The rapid rise of Bitcoin, a decentralized digital currency, has attracted significant attention from investors, researchers, and policymakers alike. The relationship between traditional stock prices and Bitcoin prices has garnered considerable attention in recent years. This research paper aims to explore the interconnections and dynamics between stock prices and Bitcoin prices by employing a Vector Autoregression (VAR) model. The study utilizes a comprehensive dataset spanning a specific time period, encompassing daily or monthly observations of stock prices and Bitcoin prices. The VAR model allows for the analysis of the joint behavior of these variables, capturing both short and long-term relationships, showing the effects of stocks on Bitcoin, but not the other way around. The research also underscores the necessity for continuous monitoring and analysis as the cryptocurrency landscape evolves rapidly. It highlights the significance of understanding the intricate dynamics between traditional financial markets and emerging digital assets, such as Bitcoin, in order to make informed investment decisions and mitigate potential risks.

To enhance the accuracy of stock price prediction for Netflix and provide individuals with a comprehensive understanding of stock trading prices, this study constructs a predictive model by employing three distinct approaches: a linear regression model, a Long Short-term Memory (LSTM) artificial neural network, and a Gated Recursive Unit (GRU) which serves as a component of the LSTM architecture. A prediction scheme is devised, utilizing historical stock data spanning from 2002 to 2022 for Netflix. The primary objective is to forecast the stock price of Netflix for the subsequent 20-day period. To evaluate the efficacy of the three models, a rigorous assessment is conducted employing robust evaluation indices. The outcomes of this analysis will enable a determination of the fitting adequacy of each model, thereby facilitating the identification of the most suitable approach for accurate stock price prediction in the context of Netflix. This research endeavors to contribute to the field of stock market analysis by leveraging advanced predictive modeling techniques for enhanced forecasting accuracy and insightful decision-making.

As the development of the globalization, more and more cross-border enterprises choose to come into the China to develop themselves. However, because they lack of popularity, digital transformation become a good choice for e-commerce, and they can use live-stream commerce to enlarge their development of space. Up to a point, live-stream commerce increase the enterprise performance. Use Alibaba as an example, in 2016, through the live-stream commerce platform which is created by Taobao, users can watch the live and buy the commodity which they like at the same time. In this thesis, I will use live-stream commerce as an epitome to show the digitization transference and explore that under the influence of the digitization, enterprises receive the positive effect and future trend.

At present, the losses caused by COVID-19 have affected the economic construction of many countries, but the underlying essence is that the dollar hegemony uses weaponized currency to force other countries to participate in the process of financialization. The dollar's extracorporeal circulation has been affected by the external force of the new coronavirus, making the dollar's control weaker, and many single-industry countries have also derived the idea of getting rid of the dollar's control, which have been solved in countries with strong real economies. By exploring the role of the real economy in combating US dollar hegemony, this paper points out that a country with a strong real economy can make its internal supply chain more complete, create jobs and control inflation at the same time, reduce the possible damage caused by financial risks in the process of dollar hegemony, and play a positive role in the recovery of the economy after damage.

The epidemic has dealt a huge blow to the catering industry. It has led to the closure of tens of thousands of brick-and-mortar restaurant economy. But the rise of AI is bringing huge changes to all aspects of society. A new industrial revolution is imminent. This is a good opportunity to use AI to reinvigorate the restaurant industry. The article suggests and proves the feasibility that the F&B industry should use AI wisely in forecasting demand, inventory management, raw material transportation, food safety, and customer service. So as to improve the operation efficiency of the catering industry supply chain, reduce operating costs, and achieve a certain degree of automation and intelligence. Keeping up with the progress of the times. At the same time, AI also brings problems such as data quality, data security, technology and personnel costs, lack of customer communication, and employee unemployment. However, according to the analyses, these problems are promisingly able to be solved properly eventually with the human acceptance of AI and social development.

The emergence and development of new media have provided new ideas and paths for brands’ marketing strategies, and countless brands have utilized the interactivity and real-time nature of new media to upgrade and transform their marketing and continuously enhance their influence and communication capabilities. HEYTEA is a clear example of using the new environment to create brand value. Through the case description, this paper will consider and study the brand communication behavior and unique marketing strategy of HEYTEA in new media. It will analyze how to make use of external opportunities such as the fast-emerging consumer groups and the fast-developing Internet and new media to overcome the problems of serious homogenization, over-marketing, weak public relations, and lack of community interaction, and explore the background reasons for these problems. Based on the issues identified, this paper will summarize the effective promotion path of the brand in the new media environment, further improve the marketing strategy of HEYTEA, and put forward practical suggestions and measures to provide consumers with more diversified services and products. The research in this paper can not only promote the optimization of HEYTEA’s marketing strategy but also provide inspiration and reference for other tea brands in the industry, guiding more brands to adapt to the new media development environment and realizing the innovation and progress of the industry.

This research paper explores the relationships between West Texas Intermediate (WTI) oil prices and various macroeconomic indicators. Given the significant role of WTI prices in shaping global economic activities, understanding their volatile dynamics is crucial for numerous industries. Predicting these prices, however, poses significant challenges due to the complex nature of the oil market, influenced by myriad factors such as geopolitical developments, supply-demand imbalances, and diverse macroeconomic parameters. The research addresses this issue by developing a predictive model for WTI oil prices, deploying an Autoregressive Integrated Moving Average (ARIMA) model. The study has a selection of macroeconomic variables that accurately reflect the global economy's various aspects influencing WTI prices. These include the NASDAQ index, the US Dollar Index (DXY), the Economic Uncertainty Index, the 5-Year Inflation Break Even, the US 3-Month Treasury, the 10Y Less 2Y, the US Oil Demand, and the difference between oil Demand and Supply. This research aims to deepen our understanding of the multifaceted relationship between WTI oil prices and these critical macroeconomic indicators. In doing so, this study offers substantial academic contributions to comprehending oil price dynamics. Additionally, it provides valueable insights for industry stakeholders, financial analysts, policymakers, and investors, enhancing economic planning and risk management across sectors.

Nowadays, the traditional economic development mode and development power have caused a series of problems such as waste of factor input, serious environmental pollution, and low economic efficiency. Green finance is thus sprouting. With the rapid economic development, more and more companies at home and abroad have begun to use Green Credit Policy (GCP) to promote sustainable development. Based on official publication databases, we delve into a deep analysis of the impact of the Green Credit Policy on companies, focusing on their industrial structure, firm performance, and response measures. Through empirical analysis and theoretical discussions, we reveal that the Green Credit Policy positively influences industrial upgrading, enhances firms’ environmental performance, and stimulates strategic responses to Green Credit Policy. Additionally, empirical data substantiates the notion that GCP exerts a "detrimental impact" on companies exhibiting subpar environmental practices. These results underscore the importance of policies geared towards sustainability in fostering a more eco-friendly and robust economy.

Based on data of China's open equity and partial equity hybrid green funds from 2018 to 2022, this paper conducts the sharp style analysis model to construct green fund style drift indicator, and apply the TM model to construct stock selection and timing indicators. Moreover, this paper constructs a panel fixed-effect model to empirically analyze the impact of green fund style drift, stock selection and timing on green fund performance. This research finds that there is a drift of investment style in green funds. Such style drift and timing have a negative impact on the performance of green funds. Stock selection has a significant positive impact on green funds. Furthermore, this research introduces style drift, stock selection and timing indicators into green fund performance evaluation, and use principal component analysis method to build a green fund performance-evaluation system. Then, this paper applies the rating system to the existing green fund market and effectively supplements the existing rating system.

Artificial intelligence(AI) is facing rapid development, which presents both opportunities and risks. The Unities States, the world’s largest economy and a leading technological power, has witnessed significant advancements in AI. As an integral part of automated production, AI drives economic productivity, but it alters the demands and structure of the United States labor market. Increasing joblessness and a decrease in the number of people actively participating in the workforce imply that AI holds the capability to substitute human employment, thereby highlighting the importance of individuals adapting to changing labor demands. Research indicates that individuals with lower educational attainment and limited cultural proficiency face a greater likelihood of being replaced by artificial intelligence (AI). However, the evolving labor market demands a greater emphasis on AI-related skills. The potential of AI to foster the development of the United States labor market is evident, as it holds the capacity to drive further innovation and growth in the American economy. This research paper takes IBM, who officially announced the use of AI as a replacement for human labor, as a case study to examine the influence of AI on the labor market in the United States., exploring the opportunities and risks brought by AI development.

Against this background, the primary objective of this study is to analyse the variables and underlying causes that contribute to the potential collapse of Silicon Valley Bank (SVB). Based on extensive research and analysis, the internal structure of SVB reveals that several key causes have contributed to the company's bankruptcy. These elements include the adverse economic conditions, the impact of the pandemic, government policies, and internal management issues inside SVB. The findings of the research underscore the impact of the prevailing economic downturn and the decision of the United States government to raise interest rates on SVB, a financial institution with a singular portfolio. Consequently, SVB is compelled to address the dearth of capital by consistently liquidating its assets. The failure of SVB Bank can be attributed to its tight association with the financial market and the overall state of the economy. The potential collapse of a financial institution might exert adverse effects on the overall stability of the financial market. Hence, it is contended that organisations should pursue portfolio diversification, enhance their liquidity management, and safeguard their cash-based assets in order to mitigate risk diversification.

In the context of the digital economy, rural e-commerce, as an emerging business model, plays a significant role in promoting rural economic development. However, there are challenges in its development. This paper first conducts an in-depth analysis of the development status of rural e-commerce in Yunnan Province, identifying a series of challenges it faces, including inadequate infrastructure and logistical difficulties. Subsequently, through theoretical analysis, the paper proposes a set of solutions and strategies for the development of rural e-commerce. These solutions mainly include strengthening rural e-commerce infrastructure construction and improving network coverage, enhancing rural e-commerce talent development, raising awareness and skills among farmers, and strengthening government support and policy guidance to provide a better development environment and policy support for rural e-commerce. The research results of this paper contribute to further promoting the development of rural e-commerce and fostering rural economic prosperity.

Management economics, as a branch of economics, helps businesses and individuals systematically and logically formulate plans and decisions, and its application in management practice makes an indispensable contribution to society. This article takes Apple and Huawei as examples, and based on existing literature, analyzes the application of management economics theory in enterprise marketing management through case analysis and data analysis. This article finds that both Apple and Huawei cleverly and flexibly apply the four core theories of management economics. As excellent enterprises, both brands actively explore the potential needs of customers and help them seize the market faster. Apple actively collects user feedback, responds to and solves user issues and opinions in a timely manner, which helps them better understand consumer needs and expectations. Huawei has always been committed to deeply understanding customer needs. The results indicate that each company has its own unique operational approach, but it is worth noting that companies that want to succeed should start with organizational structure, optimize personnel management, clarify market goals, upgrade products targeted, capture customer groups, and establish good communication; All of these are key factors for the sustainable development of the company.

Yield Curve Control (YCC) is fundamentally an interest rate tool that aims to maintain the yield curve at targeted levels across different maturities. The Bank of Japan (BOJ) initiated zero interest rates and quantitative easing in 2001, followed by qualitative and quantitative monetary easing policies starting in April 2013, and introduced negative interest rates in January 2016. It announced the implementation of Yield Curve Control policy as a policy objective for quantitative and qualitative easing. Amid the current global economic downturn, many Western countries have adopted interest rate hikes to ensure currency stability. However, Japan continues to implement Yield Curve Control policy to address the global economic slowdown. This paper, based on literature review and utilizing Japanese economic data from 2003 to 2022, employs correlation and regression analyses to delve into the impact of Yield Curve Control on the Japanese yen’s exchange rate and inflation. The study reveals that Japan’s Yield Curve Control policy has a certain positive impact on both the yen’s exchange rate and inflation, although this effect is relatively moderate. Therefore, the government should consider enhancing the use of other monetary policy tools and employing a comprehensive approach to influence exchange rates and inflation more effectively.

This article explores the current status and prospects of machine learning techniques in the stock market of china. It begins by providing an overview of the relevant concepts of machine learning and analyzing its strengths and weaknesses in the stock market context. The article also introduces the current application of machine learning techniques in the gobal stock market. In the methodology section, several machine learning models that have performed well in the stock market are listed. The article then summarizes and analyzes the specific applications of machine learning and its algorithms in the stock market of China, highlighting the advantages and limitations due to the unique characteristics of the market.Finally, the article concludes by summarizing the aforementioned content and providing an outlook on the future development direction of machine learning technology in the stock market of chinese. While the performance of machine learning technology in the stock market has its pros and cons, it is undeniable that it holds an important position in the future development of the financial market, especially within the wave of innovation and progress in the financial industry.

Recently, within the global scope, led by the Saudi League and regional clubs such as Manchester City, some teams have relied on solid capital support to purchase many players, affecting the fairness of the league. At the same time, it has also led to a decline in the quality of matches in major leagues. So based on this, this research decide to Discuss some unreasonable transfers in the world of football today and the significance of capital to the development of major leagues and football. The meaning of discussing this issue is that we hope that by discussing this issue, this research hope to find a suitable way to change the trend of using large amounts of capital to buy players to affect the fairness of the game. Our research searched for controversial deals and then compared the impact of these deals on leagues and teams. In conclusion, while the Saudi leagues and Manchester City's spending power is reshaping global football, it is crucial to balance this with the development of local talent and to maintain a competitive balance in international football. The pursuit of money should not over shadow the essence of the sport. Our research believes that the World Football transactions, such as setting up a wage cap and requiring and managing transactions.

This study looks at how ESG concerns affect the bottom lines of Chinese businesses. China has become the latest country to impose mandatory ESG reporting requirements on publicly traded corporations. This study provides evidence that Chinese firms that put an emphasis on ESG aspects are more likely to have long-term success. Investors should take ESG performance into account due to the beneficial relationship between social and environmental performance and financial success. In addition, regulators might encourage openness and responsibility by making ESG disclosures subject to the “comply or explain” approach. The theoretical foundations of stakeholder and principal-agent theories are investigated alongside recent ESG developments in China and associated laws. The study looked at information from 101 Chinese public businesses Financial success was shown to be positively correlated with social and environmental performance, whereas governance performance had no discernible effect. The study has findings that have important implications for both investors and regulators. The findings show that investors may place greater focus on ESG performance when making investment decisions. The Chinese economy will expand more sustainably if the problems with ESG reporting are solved.

This paper delves into an intriguing phenomenon: the low preference for income redistribution policies among Chinese entrepreneurs when compared to other employment statuses in China. Understanding this unique policy preference is crucial for policymakers aiming to implement effective socio-economic strategies. Drawing comprehensive insights from an array of existing studies and utilizing data from the World Value Survey (WVS), we proposed three hypotheses. These hypotheses were centered around entrepreneurs' education level, their attribution of success to effort or luck, and their inherent trust in the government, respectively.The WVS data supported two of these hypotheses. Firstly, entrepreneurs in China tend to hold the belief that success is mostly attributed to effort rather than serendipity. This belief affects their preference for redistribution policies. Secondly, among Chinese entrepreneurs, there is a lack of confidence in the government's in general, which may extend to their skepticism regarding the government's aptitude in overseeing fair income redistribution.

With the gradual formation of an international consensus on carbon peaking and neutrality, the new energy industry is a key focus for future development. Still, the industry also suffers from a fiercely competitive market environment. Therefore, the innovation performance of enterprises is crucial. This paper analyzes the impact of supply chain relationships and financial flexibility on corporate innovation from a resource-based viewpoint. Moreover, several variables are introduced to explore the optimal combination of innovation strategies. In the empirical part of the study, the study selects the panel data of listed companies in China’s new energy industry. The fuzzy set qualitative comparative analysis approach investigates how supply chain concentration, and financial flexibility affect corporate innovation. The study shows that: corporate cash is the main internal resource for R&D, industrial clusters facilitate the acquisition of external resources, and the configuration of the two can promote corporate innovation; debt and supply chain risk inhibit corporate.

Based on the development of virtual technologies and networks, the virtual idol market is experiencing a remarkable surge, attracting more and more young people around the world, especially in Asia. These virtual icons are increasingly seen as alternative brand ambassadors to traditional celebrities, helping brands broaden their brand image and target audience. A number of well-known brands, including Chanel, Gucci, and L'Oréal, have capitalized on this trend by partnering with well-known virtual icons. In keeping with this trend, some brands have even created their own unique avatars to round out their brand image. Watsons, a chain retailer specializing in personal care products, has launched a virtual ambassador "Wilson". Therefore, this paper discusses the current business value of virtual idols through theoretical analysis and takes Watsons' virtual ambassador as an example. It also analyzes and suggests the marketing strategy of Watsons' virtual idol. The virtual idol market is a new market direction with great potential, but it lacks relevant operation experience to maximize its value.