solid foundation for investors and regulators to make various decisions. These results shed light on guiding further exploration regarding to the healthy and stable development and perfection of the stock market.
Comparison of Price Prediction Based on LSTM, GRU, Random Forest, LSSVM and Linear Regression
Authors: Liang Jiali
Published: March 2023

Investment decision-making involves numerous factors to yield significant profit. Contemporarily, various models are proposed to be used in stock price prediction. However, the traditional linear model lacks the ability to mine the implicit information of the data, resulting in difficulties in deliver satisfactory performance on nonlinear data with large fluctuations and strong noises. LSTM, GRU, Optimized Random Forest, and LSSVR were employed as training methodologies to study the effectiveness in predicting directional movements of close stock prices of TESLA from July 2018 till July 2022 in comparison with the Linear regression model. This study adopted a combination of technical and fundamental analysis to reflect various sources of influence factors in the movement of stock prices. According to the analysis, the proposed models demonstrate a better accuracy score and excelled in avoiding a severe overfitting issue found in the benchmark algorism. These results shed light on guiding further exploration on machine learning techniques.
A Comparison of Stock Price Prediction with ANN and ARIMA
Authors: Ma Bowen , Yang Yanchi , Zhang Jiaming , Zhang Keli
Published: March 2023

Nvidia is one of the most competitive companies in the semiconductor industry, whose stock has risen a remarkable 5,427% in the past decade. Forecasting its stock price has always been one of the most important topics for investors, as its stock price fluctuates dramatically with the release of new products and the rising price of cryptocurrencies worldwide. This paper compares the degree of accuracy of ANN and ARIMA, which are considered to be the most commonly used and accurate models in stock price forecasting for the past 20 years, in predicting Nvidia's stock price. The time period chosen for the prediction is from June 2020 to June 2021, when Nvidia's stock price rises sharply, and the data is obtained from Kaggle and Yahoo Finance. According to the analysis, the ANN model is clearly capable of predicting the sharp fluctuations in Nvidia's stock price between 2020 and 2021, which also indicates the potential of artificial neural network-based models for stock price predictions. These results shed light on guiding further exploration of stock price prediction.
Empirical Analysis of Alibaba's Acquisition of NetEase Kaola
Authors: Hang Zhao
Published: March 2023

Contemporarily, the Internet and the cross-border e-commerce industry has developed rapidly, and the competition within the industries has become increasingly fierce. On this basis, enterprises have started to undertake mergers and acquisitions (M&A) among themselves as a measure to ease the competitive pressure. Meanwhile, many internet companies are using M&A to achieve their rapid expansion. This paper takes Alibaba's acquisition of NetEase Kaola as an example and analyses the motivation of the cross-border e-commerce company's M&A, explaining the necessity and rationality of this M&A. In addition, the quantitative and qualitative analysis method is chosen as the evaluation method. The evaluation is carried out in terms of market competition and financial indicators respectively, in order to provide an in-depth analysis of the effectiveness of this M&A and whether it meets the motivation of the company. According to the analysis, Alibaba's acquisition of NetEase Kaola has resulted in the upgrading and integration of strategies and resources, which has improved the overall effectiveness of both parties in the short term. However, there is still some space for improvement in the long-term development level. These results shed light on guiding further exploration of Internet companies to implement M&A decisions in the future.
An Analysis on the Impact of ESG System Disclosure Quality on Corporate Financing Costs under the Carbon Peaking and Carbon Neutrality Goals
Authors: Liu Hongxuan
Published: March 2023

This study reviews the link between China's green development path and green finance in recent years, based on the background of the carbon peaking and carbon neutrality goals. The relationship between the quality of corporate ESG disclosure and financing costs of corporate is investigated by using data from Chinese A-share manufacturing enterprises for the period 2012-2020. The study uses a panel data model to estimate the regressions, and finds that The information disclosed about corporate governance and social responsibility in the ESG system has a significant impact on financing costs. As China gradually develops its ecological civilization, the impact of these two dimensions on the financing cost of manufacturing businesses grows more and more. This study examines the effects of the ESG system on business operations from the viewpoint of information disclosure and advances our knowledge of the connection between business sustainability and financing costs.
Analysis of Starbucks in China
Authors: Wang Zhaozhe
Published: March 2023

Since coffee is gradually becoming popular in China, the promising market prospect that China’s coffee market has is appealing to multiple companies. Starbucks, a successful business magnate in the coffee market around the globe, occupies a huge market share in China’s coffee market. Nevertheless, numerous competitors, especially domestic coffee brands in China, and the hit caused by the COVID-19 epidemic put great pressure on the company. Furthermore, the company itself also has some weaknesses currently, which can affect the corporation negatively. As a result, based on the background of China’s coffee market, and the enterprise’s own situation, this article mainly pays attention to three vulnerabilities, giving an analysis of these problems, and some suggestions will be provided correspondingly.
Exploring Digital Marketing Strategies in Catering Industry
Authors: Chen Jiaye , Li Yixin , Liu Yuxuan
Published: March 2023

With the development and popularity of the Internet, digital marketing has gradually become popular in various industries. Following the development of the times, the catering industry applies digital marketing as the main marketing method. Starbucks, as one of the major companies in the restaurant industry, has complete digital marketing strategies that can be utilized as the research case in this paper. By exploring the advantages and disadvantages of Starbucks’ digital marketing strategy in China, combining qualitative research and quantitative research, this paper provided ideas for other brands in the catering industry to improve their digital marketing models. This paper first introduced the digital marketing strategy of the catering industry and Starbucks and the recent research related to those. Then, the paper was followed by a detailed introduction of the research tools, methods, and model. Using SPSS 25 to build a structural equation model (SEM), the path coefficients showed the relationship of variables. This paper concluded that Starbucks uses its digital marketing strategy to attract customers. This strategy heavily influenced people’s purchase intentions; however, customers’ willingness to share Starbucks products on social media was not strong enough to fulfill Starbucks' expectation of attracting potential customers through existing customers' promotions on social media. This paper figured out how to solve Starbucks's problem and how other brands in the catering industry would learn to correct it.
Business Valuation Analysis: Taking Lululemon as an Example
Authors: Yun Wenzhe
Published: March 2023

Lululemon's unique and innovative brand culture and concept, combined with the pursuit of healthy living and the globalization of sport, has led to the company's global growth. Lululemon’s creative fabric technology and design also enhanced its competitive edge. From the perspective of politics, economy, society and technology, due to the rapid expansion and emerging yoga culture and heathy life concepts, it might be overvalued according to its leading and fast-growing status in the athletic clothing market. In this paper, P/E ratio, forward P/E ratio, EV/EBITDA ratio and discounted cash flow model are adopted to value the company. The results of valuation ratios of Lululemon are higher than other competitors, and the data generated from the discounted cash flow model is lower than its current market value, indicating that the price of Lululemon is indeed overestimated. This paper would provide the investors an overview of Lululemon’s brand history, market position and basic valuation statistics.
Russian housing price forecast based on BP neural Network
Authors: Du Sidi , Liu Xiqing , Shi Songze , Zhou Guanchen
Published: March 2023

Contemporarily, Russia's real estate market has huge potential for investors. The purpose of this paper is to investigated the impact of various factors on the real estate market price based on various statistical models. We collected past housing price data from the Internet. Subsequently, PCA model was adopted to reduce the dimension of the data to simplify the calculation. Finally, the BP model is implemented to predict the price changes in the real estate market. After calculation, our forecast data and the reality of housing prices are slightly different, but the forecast of the real estate market is consistent with the reality. In order to further find the influence of various factors on housing price, we also calculated the characteristic importance of different factors and found the most important influencing factor, i.e., the region. These results can provide investors with an idea to analyze the real estate market prices, and help policy makers find the real estate market prices in line with the market rules to avoid the occurrence of bubbles.
The impact of COVID-19 on Real estate and consumer behavior based on SPSS analysis
Authors: Chen Runyu , Qi Sirui , Yu Jingyi
Published: March 2023

Since the Spring Festival of 2020, the rapid spread of COVID-19 has a serious impact on real estate enterprises. According to the Supreme People's Court, a total of 408 real estate companies filed for bankruptcy in 2020, up 8.2 percent year on year. It is worth mentioning that there are many well-known real estate companies on the bankruptcy list since the COVID-19 pandemic. In this paper, a questionnaire survey was conducted on the willingness of residents to purchase houses and their choice of real estate enterprises since the epidemic. SPSS software was used for data modeling and analysis, and the comparison was made before the epidemic. Meanwhile, a case study is conducted on the financing capacity and earnings of Country Garden, Vanke and Sunny City Real Estate from 2019 to 2021. Overall, residents’ choice of real estate enterprises has changed greatly since the outbreak, and the economy of real estate enterprises has been deeply affected. Therefore, based on the repeated situation of COVID-19, the economic choices of real estate enterprises and consumers deserve further study, and relevant policy suggestions are put forward accordingly. These results shed light on guiding further exploration of real estate enterprises risk management and residents investment decisions.
Various Applications Dynamics of Big Data Analysis in Supply Chain Management
Authors: Wang Shibo , Wang Zixuan
Published: March 2023

Contemporarily, with the rapid boost of the data quantity, big data analysis techniques have become a major tool to deal with issues in various fields. Among different research fields, supply chain management is one of fields that can be strongly improved and enhanced based on big data analysis concepts. In this paper, we discuss various applications and different implementation approaches for big data analysis in supply chain management. To be specific, the basic features of the big data analysis and supply chain management are introduced. Subsequently, the types of the analysis in big data concepts will be presented. Afterwards, the specific applications implemented in supply chain management are discussed. According to the analysis, the current challenges limitations are clarified. At the same time, the future prospects as well as the opportunity for the supply chain management based on big data techniques are demonstrated. These results shed light on guiding further exploration of big data implementation in supply chain management.
Application of Market Cycle Analysis and LSTM in Prediction of Stock Price Movements
Authors: Chen Weihang
Published: March 2023

The stock market prediction has been carried out by several ways in data science using deep learning approaches to capture profitable trading opportunities and making the trading plans. However, it is widely believed there are two main issues involved in it, i.e., efficient market hypothesis and low information noise ratio. Therefore, a prediction based model will be affected by noises thus hard to produce a prediction. In this paper, two methods will be presented for forecasting stock future performance. To be specific, LSTM (long-short time memory) and cycle analysis are implemented to predict the future period that gives a higher return than average times. According to the analysis, introducing the time analysis as a variable to input could significantly increase the accuracy of predicting the return for the next few weeks. These results shed light on guiding further exploration of the different ways of extracting periodic behaviors of the market and marking predictions based on the analysis.
US Auto Production and Price Prediction in the Context of Multiple Regression Analysis
Authors: Li Qilin
Published: March 2023

After the eruption of COVID-19, the worldwide supply chain had been seriously affected and further impaired. Logistics and semiconductors production are not going smoothly during this period and the supply and demand supply balance had been weakened by this pandemic. There is a noticeable trend that the US auto production rate is declining year after year, whereas the car purchasing price as well as the gasoline price is rising each year. This paper investigates US auto prices based on multiple factors regression model. According to the analysis, there is a direct correlation between semiconductor production and the auto car production rate. In addition, US car production rate follows along with CPI (Consumer Price Index). By comparing this paper’s results with the movements of CPI and unemployment rate, the study will derive an approximate prediction upon the future auto car prices in the US. This methodology for car price prediction is not very precise, yet it can still reflect some general opinions or human being’s faith in the future car industry. The discussed model is the one to capture this attitude and translate it into figures and graphs which can give a direct assumption regarding to the people’s attitude. Otherwise, it can simply reflect possible future investing move one rational investor may take. These results shed light on guiding further exploration of stock price variation through multiple factors varies from raw material to people’s faith in the stock markets.
Impact of China's Aging Population on Economic Development and Possible Solutions
Authors: Chen Zixuan , Xiong Ruixi
Published: March 2023

China's economic structure has been unbalanced for a long time, and now it faces the severe challenge of the aging population. This article will deeply analyze the impact of population aging from the aspects of social impact, labor force and medical security. With the unexpected arrival of an aging society, the government, society, and individuals should remain calm. They should recognize the negative and positive aspects of its effect on social development. The reduction of cheap labor will undoubtedly harm the development of labor-intensive enterprises. However, it can force these businesses to increase their labor productivity rate, move into the field of high technology and high added value, and increase the employment rate of college students and another high-quality talent. Moreover, the aging population will drive the growth of the elderly economy and related service industries such as home Economy. In this article, we will also list several ways to solve the economic crisis caused by the aging population
Statistics and application of multi logistic model and negative binomial model in data
Authors: Li Lianjie , Jing Bolin
Published: March 2023

Contemporarily, statistics are widely adopted in various disciplines to verify the effectiveness of the analysis results scientifically. This article demonstrates two applications of the statistical. To be specifical, it mainly investigates negative binomial model and the way to judge the determinacy of factors with the help of Multi Logistic model. For the former, the relative superiority of random parameter binomial model is discussed. According to the data analysis of a traffic accident in a certain place, it shows a better model fitting effect. Another case of poultry waste recycling was used to introduce and compare the using conditions and advantages of Multi Logistic model. These results shed light on guiding further exploration of applications of statistics.
A Study on the Impact and Mechanism of ESG Performance on Corporate Value
Authors: Fu Bosen , Wang Zexuan , Wei Leyao
Published: March 2023

With the improvement of the Chinese capital market in terms of regulation system and overall maturity, the significance of the ESG concept to the capital market has been rising accordingly, becoming an important source of corporate signals. In this context, ESG value investment has gradually received attention from academia and the market and a lot of discussions have been conducted on ESG and corporate value, but there are still many differences in the research on the relationship and mechanism of the two. The academic argument of ESG governance's function has been reflected in the capital market that most Chinese listed companies neglected ESG governance, and less than a quarter of them have made the disclosure on this basis. Hence, In context to this background, this paper explores the correlation between ESG performance and enterprise value as well as explains the mechanism of this effect by constructing a multiple linear regression model with sample companies from the A-share capital market. It is found that ESG performance is significantly and positively correlated with enterprise value, for every 1% increase in ESG performance, enterprise value will increase by 7.2% on average. This correlation also has been proved by this paper that can be explained by the contribution of better economic performance and a financing environment led by good ESG performance.
Analysis Meituan’s Current Situation and Development Strategy
Authors: Hou Zian , Yalong Li  , Zhang Weiquan
Published: March 2023

In recent years, Meituan has achieved certain positive results in China, but its management under the old system has led to the continuous emergence of deep-seated problems. The immaturity of the supply chain has led to a severe impact on Meituan and a lost customer base. The problem that Meituan faces are not only a supply chain problem but also the risk of expansion. To resolve these risks, we need to optimize the supply chain through Meituan, establish a general warehouse to accommodate more suppliers and establish self-pickup and distribution points. To make it easier for residents of the community to pick up the goods, the expansion of the hotel industry starts with low-star hotels and uses some guarantees and discounts to bring in new customers. These improvements are conducive to the steady and healthy development of Meituan in China and realizing an upward trend in the future.
The Impact of COVID-19 on Logistics in Context of Regression Analysis
Authors: Qiu Zhengyang , Zhang Moziyan , Zhang Ruoye
Published: March 2023

Since 2020, the epidemic has significantly affected China’s development in several different areas. As a result of the epidemic’s shifting circumstances, numerous industries have seen diverse transformations. On the other hand, the logistics sector has grown as a result of the epidemic, for instance, as consumers rely increasingly on e-commerce platforms for their purchasing. Still, it has also been impacted by national legislation. This study examines the relationship between several logistics indicators and the number of new cases added to the epidemic in order to provide an overview of the logistics industry’s growth process in the context of the epidemic (reflecting the changes in the epidemic). In this research, some indicators that mainly reflect the overall efficiency of logistics during the epidemic (e.g., LPI, Storage index, E-Logistics index, and Freight rate, as well as the number of new and accumulated confirmed cases of the epidemic), were collected and collated to represent the trend of the epidemic, and correlation and comparative analysis were conducted to obtain the specific consequences of COVID-19 on the logistics industry. A typical example is isolation control which results in a dramatic decline in the freight volume of road transportation. These results can help the logistics industry to determine the development direction and plan under the epidemic and find the development trend of the overall market through this paper.
How Can the Enterprise Strategic Performance Indicators be Constructed
Authors: Tang Meihuan
Published: March 2023

In the current commercial society, enterprises pay more and more attention to the confirmation of strategic factors and the construction of strategic performance indicators. Previous researchers have conducted in-depth research on strategy and performance respectively, but there is still a gap in the research of integrating the two to build a strategic performance indicator system. Therefore, this study will aim at this gap, based on the previous research and expansion, first clarifying the composition level of strategy and the composition system of performance, select the corresponding strategic performance indicators through analysis, and study the construction of strategic performance model through the method of building models. Through the research, a rough conclusion is that the strategic performance is positively related to the improvement of most strategic factors, such as financial benefit, operational efficiency, social benefits and market value. It can be seen that the improvement of strategic factors for performance is conducive to the development of enterprises.
Research on the Impact of Social Media Platforms on the Market Segmentation of Beauty Products and Optimization of Positioning Strategies
Authors: Zhang Xiaoqing
Published: March 2023

Currently, China has become the world’s second-largest consumer market for cosmetics. The number of licensed cosmetic manufacturers nationwide is more than 5,400, with more than 87,000 cosmetic registration and records subjects of all kinds and nearly 1.6 million products effectively documented. Although domestic brands are on the rise, on the whole, it is still some international brands that occupy the largest share of the domestic cosmetic consumption market. The development of social media, especially social platforms such as RED, where beauty products are the main domain, provides a more efficient data collection platform for domestic beauty brands to penetrate deeper into the market. This paper conducts effective market segmentation in more comprehensive dimensions and develops differentiated positioning strategies. Taking the foundation market as an example, this paper uses RED as the main platform for data mining to provide a reference for the process and ideas for companies to use social media platforms for market segmentation. From the analysis results, the data from social media platforms go beyond the traditional method of market analysis by collecting demographic, geographic data, and so on, by directly segmenting according to consumers’ actively expressed demands, thus making the basis of market segmentation more accurate and refined. Furthermore, the social media platform can show the competition situation of each segmented market. The analysis of competitors’ related data provides a more accurate basis for market assessment and, ultimately, precise positioning.
Research on Current Development and Social Media Marketing Strategies of MIXUE Ice Cream&Tea’s
Authors: Chen Mier , Xiao Qixing , Zheng Qi
Published: March 2023

As one of the hottest milk tea stores, MIXUE frequently appears on social media. This paper analyzes the current state of MIXUE’s social media marketing and identifies problems in MIXUE’s social media marketing decisions. MIXUE does not appropriately market its products; all its efforts are directed at promoting the MIXUE brand itself. In addition, MIXUE’s short video content was not impressive and did not leave a good impression of the brand. On top of that, MIXUE did not choose to hire a KOC or KOL to be the brand spokesperson. And the store planning was not reasonable, which led to stores of the same brand competing with each other. In order to solve these problems, MIXUE should improve the content of its products in the promotion and try to improve the quality of short videos. In addition, MIXUE should hire the right KOC or KOF to promote their products and brands and reasonably plan the stores to reduce the competition. This article can provide new ideas and information for milk tea companies when exploring social media marketing strategies.
The Forecasted Prospects of the Return of Investment in Elderly Care Service Industry Based on the Analysis of the Market and YADA
Authors: Chi Haotian , Zhang Jianjia
Published: March 2023

With the slow increase in birth rate, China has stepped into an aging society and the aging population will continue to grow, and the burden on young people to support the elderly is becoming heavier and heavier. The elderly care service has become a hot issue. Therefore, this paper is based on an in-depth study of the financial statements and market research of Beijing Yada Senior Living Group Co., Ltd., and analyzes the current market situation of the elderly care service industry in China using a combination of macro and microenvironment analysis and the internal and external competitiveness of the company and give recommendations for its development. The study shows that although people's social cognition has become part of the obstacles, the increasing demand for senior care services in the country according to the company's operating data in recent years shows that senior care currently belongs to a window period for investment and is highly likely to bring huge returns to investors in the future. As a result, it is recommended that more investors should focus on the senior care market and consider providing more capital as a solid foundation for its development.
Problems and Opportunities for Metal Industry after the COVID-19 Pandemic
Authors: Yang Zhiyu , Yang Zonghan
Published: March 2023

The COVID-19 pandemic has severely damaged the global economy system. In China, the metal industry is playing a key role in the reconstruction of the economy. This paper is using SWOT analysis to analyze the current situation faced by the metal industry in China after the pandemic and give corresponding advice for institutions. Strength part mainly focuses on analyzing the strong supply system in China enabling metal factories to recover the production in a short time period and also the natural advantages accrued from the huge population of China and abundant reserves of metal ores. Weakness part mainly discusses some long-lasting problems for Chinese factories, including the heavy pollution problem and the lack of competitiveness in the global market due to insufficient production technology. Opportunity part discussed two opportunities for the Chinese metal industry during the post-pandemic time. One is the high demand for metal products for reconstruction of the economy, the other one is the rise in the price level of metal products as a result of the breakthrough of the Russia-Ukraine War. Finally, the threats part mainly discusses the effect of pandemic on the metal industry. The suspension in the global supply chain restricts metal businesses from receiving raw materials and selling products. The intense competition in the metal market after the pandemic also raises the risk for metal businesses. To evidence the statement, this paper introduced data from China’s National Bureau of statistics and cited tables and graphs from the annual report from China’s National Bureau of statistics.
Research on the Effect of Policy on Real Daily Wages in the UK from 1260 to 1994 Based on Multiple Models
Authors: Chen Xingmu
Published: March 2023

Between 1900 and 1994, daily wages in the UK changed dramatically, therefore, in order to explore how the UK policies had significant impacts on daily wages, the main objective of this research is to identify the changes in UK daily wages before and after the implementation of the policies, and to forecast the future, compare simulative models and select the most appropriate forecasting model. The methodology of this study was to collect data on daily wages in the UK from 1900 to 1994, then forecasting the data through simple exponential smoothing, ARIMA model, ETS function. After predicting the daily wages in the given time period, make comparisons between the real-time statistics and the results produced by the simulative methods. The outcome of this research is the daily wages in the UK has been affected certainly by the policies, through comparing the values conducted by each model. All three models predicted the daily wages should be decreasing slightly in 1994, only fewer than 40 GBP, however, the real statistics has shown the significant increase in 1994. Therefore, the effects brought by the policies are detrimental and significant.
Application of Fama-French Three-Factor Model in Firefighter Investment Strategy
Authors: Qiao Yining
Published: March 2023

Using some models to make the portfolio optimization is a widely used approach nowadays. This paper studies how to choose the right portfolio to diversify for the firefighter who is about to retire. This allows customer to avoid risks while obtaining appropriate benefits. This paper selected five stocks from different sectors that performed better and used two main approaches. It uses the Mean-Variance analysis to analyze how to make these two mutually restricted goals, i.e., minimum variance portfolio and the maximum Sharpe ratio portfolio. At the same time, the FF3F model is used to analyze the investment weight of the selected portfolio, so that the funds can be reasonably invested. The results show that all the stocks are positively correlated. In the FF3F model, the Sharpe ratio of the non-buyout case is higher than that of the buyout case. The results in this paper show that the option with higher Sharpe ratio can obtain more return in per unit risk and is more suitable for firefighters.
Application of ARIMA Model and Exponential Smoothing Method in GDP Prediction of the United States
Authors: Lyu Gaoyue , Lyu Xiulin , Sun Nansong , Zhao Xinrui
Published: March 2023

The GDP of the United States always attracts the global attention. It represents the strength of the world's largest economy and the per capita living standard of developed countries. Therefore, many scholars try to use various methods to predict it. On the basis of previous research, this paper collects the Fred’s quarterly U.S. GDP data, uses ARIMA model and exponential smoothing to model the US's GDP from 1950 to 2021. Then, the authors compare the actual values with the predicted values to select a better model. After that, the established model is used to forecast the US's GDP. The results show that the two methods generally maintain a high degree of fit, but the error generated increases with the widening of the expected range. Among these two methods, the average error value of the exponential smoothing method is slightly smaller than ARIMA, but ARIMA's forecasts are more accurate in the early. Therefore, ARIMA should be used preferentially for the forecast in the short term and the exponential smoothing method should be preferred for long-term forecasts. Furthermore, we use the exponential smoothing method to make a short-term forecast for the U.S. GDP by the fourth quarter of 2023. The results show that the U.S. GDP will increase at an average rate of 0.9344%, and the upward trend is stable and cyclical. Finally, the result of the above provides an effective basis for the US economic construction work and plays an inspirational role for China's economic policy formulation.
The Impact of Federal Reserve’s Interest Rate Policy on US Semiconductor Industry
Authors: Liu Weichen
Published: March 2023

The Federal Reserve raised interest rates by 75BP in June. In the meantime, the American government has enacted laws and orders to promote the growth of the semiconductor sector [4]. The purpose of this essay is to assess how the Federal Reserve's interest rate policy has affected the US semiconductor industry. To determine whether it has a beneficial or negative impact on the industry, this research uses the VAR model. This study projects the yield and volatility of semiconductors using the ARMA-GARCH model. The findings demonstrate that raising interest rates encourages greater investment in the stock market, which is advantageous for the semiconductor sector. But as time passes, the yield's volatility rises as well. This paper provides the reason that since the US chip sector has long had a dominant position, chip demand is not price elastic, and the strengthening of the currency is insufficient to reduce chip demand. The outcome is dominated by net capital inflows.
Research on the Influence Mechanism of Corporate Social Responsibility on Financial Performance
Authors: Gong Peizhang
Published: March 2023

In the process of social development, corporate social responsibility and corporate financial performance have widely concerned. In academia, there is numerous researches on the connection between the two. Reviewing pertinent academic writing on the CSR and financial effect is the goal of this study, sorting out how the two elements are related and guiding corporate participation in community responsibility functions. The study of this paper draws several conclusions. First of all, most businesses that participate in social responsibility initiatives can improve their financial performance. What’s more, the participation of a few companies in social responsibility activities has nothing to do with company performance or even hinders the company's business performance. The different impact results are related to the company's operating conditions, the purpose of participating in social responsibility activities, and social recognition. If companies wish to increase their financial returns through social responsibility, they must excel at strategic management.
Yield and Volatility of TSMC under this Turn’s Interest Rate Policy
Authors: Sun Anjia
Published: March 2023

The Federal Reserve Board of Governors made the decision to increase the target range for the federal funds rate for the fourth time in 2022 on July 27. Due to the fact that many global events took place, such as the Covid-19 Pandemic, the China-US trade war, and the Russia-Ukraine war, these changes brought about the worst economic collapse seen in the United States since the Great Depression, which led to the highest inflation rate seen in the 21st century. The decision was made by the government of the United States to raise the federal funds rate in order to reduce inflation and achieve market stability and smoothness. The effects of rate rise by the Federal Reserve are substantial in a variety of contexts, particularly in the semiconductor sector. This research chose a well-known Chinese company, Taiwan Semiconductor Manufacturing Company, and intercepted its stock data from 2019 to 2022. It then used both the VAR model and the ARMA-GARCH model to simulate and analyze the data, studied the influence of Fed rate hikes on this Chinese semiconductor company’s yield and volatility rate, also made a future prediction of this Chinese semiconductor company’s development, and finally offered some comments and suggestions for the company.
Influence of historical context on group decision-making
Authors: Cui He
Published: March 2023

“Black Swans” andgroup decision making have become familiar terms in the relevant fileds. There have been many Black Swan events in history, such as the current covid9 epidemic or the failed launch of the Challenger space shuttle in 1986. In the run-up to the Challenger launch, NASA conducts a conference call. This contains typical group decision-making issues. As an example, through access to information. Aboutexamine the impact of the social and historical context of the Challenger launch on the conference call, and author also analyses the impact of these contextual factors on the decision-making group. In order to identify these potential factors so that they can be avoided in future decision making. Some Black Swan events are accompanied by group decisions, which can influence the direction of events. However, the decision makers and participants in group decisions are also influenced by different factors. For example, social context and pressure. In high pressure or reactive situations, group decisions can be biased in different ways. In the case of Challenger, the decision makers were influenced by public opinion and the pressure of the international situation at the time, which led to problematic decisions. This is why it is more important in group decision-making to look at the problem of the event itself and consider the problems that existed. This paper using a literature review research method with Challenger as the subject of the study, examines the impact of the historical context and social environment on decision-making at the Challenger pre-launch group meeting. The research results show that the context created economic, public opinion and time pressures on NASA. These pressures in turn had a huge impact on the decision makers. In the end the panel's decision making was flawed.
Budweiser's Digital Transformation in the Context of the Epidemic
Authors: Zou Zhihua
Published: March 2023

The COVID-19 epidemic has plagued the world in recent years, causing drastic changes in people's lifestyles. Beer is the third beverage in global sales after water and tea. Simultaneously, the digital economy is fast evolving. Many organizations are undertaking digital transformation. This essay focuses on how Budweiser is transforming digitally to achieve profitable growth in the post-epidemic era. Through the competitor analysis, environmental analysis, and SWOT analysis, this piece examines the company's competitiveness and development potential. This report offers Budweiser viable solutions to aid with its digital transition. COVID-19 has had a significant impact on numerous industries; therefore, businesses should have a better grasp of themselves and the industry in which they operate. "Know the enemy and know yourself," as the Chinese proverb goes, "and you can fight a hundred battles with no danger of defeat." Companies can only go to the next stage if they completely understand themselves, their competitors, and the macro-environment.
The Ongoing Recovery of U.S. Airline Stocks Through the COVID-19 Pandemic: An Event Study Approach
Authors: Fan Wendi
Published: March 2023

The COVID-19 pandemic hit the airlines, both business and leisure travels, hard due to severe travel restrictions imposed by governments around the world to combat the virus. The stock prices of major airline companies have dropped more than the broader market. This paper aims to quantify the impact of a shock to the COVID-19 pandemic on U.S. airline stock prices by examining ten specific events evenly spread through January 2020 and August 2022. Seven airline stocks are selected, including JetBlue, American, Delta, Alaska, United, Hawaiian and Spirit. It is observed that the stock prices react to public information quickly by the Efficient Market Hypothesis in most but not all situations, and to varying degrees. Simple regression analysis was performed as a supplement to understand the factors affecting the performance of transportation stocks in general. The result of this study will be useful to airline investors and stock market participants to react quickly when making investment decisions. Moreover, these results shed light on guiding regulators and policymakers to implement financial support amid catastrophic shocks from a pandemic or likewise.
How to Optimize a Financial Portfolio for a Firefighter
Authors: Qiao Jingyi
Published: March 2023

How to increase the amount of pension is a major concern for many retirees. In this paper, the question of whether retirees need to buy out their pensions is examined. Two portfolios are set up and their Sharpe rates are compared under two assumptions. The purpose of the study is to effectively assist retirees in their asset allocation. In this paper, diversified assets from four different sectors were selected to construct the portfolios. Three methods, the mean-variance model, CAPM model, and FF3F model, are used in this paper for portfolio construction and comparison. Meanwhile, the performance of the portfolios was analyzed using the weighting analysis method. The results show that "Disney" has the largest share when it chooses to buy out its pension and reinvest it using the CAPM model, while "LVMH" has the largest share in all other cases. This study may be useful for retirees who are faced with the decision of whether to buy out their pensions.
The Asset Allocation Analysis for Banking and Technology and Retail Industries
Authors: Lin Jiaxin
Published: March 2023

With the outbreak of COVID-19 in 2020, the economies of almost all countries in the world have faced inevitable and significant losses. The GDP growth rate of major economies in the world has not improved or even declined. During the pandemic, many people lost their jobs, which meant they lost a regular source of income to support them; At this time, the money made by the way of making money online -- buying stocks, or various financial products -- is very important, and portfolio analysis is the first step to successful investment. In this paper, four of the most successful companies in the United States are selected for analysis. They are AAPL, AMZN, AXP, and JPM, which respectively involve the financial industry, banking, technology, and retail industry in the United States. This article uses three methods for portfolio optimization, which are called mean-variance analysis, CAPM Model and Fama French Three Factor Model, this paper calculates the weight proportion of four companies under Three different models. The results show that in mean-variance model has the highest projected revenue among the three models, while CAPM has the lowest projected revenue. Meanwhile, among the mean-variance models, AAPL has the highest proportion of investment, but among the CAPM and FF3F models, JPM, which has the worst performance in the mean-variance models, has the highest proportion. This research will benefit the related investors in financial markets.
Case analysis of Zara localization failure in China market
Authors: Chua Edison Lin , Guo Chenye , Xiang Beihan , Xing Xuanming
Published: March 2023

Zara is one of the biggest fast fashion industries in China market, some researchers discovered that during the recent decade Zara was gradually declined but the main reason for Zara's decline is still a lack of a unified explanation. Therefore, our research topic is “Case analysis of Zara localization failure in China market” and in this paper, we have used SWOT analysis to analyze the strengths, weaknesses, opportunities, and threats of ZARA. And our research showed that there is a lot of question that cause Zara to fail in China market such as potential political controversial statement (Xinjiang cotton issue), the acceptance of fast fashion downward in China market, epidemic, competition, and so forth. Furthermore, our suggestion for Zara is to avoid any potential political controversial statement, more focus on the online platform, and do more research on China market.
A Study of Starbucks (China) Cross-Cultural Marketing Strategy
Authors: Liu Boxuan
Published: March 2023

Starbucks, a multinational coffee chain, has been the head of China’s coffee industry since it entered the Chinese market in 1998 with its high-quality coffee and people-oriented business service concept. Moreover, as China’s economy continues to grow and its level of consumption rises year by year, the Starbucks China market has become the second largest overseas market besides the U.S. domestic market. The author hopes to draw lessons from the analysis of Starbucks’ marketing strategy in China and give certain implications for restaurant chains in the context of new retail. In today’s Chinese society, Starbucks sells not only coffee but also services and the “third space” provided to consumers. People generally consider Starbucks as a petty and fashionable lifestyle. This paper analyzes the macro environment and industry environment of Starbucks in China by using PEST and the five forces model to point out the problems that still exist for a multinational coffee chain in the Chinese market.
Research on Perfect Diary Product Features and The Choice of Advertising Media
Authors: Chen Peiyun , Xia Mingxi , Zheng Sijia
Published: March 2023

By studying this topic, we can find from the business data of Perfect Diary that China’s local make-up brands have encountered unprecedented development challenges and opportunities. As a new make-up brand, Perfect Diary not only leads similar domestic brands but also breaks the traditional brand marketing model. With the advent of the era of big data, how Perfect Diary is launched and promoted on social media and various platforms is worth studying and learning. During the investigation, this paper used the following methods: Case study, Literature research, and Comparative analysis. And this paper summarizes the brand a few points: Industry Status, Behavioral characteristics of consumers, Consumer Characteristic Analysis, and Problems with Perfect Diary. Through the discussion, this paper finds the loopholes in the brands that are operated through self-media today. Moreover, this paper also finds solutions to the existing problems, which is also the key to promoting the development of the media industry.