ISSN 2960-1312(Online) Editor: Ji Chen (Denver University), Alexei (Columbia University), Aytek Erdil (University of Cambridge), Cosimo Arnesano (University of Southern California), Freya Baetens (Cambridge University), Osman (Carnegie Mellon University) Finance & Economics serves as a dynamic platform for scholars, practitioners, and students to exchange their latest research and insights in the fields of finance and economics. The journal stands out for its comprehensive coverage, spanning traditional topics such as investment, banking, and financial markets, as well as emerging areas like behavioral finance, fintech, and sustainable finance. This broad scope ensures that readers stay informed about the most relevant and cutting-edge developments in the discipline. Additionally, Finance & Economics places a strong emphasis on the practical applications of research, fostering studies that offer real-world implications for policy formulation and business decision-making. This commitment to bridging theory and practice makes it an essential resource for professionals in finance and economics.
Exploring the analysis of the impact of Tianjin’s economic development on carbon emissions
Amid the swift expansion of the global economy, environmental issues in China have garnered increasing scrutiny. Along with the increase in China’s economic development level, the total amount of carbon emissions in China is also rising. As one of the economically developed cities in northern China, Tianjin will inevitably impact the environment during its development. This paper explores the factors affecting carbon emissions in Tianjin through relevant data from 2002 to 2021, based on the Kaya constant equation and using the LMDI model. It learns that economic development is the main contributing factor to carbon emissions and further compares and analyzes the GDPs of various industries in terms of economic benefits. In order to promote the low-carbon development of Tianjin, it should maintain sustained and stable economic growth, formulate low-carbon policies that are tailored to its actual situation, transform the economic development model, restructure the industry, and promote the ideology of sustainable consumption, among other measures.
The Impact of Climate Risk Perception Bias on Corporate Investment Efficiency: Evidence from China
As a long-term systematic risk factor that affects corporate earnings, climate risk profoundly impacts corporate behavior and decision-making. By making reasonable judgments about climate risk and adopting corresponding countermeasures, companies can mitigate inefficient investments resulting from biased perceptions of climate risk. This study analyzes the impact of climate-related perception bias on inefficient investment decisions among A-share listed companies in China from 2011 to 2023. The results demonstrate that biased perceptions of climate risk significantly increase business investment inefficiency; specifically, a greater degree of climate risk perception bias in a company correlates with a higher level of inefficient investment. The research fills the gap between climate risk perception and investment efficiency, providing valuable insights for policymakers and senior company management.
Intelligent Analysis Methods and Methodology of Banking Regulation Rules - Real Issues and Improvements in the Implementation by Commercial Banks
Banking regulation rules serve as the institutional basis for promoting commercial banks’ healthy and sustainable development. The linguistic complexity within the regulation discourse system leads to challenges in overall comprehension and execution, as well as disparities in interpretation and enforcement. By introducing intelligent analysis methods, the author conducts comparative analysis and historical research on regulation rules from both crosssectional and historical development perspectives. This approach maximizes the exploration of regulation essence and the identification of laws of change, thus enhancing the effective implementation of regulation rules in the design of commercial banking systems.
How the Hope of Profit Engenders Economic Behaviors
The hope of profit creates incentives rooted in the prospect of residual profits, motivating firms towards cost minimisation, revenue maximisation, and innovation, but potentially also towards opportunism or externalising social costs. Whether such behaviour is better or worse requires an evaluation of which ownership structures magnify societal welfare. While profit incentives may cause cost-cutting behaviours and inefficient resource allocation in private industries, the absence of it government and charity-run industries often leads to a higher quality baseline in essential services, better welfare, and reduction in deaths. By focusing on an unregulated baseline, the article employs Hart et al.’s (1996) model of optimal ownership structure to sort industries into four quadrants based on varying hidden-harm potential and innovation-payoff levels. Under each quadrants, case studies on welfare, customer satisfcation, and service quality are provided and analyzed. Overall, it argues that an economy made up entirely of public and charity-run enterprises would, on balance, engender better behaviour.
How Interest Rates Affect U.S. Commercial Banks
This article explores how interest rate fluctuations impact U.S. commercial banks, focusing on the 2022–2023 period when the Federal Reserve sharply raised the federal funds rate to combat inflation. This article finds that rising rates widened net interest margins, boosting banks’ net interest income (NII). However, higher rates also brought challenges. Exemplified by Silicon Valley Bank (SVB)’s collapse, this article notes that the market value of banks’ long-term fixed-rate assets plummeted, leading to widespread unrealized losses. Moreover, deposit flows shifted, with large banks gaining deposits post-SVB failure, while regional and mid-size banks faced outflows and had to raise deposit rates to compete. By early 2023, funding costs rose and loan growth slowed, pressuring NII. The article further examines banks’ interest rate risk management strategies, including asset-liability management (ALM), financial derivatives, and regulatory stress tests, noting gaps in pre-2023 stress scenarios. It highlights that effective governance and diversified operations can mitigate risks, while poor risk management led to failure. The 2022–2023 experience also underscores that prudent rate risk management turns rate hikes into opportunities, while mismanagement increases vulnerability.
A Study on McDonald’s Marketing Strategy – Audience, Offerings, GTM, and Growth
This study analyzes McDonald’s positioning and competitive dynamics in China’s quick-service restaurant (QSR) market through the lenses of brand meaning, target consumers, product strategy, and communication pathways. Drawing on illustrative evidence from field observations and survey responses, triangulated with public information on store density and price tiers, we identify growth drivers and constraints and propose improvements that balance standardization and localization. Structurally, the paper foregrounds a causal chain—audiences- contexts- offerings- conversion—and presents arguments in integrated prose rather than bullet points.
Interest Rates and Subnational Finance:How China’s Local Governments Manage Interest Rate Risk
This paper analyzes how interest rates affect China’s local governments through their on-budget local government bonds (LGBs) and off-budget Local Government Financing Vehicles (LGFVs), and evaluates the main tools used to manage interest-rate risk. Using a policy-anchored case study drawing on fiscal documents, central-bank communications, and market research from 2021–2025, I trace four channels: refinancing costs, debt-service burdens, project valuation, and market access via spreads. I then assess the effectiveness of debt-refinancing programs and related governance frameworks. I find that the 2024–2025 environment of stable policy rates alongside targeted refinancing reduced average new-issue LGB coupons versus 2023, easing near-term cash-flow pressure. However, benefits are uneven: weaker LGFVs continue to face rollover constraints and limited access to derivative hedges, leaving residual vulnerabilities. The paper highlights implications for fiscal sustainability and outlines directions for microdata-based evaluation of risk transfers between budgets and LGFVs.
The Impact of Interest Rate Fluctuations on Commercial Banks and Their Risk Mitigation Strategies
This thesis investigates the heterogeneous effects of interest rate fluctuations on commercial banks and assesses the effectiveness of their risk mitigation strategies, with a focus on the 2022–2023 U.S. Federal Reserve rate hike cycle (0.25% to 5.5%) as a critical empirical context. By integrating theoretical frameworks, quantitative data analysis, and comparative case studies, it examines how large international banks and small/regional banks differ in their exposure to rate risk and risk management practices. Key findings include: 1) Interest rate hikes enhance net interest income (NII) for large banks with positive repricing gaps (e.g., JPMorgan Chase’s 40% year-over-year NII growth in 2022) but cause severe deposit outflows and unrealized bond losses for small banks; 2) Asset-Liability Management (ALM) and financial derivatives are core mitigation tools, yet small banks lack access to derivatives (only 15% of U.S. small banks use interest rate swaps, compared to 75% of large banks); 3) Failures like Silicon Valley Bank (SVB) result from neglected duration risk and over-reliance on uninsured deposits. The study concludes with targeted recommendations for banks (e.g., small banks adopting cloud-based ALM tools) and regulators (e.g., size-specific stress testing) to strengthen financial resilience amid rate volatility.
Winning Consumer Trust: An Analysis of Xiaomi's Unique Digital Marketing Path
In the context of the global digital economy’s rapid development, the deep integration of the internet and social media has not only reshaped consumer behavior patterns, but also made digital marketing a core driver for enterprises to seize market share and achieve sustainable growth. This paper takes Xiaomi, a representative enterprise in the global consumer electronics and smart manufacturing industries, as a case study. The study reveals that in the pre-launch phase, Xiaomi effectively captures target audience traffic and builds initial brand trust through three core approaches: multi-platform social media synergy, founder-led brand storytelling, and meme-driven user-generated content (UGC) campaigns. After entering the market, Xiaomi further strengthens its competitive edge by implementing a competitive pricing strategy and deepening social interaction. The core logic of these strategies lies in continuous trust penetration (solidifying user trust through consistent brand behavior) and user co-creation (letting users participate in the brand’s value chain to enhance user loyalty). Finally, the paper provides targeted recommendations: for Xiaomi’s global expansion, it suggests adapting digital marketing strategies to local cultural contexts and platform characteristics; for marketing technology upgrades, it proposes increasing investment in big data and artificial intelligence to improve user portrait accuracy; it also offers insights for marketing innovations in other industries, such as the application of the trust + co-creation model in the fast-moving consumer goods and service sectors.
The Impact of Corporate Green Technological Innovation on Environmental, Social and Governance-An Empirical Analysis Based on Green Patent Data from Chinese A-Share Listed Companies
Against the backdrop of China's dual carbon goals, green innovation has become a critical pathway for enterprises to achieve sustainable development. This study examines the impact of green patents on corporate Environmental, Social and Governance (ESG) performance using panel data from Chinese A-share listed companies between 2015 and 2023, further exploring the moderating effects of firm size and state-owned attributes. Employing a fixed-effects regression model with interaction terms to capture moderation effects, the findings reveal that: Regression results indicate that the quantity of green patents exerts a significant positive influence on corporate ESG scores, with green innovation activities enhancing overall performance across environmental, social, and governance dimensions. Further moderation analysis reveals that firm size exerts a significant negative moderating effect on the relationship between green patents and ESG performance, whereas state-owned enterprise status does not significantly impact this relationship. This study enriches empirical evidence on the linkage between green innovation and ESG performance, providing a reference for governments to formulate differentiated green policies and for enterprises to implement sustainable development strategies.
Bed Bath & Beyond: Reevaluating Capital Structure for Sustained Shareholder Value
This paper focus on the how Bed Bath & Beyond (BBBY), a key player in the home goods retailing industry, optimize its capital structure to solve the inefficiency of its cash-heavy, without debt strategy and rebuild the positive relationship between capital structure and shareholder value. The main goal is providing feasible measures for BBBY and similar retail companies that facing parallel financial situation with long-term shareholder value growth. The study adopts a case-focused research approach. Firstly, analyze BBBY’s business model and current capital structure characteristics to identify its issues; then evaluate the potential of strategic adjustments; and use cross-industry corporate cases to illustrate common challenges in capital structure management. Key research results include identifying the inefficiency of BBBY’s conservative capital structure and verifying that targeted adjustments can enhance indicators like EPS and reverse return dilution. The research concludes that BBBY’s capital structure requires dynamic optimization based on market conditions, and similar retail enterprises should balance liquidity with capital efficiency—offer practical references for managers in retail and consumer-facing sectors to improve capital structure decision-making.
Youth sports software market has been a fast-growing market. In this paper, we explore the market definition, current market size and future growth rate, and further examine its core target customers, software platforms and competitive landscape. Looking forward, we analyze the driving forces for this market growth and highlight the major market trends in the youth software market.
Analysis of the Business Model for New Energy Vehicles Surpassing Traditional Fuel Vehicles in Chinese Market
Under the backdrop of low-carbon transformation in the global automotive industry, New Energy Vehicles (NEVs) in Chinese market have achieved market dominance over traditional Internal Combustion Engine (ICE) vehicles through business model innovation. This study employs case analysis and SWOT methodology, focusing on leading NEV manufacturers in China (Tesla, BYD, NIO, Huawei, etc.), to systematically examine successful innovations in three key areas: sales strategies, product definition, and ecosystem development. Key findings include: 1. Motor technology has disrupted the engine performance-based premium pricing system; 2. Integrated hardware-software-aftermarket ecosystems have established new competitive barriers; 3. Significantly shortened R&D and manufacturing cycles have transformed traditional automotive development systems; 4. Direct/hybrid sales models have markedly improved channel efficiency and quality (35% increase in customer satisfaction). The research confirms that NEVs' competitive advantage stems from "technology + model" dual drivers, while also highlighting challenges including inadequate charging infrastructure (rural coverage <12%) and consumer concerns regarding safety and range. The core contribution of this study lies in demonstrating that Chinese NEV leadership stems not merely from technological breakthroughs, but more fundamentally from systematic business model innovation. These findings provide both a replicable framework for traditional automakers transitioning to electrification and new market entrants, as well as theoretical foundations for policymakers to optimize industry support measures. NEV business practices are actively redefining the competitive rules and development trajectory of the global automotive industry.
Analysis of Global Expansion, Sustainability Challenges, and Strategic Responses on Shein's strategies
This study examines Shein’s ultra-fast fashion model and its global expansion strategy. The research focuses on how Shein competes with traditional well-established brands like Zara and H&M in the fast fashion industry through digital marketing and cost-effective operations. At the same time, Shein also faces risks related to sustainable development, policy regulations, and brand reputation. This article employs the PESTEL and SWOT frameworks to conduct a systematic analysis of the external environment, internal strengths and weaknesses, and deeper social environmental impacts from different perspectives and disciplinary viewpoints. The final research structure indicates that Shein’s rapid growth has significant advantages in terms of efficiency and market penetration. However, its low-cost production and manufacturing model, as well as its lack of originality, have led to insufficient long-term competitiveness. The research has put forward many strategic suggestions targeting Shein's weaknesses, including accelerating the transformation towards sustainability, ensuring transparency in the supply chain, diversifying the brand, and deepening digital applications. Overall, this article provides a useful reference for ultra-fast fashion e-commerce to achieve sustainable growth under the global environmental, social, governance (ESG) expectations.
Logistic Regression for Customer Churn Analysis: The Role of Data Proportion and Class Balancing in Model Performance
Customer churn prediction has become a critical challenge for the banking industry, as retaining existing clients is often more cost-effective than acquiring new ones. This study applies logistic regression to the Bank Customer Churn dataset (Kaggle, 2017), which contains 10,000 records and 13 features. After preprocessing, including removal of irrelevant identifiers, categorical encoding, and feature selection, seven key variables were retained. The research explores the impact of training set proportions (50%, 60%, 70%, 80%) and class balancing techniques (oversampling vs. no balancing) on model performance. Results show that model accuracy remains stable at approximately 0.81 across different training ratios, suggesting that increasing training size does not yield significant gains. In contrast, balancing the dataset reduced overall accuracy (0.72 vs. 0.81), reflecting the trade-off between accuracy and minority class recall in imbalanced classification. Logistic regression coefficients further revealed interpretable patterns: customers in Germany had higher churn odds, while active membership, longer tenure, and multiple product ownership reduced churn likelihood. These findings contribute to understanding how data preprocessing choices affect churn modeling outcomes and provide actionable insights for banking institutions seeking to strengthen retention strategies.
POP MART Marketing Strategy and Innovation Path
Since its creation 12 years ago, Pop Mart has succeeded in transforming from a simple and small toy collection shop to a famous IP brand that primarily develops its pop toy products. This study contributes to the present literature from two aspects. First, this study uses 4Ps model to analyze the marketing strategy of Pop Mart. Second, Pop Mart's segmentation, targeting and positioning analysis to propose ideas and suggestions for its future development strategies in accordance with the circumstances of the moment and the prevailing economic climate. Through detailed analysis, the paper attributes Pop Mart’s success to its scarce marketing strategy on the product, channel and user sides. The paper also identifies existing problems beneath the current marketing strategy, including market backlash, the risk of an uncontrolled “yellow cattle” economy, and the dilution effect of industry homogenization. To resolve these issues, the paper puts forward constructive suggestions, such as managing scalpers, adopting a more diverse scarcity model to invoke differentiated satisfaction in customers, and transitioning from limited editions to backstories as the core of its IP content.
Analysis of the Impact of Equity Structure on the Capital Market Performance of Technology Companies in the Initial Stage of Listing
This study takes Xiaomi Group and Gold and Silver Cat Group Limited in the Hong Kong stock market as samples, focusing on the impact of equity structure on the capital market performance of technology companies in the early stage of listing. Among them, Xiaomi adopts a dual shareholding structure, while Golden Cat and Silver Cat are "same shares and equal rights" and the equity is dispersed; Through the calculation of cumulative excess return (CAR) and the analysis of price-earnings ratio and other indicators through the event research method, it is found that the trend of CAR in the early stage of Xiaomi's listing is stable, and the price-earnings ratio shows a recovery trend in the later stage, showing strong market and valuation resilience. This study finally points out that the equity structure is the core factor that determines the performance of the capital market in the early stage of listing to a certain extent, and the dual equity structure is significantly adaptable to ecological technology enterprises.
The Test of ARIMA's Stock Price Prediction Capability in Stable and High-Variability Scenarios - A Comparative Study Based on Guizhou Moutai and NVIDIA
The stock market is the "barometer" of the economy. Stock price forecasting is core focus of investors. Time series models like ARIMA are widely used for this purpose. However, the stock market’s high volatility challenges the model’s universality. This study selects two stocks with distinct price characteristics: Kweichow Moutai (relatively stable stock prices) and NVIDIA (significant price fluctuations driven by major positive news) as research objects. ARIMA is used to predict their price. RMSE is used to assess how accurate the predictions are. Major events that happened to the two companies are examined to explain prediction deviations. Results show that when predicting Kweichow Moutai’s stock price, the ARIMA model achieves high accuracy. However, when it comes to the task of predicting NVIDIA’s stock price, a striking and persistent gap emerges between the forecasted figures and the actual market outcomes. This pronounced discrepancy underscores a critical weakness in the models employed: they appear to falter precisely when confronted with sudden, high-impact shocks—such as unexpected regulatory announcements, geopolitical flashpoints, or abrupt shifts in consumer demand—that lie outside the historical patterns on which their parameters were trained.
Analyzing Production Efficiency and Scale Economies: A Cobb-Douglas Model Application on TSMC
This study will utilize the Cobb-Douglas production function to analyze the production efficiency and cost minimization problems of TSMC (Taiwan Semiconductor Manufacturing Company). By using linear regression to analyze the annual reports of TSMC from 2015 to 2023, the major goal of this report is to determine the total output (annual revenue) and to estimate the total factor productivity (A). The results shown indicate that the production process of TSMC is very consistent with the regular scale revenue estimation, and the elasticities of labor and capital, respectively, are 0.55 and 0.43. This shows the labor cost is slightly higher than the capital cost. Moreover, the estimation of total factor productivity (A) reflected that TSMC has high technological efficiency and is constantly improving its productivity. This study further discusses the results based on linear regression, how to improve resource allocation and promote productivity efficiency, and provides some recommendations, such as technological innovation, capital use efficiency improvement, green manufacturing, and global market layout. Lastly, this report provided beneficial references on effective production management for semiconductor industries and offered some useful insights for other technical industries.
Exchange Risk Management of Multinational Enterprises under the China-US Trade War: Case of Yutong Packaging
After the outbreak of the China-US trade war in 2018, tariffs and exchange rate fluctuations increased the uncertainty of transaction costs for multinational enterprises, making foreign exchange risk management a critical issue for companies to cope with the impact. Yutong Packaging Technology is one of the world's largest producers of premium paper packaging. As its customers are spread all over the world, the China-US trade war is certain to expose the company to exchange risk. This paper uses Yutong Packaging as a case study and finds that under the environment of the China-US trade war, Yutong Packaging effectively avoided exchange rate risk through foreign exchange hedging operations, buffered the impact of foreign exchange losses on profits, and ensured the stability of profits from overseas businesses. This study enriches the practical application of risk management and financial strategy theories and provides feasible foreign exchange risk management approaches for export-oriented multinational enterprises.
How Green Financial Instruments Mitigate Climate Risk: A Case Study of Build Your Dream's Green Bonds
Climate change poses a significant risk to the global economy, including physical risks such as extreme weather and transition risks like carbon tariffs. The paper discusses Green financing, such as green bonds, as effective measures to address the risk associated with climate change through funding sustainable projects. This paper revolves around how Build Your Dream (BYD), a leading Chinese new energy vehicle company, leverages green bonds to mitigate climate risks. This study further analyzes BYD's climate exposure, details of its green bond issuance like "19 Yadi G1", and the mechanism through which these green bonds are set to reduce these risks. This research reveals that BYD suffers from physical risks at the production stage, and most of these risks result from changes in climate events and transition risks from carbon tariffs. Introduction factors such as low-carbon technologies, energy storage, and effective infrastructure have improved BYD's environmental performance, reducing financial cost and enhancing its market reputation. The Green bonds support low-carbon innovation, help it comply with carbon markets, and fund resilient infrastructure, ensuring its alignment with China's "Dual Carbon" goals (Carbon peak by 2030, neutrality by 2060). The research shows companies reacting positively to green bonds, as indicated by increased stock price and Environment Social and Governance (ESG) ratings for the certified bonds. The case study reflects how green bonds can manage climate risk while delivering financial and environmental benefits to the industry. The research recommends a stronger market in Canada and globally to support sustainable development.
Beyond Nation Averages How Vaccine Hesitancy and Perceived Barriers Warp the Relationship between Vaccination Coverage and Disease Incidence
Whereas there is a theoretical negative relationship between vaccination rates and the occurrence of disease, administrative-level data is often unable to represent the distorting impact of local vaccine hesitancy. By a comparative analysis of China, the United States and Nigeria, this paper shows that non-significant findings in national level analysis accurately show the critical nature of perceived barriers (such as the transportation costs, religious resistance) and some cues to action. This leads to the breakdown of the protective effect of high overall vaccination coverage by forming groups of vulnerable people. The conclusion drives home the importance of using finer-grained data to extract the moderating role of vaccine hesitancy and suggests a policy shift toward targeting and interventions at localized levels rather than national overall averages. Consequently, understanding and addressing community-specific attitudes is essential for designing effective immunization programs. Future research should therefore prioritize the collection and analysis of sub-national data to better identify and resolve disparities in vaccine access and acceptance.
Report on Foreign Exchange Risk Management Solutions-The Walt Disney Company’s Financing
In order to solve special foreign exchange risk problems, this report takes Walt Disney Company as a typical example. It first collects global foreign exchange data in 1985 comprehensively, then discusses the advantages and disadvantages of ordinary hedging tools including forwards, futures, and options in financial risk management. What’s more, it also deeply analyzes the benefits of the special method of swap trading when foreign exchange risks occur, exploring how swap transactions can better match the long-term and complex risk exposure of enterprises. The study found that Goldman Sachs’ method, which involves issuing ten-year ECU euro bonds and converting them into yen liabilities through currency swaps, can effectively avoid the shortcomings of ordinary hedging tools. It not only successfully solves the problem of foreign exchange risks, but also provides a valuable reference for enterprises to face risk management in the future, especially for multinational companies dealing with cross-currency and long-term financial risks.
Research on the Deep Demand of guesthouse Social Media Marketing for Generation Z
Contemporary' Generation Z' has a consumer demand for personalized experience in the hotel market. The consumption attribute of "pursuing uniqueness, paying attention to experience and preferring to socialize" has already occupied a dominant position in the hotel industry today, which has forced the hotel marketing logic to change accordingly, and narrative communication of new media is one of the ideal ways to adapt to this trend. Therefore, this paper discusses the methods to meet the uniqueness of the Z generation, and finds that there are some shortcomings in the current guesthouse marketing, such as homogenization of content, superficial narration and dislocation of channels. The reason is that it does not pay attention to the unity of the needs of the Z generation in three aspects: "experience+emotion+socialization". Starting from refining the needs of the Z-generation group, this paper proposes to build a "three levels of innovation" in the product and marketing of guesthouse from "deep extraction of cultural symbols-multi-platform narrative matrix-user co-creation precipitation", which is helpful to help guesthouse get rid of the fate of "traffic is king" and realize an advanced "Z-generation business model" whose value is determined by its intrinsic value.
The Practical Logic of Chinas Fintech Planning and Governance and Global Mirror: A comparative study based on China, Europe and the United States
In the era of digital economy, fintech, as a deep integration of finance and technology, is reshaping traditional financial landscapes and playing a pivotal role in fostering financial innovation and economic growth. However, existing studies lack a comprehensive analysis of its ecological synergy and differential impacts across institutions and regions. Through literature review and case analysis, this study examines the driving forces, economic effects, and influencing factors of fintech development. The findings reveal that while fintech—propelled by technological advances, policy guidance, and market demand—enhances financial efficiency and promotes economic growth, it also introduces challenges such as data security risks and regulatory adaptation. The study further identifies distinct governance models in China, the U.S., and the EU, highlighting China’s planning-led approach with its phased evolution and central-local coordination. Future efforts should focus on strengthening technological integration, improving regulatory frameworks, and fostering cross-border cooperation to support the high-quality development of fintech in a global context.
Using Machine Learning- based Linear Regression to Analyze the Impact of M2 on the Stock Market Index from China
This paper investigates whether money supply (M2), as published by the People’s Bank of China, can significantly explain or predict fluctuations in China’s stock market, represented by the Shanghai Stock Exchange Composite Index. Using monthly data from June 2015 to June 2025, the research constructs a regression model with Python’s scikit-learn Linear Regression tool. Both variables are log-transformed, and the dataset is divided into training and testing sets to evaluate predictive performance. The model results indicate a positive correlation between log(M2) and log(SSE), but the explanatory power is extremely limited, with R² values close to zero and even negative in the testing set. Error metrics such as MSE, MAE, and RMSE further reveal that prediction accuracy is weak and unstable, with results often distorted by policy interventions and institutional frictions. These findings suggest that while M2 has some influence through the liquidity channel, its role is indirect and fragile in China’s policy-sensitive market. By integrating traditional financial theory with machine learning validation techniques, this study provides transparent visualization, predictive testing, and policy insights, offering quantitative evidence for understanding the complex interaction between monetary policy and the Chinese capital market.
The Impact of FinTech Development on SME Credit Access in China: Evidence from Provincial Data
The rapid rise of Financial Technology (FinTech) has reshaped the landscape of inclusive finance in China. Against the backdrop of national policies such as the FinTech Development Plan (2022–2025), this study examines whether provincial-level FinTech development is linked to the distribution of credit between small and medium-sized enterprises (SMEs) and larger firms. Using panel data from 31 provinces in China from 2011 to 2020 and applying a univariate linear regression, the study examines the relationship between the Digital Inclusive Finance Index and the share of SME loans in total provincial loans. The results show a strong negative link. This means FinTech growth is tied to changes in how credit is shared, not to the total amount of SME credit. The change is different across regions. Eastern provinces have more balanced results, but central, western, and northeastern regions see bigger drops in SME loan shares. The policy meaning is clear. Different places need different plans. These plans include building more digital infrastructure in regions that fall behind, using both old and new credit models, and making the sharing of financial resources fairer for all.
The Evolution of Financial Engineering: A Cross-Era Comparative Analysis of Disney’s Yen Financing and Mercedes-Benz’s Green Panda Bond
This paper presents a cross-era comparative analysis of two typical cross-currency financing transactions: The Walt Disney Company’s 1985 ECU-bond-to-yen swap and Mercedes-Benz’s 2022 green Panda bond. The study of these cases shows how financial engineering has changed to meet new corporate goals and regulatory conditions. The analysis reveals three key changes: first, the strategic approach to regulation has shifted from avoidance to integration, using policy incentives to gain an advantage; second, risk management frameworks have incorporated geopolitical and ESG factors in addition to financial ones; and third, success metrics have changed from focusing only on cost reduction to multidimensional value creation that includes sustainability and strategic goals. These findings demonstrate how financial innovation consistently adjusts to institutional settings while upholding its fundamental purpose of maximizing value in the face of limitations.
Analyze the impact of the financial crisis in China since 2020 and evaluate the methods that the banking system can do to prevent this phenomenon.
The COVID-19 pandemic of 2020 served as a trigger, causing economic development around the world to enter a state of stagnation or even regression. Massive unemployment occurred worldwide, supply and demand spiraled downward, individuals lost confidence in the future, many small and medium-sized enterprises went bankrupt, and China lost some of its advantages in export trade. Since the impact of the COVID-19 financial crisis is not yet over and the trigger is different from past crises, fewer scholars have studied this direction, which is a ksy focus of this thesis. This dissertation focuses on analyzing the impact of the financial crisis on China and identifying appropriate banking system solutions. For the impact, the research methodology of primary and secondary surveys was used, and the author interviewed experts in the financial industry and analyzed numerous indicators (including GDP growth rate, inflation rate, international trade, investment, per capita consumption, and the Gini coefficient) in the last ten years. The research results of many famous scholars were also referenced. In terms of solutions, the author refers to the solutions used by the world's major developed countries during the subprime crisis and the financial crisis in the United States and Europe, and derives the solutions that are most suitable for the financial crisis since 2020.
An evaluation of the NBA's Business Model and Market Strategies in China
This study looks at the NBA’s business model and market strategies in China. The focus is on the celebrity effect and revenue diversification. Both secondary sources and a survey of 45 respondents are used. Data are analyzed with descriptive statistics, Pearson correlation, and multiple regression. Results show that celebrity influence strongly raises purchase willingness. Frequent viewership also increases purchase willingness. Revenue diversification provides stability, but it has a less significant impact on consumer behavior. Digital platforms help the NBA reach young fans and expand exposure, but they do not raise purchase willingness much. The findings suggest that the NBA’s growth in China relies more on star-driven marketing. At the same time, digital transformation and local cooperation are key to long-term success.