Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
Javier Cifuentes-Faura, University of Murcia
As the market becomes more transparent and trading strategies become homogeneous, the prediction of prices has become more difficult. This paper has selected the closing prices of the stock market and futures market from 2016 to 2019 and built the VAR model and ARMA-GARCHX models to study the relationship between the closing prices of the stock and futures markets. This paper found that the futures market is greatly affected by the stock market, and the stock market is less affected by the futures market. This paper uses specific data for mathematical modeling analysis, and the results obtained are highly reliable. The model provides a valuable tool for understanding and predicting market volatility, which is essential for investors seeking to make informed decisions in this context. As a result of this study, investors can predict the volatility of the futures market through the fluctuations of the stock market, thereby avoiding risks and improving returns.
This paper delves into the intricate relationship between climate change, extreme weather events, urbanization, and its multifaceted impacts on business and society. It charts the historical trajectory from the Industrial Revolution to contemporary urbanization, revealing the critical role of human activity in driving climate change. The changing interplay between urbanization, industrialization, economic growth, and environmental consequences. Through an interdisciplinary lens, this paper reveals the intricate links between climate change, extreme weather events, and urbanization. The escalating frequency and intensity of extreme weather events, from heatwaves to floods, have ripple effects on economies and communities across the globe. In the midst of these climate challenges, the concept of resilience as a guiding framework has taken center stage in the discussion. Once a psychological construct, resilience has evolved into a multidisciplinary approach to climate risk. This paper explores the collaborative efforts of government, business, and civil society in developing adaptive strategies that enhance climate resilience. It emphasizes the crucial role of business in building climate-resilient supply chains, supporting communities, and promoting environmental sustainability. The need for collective action is emphasized, urging stakeholders to work together to address the complex challenges of climate change. By understanding these interconnections, societies can use adaptive strategies to navigate the changing climate landscape and advance toward a future of shared prosperity, environmental sustainability, and resilience in uncertainty.
This paper provides a comprehensive analysis of the investment potential of office properties in Beijing's Chaoyang District, considering political, economic, and social factors. The analysis highlights the opportunities and challenges in the pre-pandemic era. In terms of political factors, it discusses government policies affecting the supply and demand of office properties, especially in the central business district and peripheral areas. The economic factors section examines the GDP growth trends in Beijing, demonstrating a focus on high-quality growth and the implications for the office property market. It also evaluates the stability and growth prospects of the market based on supply, absorption, and vacancy rate data. Additionally, the social factors analysis considers the impact of technology, transportation improvements, ecological enhancements, and the development of cultural and innovation industries on office property demand. The paper concludes that, despite challenges, Chaoyang District presents substantial investment potential, particularly with the rise of technology and innovation sectors, improvements in infrastructure, and ecological and cultural developments. The study also discusses the lessons learned from the pandemic's impact on the office property market, highlighting the market's resilience and adaptability.
Stock price prediction remains an attractive and essential area in financial markets, with researchers constantly working hard to improve existing models or develop new ones to achieve more accurate predictions. Foreseeing the future direction of stock prices allowing people to plan and formulate effective investment strategies. However, predicting stock prices remains a difficult challenge due to many uncontrollable factors. Traditional forecasting methods rely primarily on economic data analysis and formulation. However, these traditional methods often provide limited information and forecast accuracy due to market uncertainty. Many business organizations and individual investors started to utilize the programmed approaches to improve the accuracy of stock price predictions as machine learning and deep learning capabilities continue to advance. Through an actual case study, this essay examines the innovative use of machine learning methods for researching in the field of predicting stock prices. In the case study, an LSTM model is built to find the transforming trend of the stock price, while Google’s stock price is collected to use as the dataset for training the model. The article finally conducts a comparative study on stock price prediction based on LSTM is conducted to clarify its working progress and accuracy of the outcome.
Murder mystery games have experienced a notable surge in popularity, with their origins deeply rooted in storytelling traditions. This research paper delves into the reasons for their rise, emphasizing the influences of macroeconomic factors, educational trends, and digitalization. These elements not only provided a backdrop for the murder mystery game's resurgence but also played a pivotal role in shaping its contemporary form. A comparative analysis of online and offline modalities reveals distinct user experiences and commercial potentials for each. Furthermore, the research offers pragmatic suggestions for entrepreneurs interested in establishing offline murder mystery stores, underscoring the nuances of market dynamics and consumer preferences. Harnessing statistical data from past survey results and well-informed estimations, the study presents a data-driven exploration into the genre's growth and transformation. By charting the game's historical trajectory and examining its present state, this paper provides a holistic overview of murder mystery games in the modern context and their significance in the evolving entertainment industry.
As the flow of financial capital continues to expand, China's domestic non-financial enterprises have shifted virtual to real to a certain extent and have deepened the degree of digital transformation. In October 2022, China put forward a strategic plan to accelerate the construction of "Digital China", and promote enterprise restructuring through improving digital transformation. This paper explores the impact of enterprise digital transformation on the investment structure of Chinese A-share-listed non-financial enterprises in Shanghai and Shenzhen, taking the A-share-listed non-financial enterprises in Shanghai and Shenzhen from 2011 to 2021 as the research sample. The empirical analysis finds that enterprise digital transformation improves the investment structure of enterprises and promotes enterprises to "shift from virtual to real". Based on this analysis, a heterogeneity analysis is conducted, and it is found that under different internal environments, such as the nature of different shareholdings, the influence of enterprise digital transformation on enterprise investment structure is different.
This study delves into the relationship between the long-term trend of population aging and the risk-free rate against the backdrop of China's diminishing demographic dividend and declining birth rate. It further examines the mechanisms via which population aging affects the risk-free rate. The phenomenon of population aging is distinguished by a rise in the percentage of older individuals and a decline in the percentage of younger individuals, hence exerting a diverse range of effects on the economy. The demographic transition holds significant influence over savings, investment, labor supply, and interest rates, making it a crucial macroeconomic issue. This study employs a literature review methodology and conducts data analysis to construct a "elderly population ratio" framework grounded in life cycle theory. The objective is to investigate the correlation and knowledge significance of the risk-free rate.
On March 17th, 2022, the Federal Reserve issued its first federal funds rate hike to address elevated inflation rates and consumer prices amidst the post-pandemic period. By July 2023, the Fed had raised the rate eleven times, increasing it from 0.25% to 5.50%. These monetary policies not only played a role in stabilizing prices and containing inflation but also contributed to strengthening the U.S. dollar index. This research analyzes the quantifiable impact of these rate hikes on the dollar index by implementing time series models and creating visualizations of daily, weekly, and monthly index trends. Specifically, leveraging data from 2010 to 2023 and utilizing ARIMA modeling, the goal is to provide an understanding of the relationship between the Fed’s monetary policy choices and the standing of the U.S. dollar in global financial markets. A key finding is that there is a positive increase in the dollar index change after the rate hikes compared to no action by the Fed. The daily data is less convincing than the monthly data in reaching this conclusion.
Inequality has always been a topic of discussion among scholars. In this essay, one crucial measure of inequality—the Gini Index—is analyzed to find the influencing factors within the labor market. By running four regressions independently, the labor force changed from being positively related to being inversely correlated, and employment in services changed from being negatively associated to being positively related. The empirical results proved that the labor force, employment in agriculture as a percent of total employment, and unemployment rate are negatively related to the Gini index, and the rest of the variables (employment in service as a percent of total employment and population with tertiary degree) have a positive correlation. More labor force, employment in agriculture, and unemployment rate are accompanied by less Gini index. Take education level as an example; those at the top have better access to education and skill development in economies with significant income inequality, making them more likely to engage in higher-paying service or knowledge-based industries. Meanwhile, those with lower incomes may have fewer opportunities for schooling and are more likely to work in low-wage agricultural or manual labor employment.
Convertible bond is a financing means of both stock and bond, and it is also a refinancing means of listed companies in our country. Based on the study of convertible bonds, this paper analyzes the impact of convertible bond issuance on the financial performance of the issuer, and through the analysis of different financial indicators of China's A-share listed companies, draws the following conclusions: in 2017 and beyond, convertible corporate bonds can bring significantly higher return on total assets, and convertible corporate bonds have forward utility.And put forward the following reference suggestions, for the regulatory authorities, not only to gradually relax the threshold of bond issuers, but also to strengthen supervision. For investors, convertible bond financing can be used as a criterion to screen non-financial companies with a good business environment, and they should also continue to pay attention to the use of funds issued by convertible corporate bond companies.
In the context of information digitization, big data's ascendancy has profoundly impacted industries, especially e-commerce, ushering in a new era of data-driven transformation. The motivation for this research arises from understanding how pivotal big data analytics is in reshaping enterprise functionalities. Utilizing a ten-fold literature analysis, this study explores the interdependent relationship between the Taobao platform and the expansive Alibaba database. The investigation reveals that through big data, Taobao has fine-tuned its strategies, enabling large-scale personalization, accurate market forecasting, and the enhancement of supplier relationships. Such adaptative measures have not only solidified Taobao's market position but have also charted a course for enterprises seeking to harness the full potential of big data. The revelations from this study are seminal, emphasizing that in today's digital milieu, leveraging big data analytics is less of a luxury and more of a necessity for sustainable enterprise growth.
As technology continues to advance and society progresses, the market demand for digital transformation in the banking sector has been growing steadily. This article initiates an internal interview on the digital transformation project of Shanghai Pudong Development Bank (SPDB), and based on this, analyses the specific details and benefits of the project, and puts forward corresponding suggestions for SPDB to smoothly promote the digital transformation project. Through horizontal comparison, the analysis shows that digital transformation projects will bring significant economic and social benefits to SPDB, reducing cost expenditures. Overall, to effectively accomplish digital transformation, it is essential for researchers from diverse fields to collaborate and establish strong connections between various themes and disciplines. This interdisciplinary approach acknowledges the interdependence of business models and underscores the need for concerted efforts in integrating different areas of expertise.
This paper studies the relationship between financial/numeric literacy and household saving and investment behaviors using the New York Fed’s Survey of Consumer Expectations. Using a panel dataset and a regression analysis, the study finds that although overall propensities to save, measured by saving rate and savings-to-wealth ratio, does not show a significant correlation with literacy measures, individuals’ portfolio choices between risk-free and risky assets are indeed affected by both literacy measures. The research indicates that individuals who report higher self-rated financial literacy and attain higher numeracy scores tend to allocate a more substantial portion of their savings into stocks. By contrast, they are inclined to hold a smaller portion of their wealth in risk-free liquid assets, such as checking accounts. More particularly, individuals with higher numeracy scores tend to allocate approximately 5.384% greater portion of their investments into stocks while simultaneously reducing their investments in checking accounts by 4.251%. Similarly, those with higher financial literacy tend to demonstrate an average increase of 10.085% in stock investments, coupled with a decrease of 12.506% in checking account investments. Notably, these effects are separate from influences of other factors like education, gender, and income.
Financial institutions, as the primary entities within the business sector, strive to achieve profitability and long-term expansion as their core objectives. Examining the reciprocal association between the advancement of financial institutions and economic growth through the lens of profit maximization holds considerable merit in enhancing the oversight of financial institutions. This paper examines the reciprocal relationship between financial institutions and local economic development from the perspective of profit maximization theory. It investigates the connection between economic growth and the profit acquisition activities of financial institutions, aiming to contribute to the advancement of local economic development. From the standpoint of profit maximization, the operations of financial institutions contribute to augmenting the momentum of economic progress. However, it is important to note that the unregulated expansion of financial institutions can also heighten the vulnerability of economic development, with potential consequences for excessive profit-seeking. Hence, with regards to the objective of maximizing profits, it is imperative for local governments to effectively oversee and manage financial institutions, establish a comprehensive market management framework, facilitate the well-regulated functioning of financial institutions, and foster the advancement of the economy towards high-quality development.
After the supply chain has gradually become a popular concept for research and attention, its core—logistics system and the debt of enter-prises therein have also been the subject of continuous discussion in the industry and academia. This study centers on the level of logistics in the supply chain and the debt pressure of industrial and commercial enterprises, analyzes the relationship between the two from the supply chain perspective, adopts the literature review method to put forward theoretical hypotheses, and constructs an econometric model and a system of related variables, and uses inter provincial panel data to carry out empirical demonstration of fixed-effects regression analysis. The results found that the logistics level alleviates the pressure of industrial and commercial liabilities, further analyzes the internal mech-anism from the perspective of debt generation and debt realization in each logistics link, and puts forward corresponding measures, which contributes new perspectives to the study of supply chain finance and explains the connection between the two key elements.
When the supply chain operates in an uncertain environment, especially for fashion products with fast changing trends and short life cycles, matching supply and demand is the main task. This requires enterprises to have the ability to analyze risks and manage the supply chain. This paper is mainly about a case analysis of Sport Obermeyer who is confronting two core issues, “Greater products variety and more intense competition have made accurate predictions increasingly difficult” and “How to allocate production between two suppliers”. The key tool to solve these two problems is the Newsvendor Model. Following the principles of the model, the article first calculates the expected quantity and profits of each product. Afterwards, based on the comparison of the mismatch cost of each product, the article provides a preliminary decision. After analyzing the advantages and disadvantages of the suppliers, the article obtains the final result. This process demonstrates some ways on risk analysis and supply chain management and provides some new perspectives for the development of the enterprise and related research in the future.
Disney movies have consistently proven to be a leader in the entertainment industry, not only because of their ability to resonate emotionally with audiences but also because of their outstanding contribution to the economy. At the heart of this economic impact is the exceptional production quality of Disney movies. The dedication to high-quality filmmaking ensures that Disney movies capture the hearts and minds of a wide range of audiences, thus guaranteeing consistent and substantial box office returns. As a giant in the movie industry, Disney does not rely solely on ticket sales; their movies are the starting point for countless other sources of revenue. For example, the demand for related merchandise tends to spike at the same time after each Disney movie is released. From action figures and costumes to bedding and school supplies, Disney-branded products go off the shelves. These merchandise not only boost Disney's profits, but also contribute to the growth of the manufacturing, retail, and distribution industries, which in turn stimulates broader economic growth. In addition, Disney's movies play a pivotal role in the success and expansion of its world-renowned theme parks. Characters and stories from Disney movies come to life in these parks, making them irresistible attractions for children and adults alike. As these parks thrive, so do their neighboring tourism and service industries, contributing greatly to the local economy. On the global front, the universal appeal of Disney movies has ensured the continued health of the worldwide theater industry.
This article explores the importance of the methods in quality control in the semiconductor industry. Three test methods in ABC tronics, a semiconductor company from “Case-ABCtronics: Manufacturing, Quality Control, and Client Interfaces”, will be used to test the data comes from an air quality database available on Kaggle. These data initially taken from Numbeo as an aggregation of user voting. The results of the three different methods are analyzed to draw their respective conclusion, that is whether the investigation report will be accepted or not. In the comparison of three methods, the new testing method is more likely to reject the entire result, and individual chip testing method is a most recommended test method with several advantages. The article emphasizes the usefulness of the findings for other manufacturers in the industry who are looking to improve their quality control measures and maintain high standards of product quality.
In 2022, Louis Vuitton's sales surpassed the historic €20 billion mark and were well ahead of the sales of other competing luxury brands that year. Moreover, compared to the first half of 2022 results, sales in the first half of 2023 continue to rise. Based on this, by analyzing the marketing strategy of Louis Vuitton, this paper can conclude that cooperation with celebrities, co-branding with other industries and deep localization are the three main marketing methods of the brand. In addition, by combining 4Ps marketing theory, the advantages and disadvantages of the company's marketing strategy are analyzed from different perspectives, so as to better understand LVMH's business model and development direction. This essay aims to discuss how exactly these marketing strategies are used to ensure Louis Vuitton’s success.
Since the COVID-19 pandemic outbreak, many studies have explored the impact of the COVID-19 pandemic on financial markets and investors’ decisions. Most of the studies are conducted under the assumption of rationality and efficient market hypothesis, which imply that investors’ decisions are always aiming at the maximum profit. However, analyses of investors’ behaviors during the pandemic with a focus on irrationality are not common. Irrationality is the main theme of behavioral finance, which studies the psychological factors that bias investors’ decisions from rationality. This paper reviews common theories and biases studied in behavioral finance, including heuristics, mental accounting, disposition effects, overconfidence, and anchoring. In this paper, those concepts are linked to the increased volatility and strikes in financial markets during the pandemic. By analyzing the relationship between behavioral finance concepts, hypotheses are given regarding the impact of the pandemic on increase or decrease of the common irrational behaviors in the financial markets, especially in the stock market.