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.