Highlights in Business, Economics and Management
Highlights in Business, Economics and Management is an open access, peer-reviewed publication series published by Darcy & Roy Press. It aims to publish conference proceedings dealing with all areas of business, economics and management, etc.
Analysis of Factors Influencing Consumer Trust in Live E-commerce
With the application of 5G technology in the commercial field, live streaming e-commerce is flourishing in the new era of consumption, where consumer trust is the key to winning the market and the future, as well as a rare resource. This article explores the results analysis of consumer trust from three aspects: consumer behavior, enterprise development, and e-commerce ecosystem, and discusses the influencing factors of consumer trust in live streaming e-commerce based on product, consumer psychology, and e-commerce marketing strategies. The conclusion drawn is that the long-term evolution of e-commerce relies on the sustained trust of consumers. If live-streaming e-commerce platforms can establish and maintain high levels of trust, consumers will prefer to make repeat purchases on the platform, thereby promoting the platform's long-term development. On the contrary, if the platform has false advertising, product quality issues, etc., it will seriously damage consumers' trust and lead to user churn. In the operation of live streaming e-commerce, there are also moral risks such as the "popularity of people" being greater than the "popularity of goods", as well as trust crises and risks such as lack of product authenticity and protection of consumer rights, which require corresponding response strategies. Such as establishing strict admission mechanisms, improving the legal awareness and professional ethics of anchors, and strengthening consumer rights protection.
Copyright (c) 2024 https://creativecommons.org/licenses/by-nc/4.0
Analysis On the Development of Apple Inc. Based on SWOT-Model
The analysis of Apple Inc. was undertaken to understand its strengths, weaknesses, opportunities, and threats (SWOT). Using quantitative research method, the study explored Apple's brand identity, ecosystem synergy, cut-edge technology. The outcome revealed Apple's success in maintaining a strong brand identity through innovation and user-friendliness. However, weaknesses like premium pricing and over-reliance on iPhone sales were identified. The analysis highlighted opportunities in augmented reality and wearable technology. Potential threats included regulatory challenges and intellectual property disputes. Overall, the study provides valuable insights for Apple to leverage strengths, address weaknesses, and capitalize on opportunities to sustain its leadership in the technology industry.
Copyright (c) 2023 https://creativecommons.org/licenses/by-nc/4.0
Assessing Extreme Weather Risks for Insurance Underwriting with ARIMA and Entropy Weight Method: Insights from Brazil and India
As the frequency of extreme weather events increases around the world, it has had a great impact on the insurance industry, especially in Brazil and India, which suffer frequent natural disasters. Insurance plays a significant role in risk sharing and post-disaster reconstruction, but due to the uncertainty of profitability, whether insurance companies should underwrite insurance policies in these areas has become an important issue facing them. Given this, this paper establishes an insurance assessment model based on extreme weather based on ARIMA and entropy weight method and combined with TOPSIS. By evaluating the potential loss and profit of the insurance company after the insurance, to judge whether the insurance company should be insured in the field of extreme weather insurance in a given area. Last, this paper applied our model to Brazil and India, countries that are experiencing severe meteorological disasters, and concluded that it is wise for insurance companies to underwrite policies there.
Gender Discrimination in Fertility and Family Raring in the Contemporary Chinese Family
In contemporary China, gender discrimination remains common in the context of childbearing and family raring, particularly in rural areas. Despite social progress, the traditional son preference continues to influence when families make decisions, resulting in insufficient investment in the education and family investment of girls. Gender discrimination and gender equality is a significant area of research in the present era. The study indicates that there has been some progress in addressing the underlying causes of gender discrimination in the country. However, there is a lack of consensus on the specific factors contributing to gender discrimination within the family, particularly about childbearing and family upbringing. This study aims to elucidate the manifestations of gender discrimination in reproductive attitudes, family educational investments, and parenting styles, and to analyze the impact of these factors on children's emotional, social, and academic development. Accordingly, this paper examines sexism in fertility attitudes and family parenting by synthesizing and analyzing existing literature. The findings demonstrate that gender discrimination not only affects girls' educational opportunities and mental health but also has adverse consequences for mothers. To promote greater attention to gender equality at the familial and societal levels, this paper puts forth policy interventions and cultural shifts that could facilitate more equitable family-rearing and educational environments.
Copyright (c) 2024 Highlights in Business, Economics and Management https://creativecommons.org/licenses/by-nc/4.0
Official and Grassroot Responses to the Japanese Textbook Controversy: A Comparative Study on China and Korea
Japan’s ongoing revision of its wartime history, particularly through its school textbooks, continues to be a major source of diplomatic friction in East Asia, intertwining issues of national identity and collective memory. The intensification of these disputes in 2002 and 2005 marked significant turning points in Sino-Japanese and Korea-Japanese relations. This paper delves into the official and grassroots responses from both China and South Korea, shedding light on the different characteristics exhibited by each country’s approach to manage disputes, as well as the relationship between government-led diplomatic maneuvers and popular nationalist movements. Through a constructivist lens, the analysis reveals how these countries not only react to historical controversies but also play an active role in shaping regional narratives and international perceptions. This study aims to provide a deeper understanding of the nuanced dynamics between official state responses and grassroots movements in China and South Korea as strategic efforts to shape national identity, public sentiment, and international legitimacy.
Analysis of the Success Factors of Peking as a Location
Beijing, as the capital of China, is not only the political centre of the country, but also an important window for international exchanges. The paper takes Beijing as the target city and uses Beijing’s success factors to provide a reference for the development of other surrounding cities. And at the same time, Beijing's development will also drive the development of the surrounding cities, forming an economic circle centred on Beijing, which will be more conducive to promoting the synergistic development of the entire region and achieving a win-win situation.
Copyright (c) 2025 Highlights in Business, Economics and Management https://creativecommons.org/licenses/by-nc/4.0
Research on Strategic Alliance Conflict Issues Based on the GMCR Model
With the rapid advancement of global economic integration and technology, strategic alliances have become an essential means for multinational enterprises to swiftly enter foreign markets and implement globalization strategies. Conflicts among alliance partners significantly impact the stability of alliances and the profitability of enterprises. This study examines the effects of conflict on alliance stability from the perspectives of the causes of conflict and the categorization of conflicts. Furthermore, it employs the Graph Model for Conflict Resolution (GMCR) to model alliance conflicts, paving the way for new approaches to investigating conflict issues within strategic alliances.
Threads of Transformation: Prerequisites and Sustainable Economic Strategies for T&A-Catalyzed Industrialization in Emerging Nations
This paper examines the prerequisite conditions necessary for the textile and apparel (T&A) sector to catalyze industrialization and economic growth in emerging nations. Despite the simplicity of entry into the sector, characterized by its labor-intensive nature, minimal capital requirements, and limited technological expertise, its ability to sustain economic growth hinges on development past critical economic prerequisites. The central thesis argues that emerging nations must transition beyond rudimentary participation in global value chains (GVCs) to adopt economic development strategies in labor, infrastructure, capital, and trade that cultivate intrinsic value and sustain economic success. The four essential prerequisites are labor abundance and integration into GVCs, infrastructural investment, access to capital, and export-import trade policies. This paper explores how these economic fundamentals can develop into long-term growth drivers through human capital development, infrastructure investment and agglomeration economies, financial deepening, and trade diversification. Drawing on key economic models—including the Lewis Dual-Sector Model, Solow Growth Model, Heckscher-Ohlin Model, Marshallian externalities model, and Ricardian Trade Model—as well as case studies from emerging T&A markets and T&A-industrialized global superpowers, the paper underscores the role of industrial policy in fostering value-added production, innovation, and mitigating risks inherent to low-value manufacturing. Ultimately, this paper advocates for a shift from a "bare minimum" approach towards a value-driven economic strategy that supports competitive, self-sustaining T&A industries in emerging nations.
Striking a Balance: Navigating Economic Growth and Environmental Protection Amid Climate Change
This paper explores the critical issue of balancing economic growth with environmental protection within the broader context of climate change. Climate change has become a pressing global challenge, primarily driven by human activities, particularly since the onset of the Industrial Revolution. The rise in global temperatures has led to a cascade of environmental impacts, including rising sea levels, extreme weather events, and widespread ecosystem disruption. These ecological crises pose significant threats to human lives, water resources, and food security, exacerbating the tension between economic development and human survival. However, economic growth and environmental sustainability do not necessarily have to be in conflict. By adopting well-planned sustainable development strategies, it is possible to achieve both. This paper will analyze specific case studies that highlight these challenges and provide policy recommendations aimed at fostering a harmonious balance between economic development and ecological protection. The goal is to offer practical solutions for achieving sustainable progress in the face of the ongoing climate crisis.
The Correlation Between Different Country Stock Market Indices
The main purpose of this project is to explore the correlation between different stock market indices. Using cointegration test to measure the correlation between different countries’ stock market indices to get the results illustrate the strength of the relationship between different countries, thereby helping investors make correct decisions in real investments.
From Green Innovation to Sustainable Development: The Path and Challenges of Improving Corporate Performance
In the face of ever-growing environmental challenges and resource constraints, a feasible approach to sustainable development is the emerging concept of a green economy, which strives to foster an economically circular and regenerative model that is both eco-friendly and socially equitable. In recent years, the concept of a green economy has been gaining traction. This refers to an economic system centered around sustainable development and the utilization of renewable resources. The idea is to create an economy that is environmentally friendly and socially responsible. Embracing a green economy offers numerous benefits, Among its benefits are the creation of employment opportunities within renewable energy sectors, the enhancement of public health resulting from decreased pollution levels, and an increased capacity to withstand environmental hazards. However, transitioning to a green economy requires concerted efforts from governments, businesses, and individuals alike, including policy reforms, Investments in clean technologies, coupled with alterations in behavioral and consumption patterns, are essential. Educational initiatives and awareness campaigns hold a pivotal role in advancing the adoption of sustainable lifestyles and nurturing an environmentally responsible mindset.
The Application and Impact of AI in Human Resource Management
With the advent of the information age, AI has been widely used in various industries. AI technology has penetrated into all aspects of the human resources industry. This paper analyzes the application and current status of AI in various aspects of human resource management. This paper concludes that at present, AI can be used in various links such as information screening in recruitment, enterprise recruitment demand forecasting, personnel management, and personnel process management. The intervention of AI makes the human resource management process informatized, data-based, and accurate. But at the same time, the intervention of AI has also brought problems and challenges to human resource development. First of all, there is the information security problem brought about by big data. Enterprises need to have information security awareness when managing human resources, protect the privacy of employees, and avoid information leakage. Secondly, due to the technical limitations of the algorithm, the calculation results may be biased. Therefore, enterprises should pay attention to the combination of data and manual assessment to make assessment management more fair.
Research on the Relationship between Loyalty and Willingness to Work Overtime of Post-2000 Employees
Post-2000 employees are gradually becoming a new force in the workplace. They have unique value systems and workplace concepts. How to enhance the loyalty of post-2000 employees and reasonably guide their willingness to work overtime has become an important issue. The issue needs to be solved urgently. This research employs a questionnaire methodology to investigate the influence of employee loyalty on the willingness to work overtime among post-2000 employees. Additionally, the research examines the moderating role of salary satisfaction in this relationship. The results demonstrate that the coefficient of employee loyalty is 0.336, and the coefficient of salary satisfaction is 0.228. Furthermore, the significance of both coefficients is less than 0.001, which substantiates a positive correlation between the loyalty of post-2000 employees and their willingness to work overtime. The cross-term between employee loyalty and salary satisfaction is 0.112, indicating that salary satisfaction plays a positive moderating role in this relationship. Based on the research results, this paper argues that companies should improve the loyalty of post-2000 employees, optimize the salary system, and arrange overtime reasonably. Employees should integrate into the corporate culture, improve self-awareness, continuously learn and grow, and find a balance between work and personal life.
Modeling the Influence Mechanism of Hotel Consumers' Purchase Intention Based on Bayesian Networks
This article aims to explore the influencing mechanism of hotel consumers' purchase intention and provide scientific decision-making basis for hotel managers. The research adopts Bayesian network as the theoretical framework and modeling tool, and through multi-channel and multi-level data collection methods, it covers many dimensions such as price, service quality, hotel facilities, geographical location, brand reputation, customer evaluation, personalized service and social media influence. By constructing and verifying the influence mechanism model of hotel consumers' purchase intention based on Bayesian network, this article finds that service quality and customer evaluation have a direct and significant impact on consumers' purchase intention; The price, hotel facilities, geographical location and other factors indirectly affect the purchase intention through the interaction with other factors. Word-of-mouth communication on social media has also proved to play an important role in consumer decision-making. The results of this study deepen our understanding of hotel consumer behavior and provide targeted marketing strategy suggestions for hotel managers.
ESG and Carbon Neutrality Goals: Literature Review and Investment Strategy Analysis
Against the backdrop of escalating global climate change and the pressing urgency to mitigate environmental impacts, achieving carbon neutrality has become a critical focus in transitioning to a sustainable low-carbon economy on a global scale. Within this context, Environmental, Social, and Governance (ESG) frameworks play an increasingly recognized and essential role in supporting low-carbon economic development across various sectors. This paper systematically reviews the role of ESG in achieving carbon neutrality, exploring its effectiveness not only in selecting low-carbon enterprises but also in facilitating the development of robust low-carbon investment strategies. Through a comprehensive literature review, it reveals how ESG frameworks enable companies to undertake low-carbon transformation initiatives and delves into the application of relevant investment tools, assessing their significant contributions to carbon neutrality goals. Additionally, this paper addresses the persistent challenges faced by ESG frameworks, including issues of standardization, transparency, and accountability, and proposes future research directions alongside actionable suggestions to improve the ESG framework to better support the global pursuit of carbon neutrality and a more sustainable future.
Analysis of Different Trading Strategy Applicability to Cryptocurrency Market
Since cryptocurrency trading and regulatory mechanisms are not yet mature, and there are few studies on the applicability of various trading strategies, it is necessary to conduct research on cryptocurrency market trading strategies to promote its healthy development. To this end, using the commonly used historical price data of Bitcoin, Ethereum, and Litecoin, the strategies of pairs trading, momentum trading, and grid trading are applied to analyze their trading characteristics, explore their applicability, and put forward relevant suggestions. The research results show that each trading strategy has its applicable market environment, and the trading strategy should be reasonably selected according to the market situation. Pairs trading uses cryptocurrency pairs with strong correlations to select a reasonable trading range according to their residual swings trend. Its trading volatility and yield are low but relatively stable. Momentum trading is suitable for highly volatile cryptocurrencies. The Moving Average Convergence and Divergence (MACD) and the Relative Strength Index (RSI) can be comprehensively applied to effectively reduce the number of momentum transactions and improve the accuracy of price swings trend prediction. Grid trading can achieve stable and considerable returns in a market with long-term strong volatility, but transactions are more frequent. The number and size of grids should be dynamically adjusted according to the value and volatility of cryptocurrencies and combined with market changes.
Research on the impact of equity pledge loans on financial distress and forecasting ability--Based on the "Factor-Logit" model
China has taken many steps in recent years to improve capital market oversight to guarantee the market's steady and sound growth. One of the most important strategies is to apply ST and *ST warnings to listed corporations that are operating in an unhealthy manner. At the same time, stock pledges are typically preferred by listed company shareholders as a convenient and effective financing option. This study selects financial and corporate governance variables, builds "factor-logit" analysis models to compare the prediction ability, and focuses on pertinent data of equity pledges involving the controlling shareholders of A-share listed companies in Shanghai and Shenzhen from 2003 to 2023. The findings indicate a negative relationship between the controlling shareholder's equity pledge actions and the likelihood of financial difficulties during the next three years. At the same time, the addition of equity pledge data has in fact increased the prediction's accuracy of financial hardship. This finding can give external lenders more precise investment information and has practical consequences for reducing financial crises.
A Study on the Impact of Social Media Marketing on Consumer Purchasing Decisions — A Case Study of Douyin
The rapid development of social media has significantly changed consumer behavior patterns, making online shopping an indispensable part of life. This paper delves into the impact of social media marketing on consumer purchasing decisions against this backdrop. Taking Douyin as an example, the study reveals that content quality, online reviews, influencer charisma, and promotional activities are key influencing factors. The constructed consumer purchasing decision model for social media platforms shows that consumers are influenced by content quality in the awareness stage, by online reviews and influencer charisma in the interest stage, and by promotional activities in the purchase intention stage. The conclusion provides relevant suggestions from the perspectives of consumers and social media platforms, emphasizing that consumers should make careful decisions while platforms should enhance management and optimize marketing to address the opportunities and challenges posed by social media marketing.
Global Economic Governance Mechanisms: Coordination Pathways Between Market Activities and Public Policies
This paper explores the pivotal role of global economic governance mechanisms in coordinating market activities and public policies, as well as strategies to promote sustainable development and effective international cooperation in the context of globalization. However, the globalization of market activities has introduced new governance challenges, particularly in the areas of environmental protection, social responsibility, and the digital economy. This paper analyzes the roles and limitations of current major international public policy frameworks, such as the World Trade Organization (WTO) and the International Monetary Fund (IMF), as well as regional cooperation mechanisms like the Regional Comprehensive Economic Partnership (RCEP), in promoting trade liberalization, financial stability, and sustainable development. Furthermore, it delves into ways to optimize these existing mechanisms to better address emerging economic challenges, particularly in the realms of the digital economy and cross-border data flows. Finally, the paper proposes policy recommendations for constructing new mechanisms of global economic governance, emphasizing multilateral cooperation and the introduction of innovative mechanisms, and calls for a more flexible and effective global governance system to tackle the increasingly complex challenges of the global economic environment.
The impact of Internet media on the stock market
Since mankind has entered the information age, the amount of information has increased exponentially. The Internet has emerged and easily permeated into people's daily lives, influencing the way people obtain information. Information is an important basis for investors' decision-making. Internet information affects the behavior of investors through social media and online news, and then has an impact on the entire stock market. This paper reviews relevant literature and focuses on the impact of Internet media on the stock market.
Research on the Spatial Spillover Effect of Carbon Emission Trading on Carbon Emission Intensity
This article is based on panel data from 30 provinces in China from 2006 to 2019, analyzing the spatial spillover effects of carbon emission trading on carbon emission intensity through spatial econometric models. The empirical results indicate that China's carbon emission efficiency has significant regional differences and spatial correlations. Carbon emission trading can significantly reduce the carbon emission intensity of the treatment area, while also having a suppressive effect on the carbon emission intensity of surrounding areas. Based on the above conclusions, this article suggests promoting the opening and innovation of the carbon emissions trading market, increasing monitoring and control of the negative impact of carbon emissions trading, and promoting the optimization and improvement of carbon emissions trading policies.
Industry Prosperity and Stock Return: Evidence from China’s Real Estate Industry
The influencing factors of capital asset pricing have been a hot topic in academic research, yet the practice of incorporating industry prosperity into factor models for quantitative analysis is limited. By creating a new factor based on the National Real Estate Climate Index and adding it to the Fama-French three-factor model (FF3), this study focuses on China’s real estate sector and examines the impact of industry prosperity on capital asset pricing. Empirical findings from the real estate sector of China’s A-share market include: (1) The FF3 shows good applicability, with a positive market premium, a negative size premium and a negative value premium; (2) A rise in industry prosperity has a significant negative impact on the excess returns for the next period on low book-to-market stocks and large-cap stocks with a medium book-to-market ratio; (3) Industry prosperity has some interactive effects on the FF3 factors. The objectives of this study are to fill the research gap, to support investment strategy optimization, and to serve as a guide for policy practices.
A Research on the Application of Option Pricing Strategy Framework Based on BS Model
This paper first reviews the development history of option modeling and its application in corporate strategy, providing a comprehensive background for understanding its evolution. It introduces the European option pricing model studied by scholars in the past, particularly focusing on the Black-Scholes (BS) model, a foundational tool in financial modeling. After establishing the research significance, this paper discusses several basic properties and influencing factors of the BS model while introducing real options as a dynamic framework for strategic decision-making. The core focus of this paper lies in the modification and adaptation of the BS model at the corporate strategy level. Specifically, it develops a combined model that integrates the BS real option method to address the limitations of traditional models, enhancing their applicability to complex business scenarios. Xinhua Wenxuan Company is employed as a case study to validate the feasibility of this refined model, providing a practical evaluation of its results. Lastly, this paper highlights the future research direction of this model, underlining its adaptability and potential for broader applications in corporate strategic management, particularly in industries characterized by high uncertainty and innovation.
The Impact of Cryptocurrencies and Their Regulatory Challenges and Countermeasures
This paper mainly talks about the regulatory issues of cryptocurrencies and their potential impacts. With the rapid development of digital currencies, their status in cross-border payments is constantly rising, but it also brings high volatility and various economic crime risks, which is expected to change the current financial system. This paper conducts a literature review and case analysis to compare the different practices of countries in cryptocurrency regulation and points out the deficiencies of the current regulatory framework in responding to technological changes and safeguarding the interests of investors. It proposes relevant suggestions to enhance transparency, security, and innovation. The study also pays special attention to stablecoins and central bank digital currencies, which explores whether it can mitigate the market volatility and potential financial risks of cryptocurrencies to some extent. The future regulation of cryptocurrencies needs global cooperation and technological innovation to enable cryptocurrencies to play a positive role in economic development.
An Overview of the Impact of Financial Technology Development on the Real Economy
Financial Technology (FinTech) is leading profound and significant changes in the structure of the global economy at an unprecedented speed with a thunderous momentum. It has subversively reconstructed the operation mode of the traditional financial industry and sown extensive and far-reaching seeds of change in the real economy. This paper aims to comprehensively and deeply scrutinize the multidimensional and omnidirectional impact of FinTech development on the real economy. FinTech has played a vital role in promoting the prosperity of the consumer market, effectively stimulating the vigor of consumption; at the same time, it has opened new channels of financing for small and medium-sized enterprises (SMEs), effectively alleviating the bottleneck of the funding that they have been facing for a long time. In addition, FinTech has significantly improved the overall efficiency of financial services, enabling financial resources to flow more efficiently and conveniently. In optimizing the efficiency of capital and resource allocation, FinTech also shows strong potential to help resources achieve better allocation. More importantly, FinTech has actively stimulated innovation and entrepreneurship, injecting a new powerful impetus for economic development.
Predictive Research of the US Stock Market: Comparative Analysis Based on Multiple Data Science Methods
This study thoroughly investigates the effectiveness of numerous data science techniques in forecasting trends inside the US stock market using a wide range of machine learning (ML) and deep learning (DL) approaches. Among the investigated techniques are decision trees, random forests, long short-term memory networks (LSTM), and support vector machines (SVM). The study underlines both the benefits and drawbacks of every model in real-world settings by means of numerous comparisons, therefore evaluating its predictive capability. The results show that although simpler models such random forests and decision trees have a degree of interpretability and are easier for investors to understand, they frequently fail to portray the complexity of market behavior. On the other hand, creative models like LSTMs and fusion techniques show shockingly great capacity to analyze and predict complex market processes, so far much above conventional approaches. For legislators seeking improved knowledge of market behavior and trends as well as for investors seeking portfolio optimization, these findings have major ramifications. By means of improved prediction models, stakeholders can make better judgments, so enhancing possibly financial returns. At last, this study provides perceptive analysis that enhances our ability to project on the always shifting terrain of the financial markets.
A Quantitative Strategy for value investing in Small Cap Stocks Based on Positive Feedback Asymmetry
Significant positive feedback trading exists in the Chinese market, and there is a significant difference between the extent of chasing up and killing down in the context of positive feedback trading. The purpose of this paper is to investigate whether a quantitative investment strategy with this asymmetric trait as the core factor can achieve significant excess returns and reduce the risk impact of irrational investors in the market. This paper is based on the CSI 500 index represented by small-cap stocks as the strategic stock pool, and further constructs a quantitative stock selection strategy, which firstly estimates the positive feedback trading asymmetry index of individual stocks in the market through the framework of SW, and at the same time, combines the Chinese three-factor model with Amihud's illiquidity index to construct the factor portfolios, and conducts a validity test to ultimately select the four portfolios with the highest cumulative returns as factor portfolios. This paper concludes that the strategy has a return of 316.73% during the back testing period, a weekly Sharpe ratio of 0.33, and a maximum backtest of 36.41%, realizing a significant excess return with controlled risk.
An A-Share Board Chasing Strategy Based on the JoinQuant Platform
The price limit system sets a limit on the price fluctuation of stock prices to ensure the stable operation of the securities market. Current research mainly focuses on the impact of various price limit policies on the stock market, but research on short-term investment strategies and methods for price limit stocks is still insufficient. Since the proportion of people who can get great investment returns in the Chinese stock market is very low, this paper aims to explore the stocks with good liquidity on the stopping stocks to construct investment strategies. In this paper, five important stock factors are identified through the multi-factor stock selection method, and then through the Join Quant platform with a back testing method, we finally get a good excess return and determine the value range of these five factors. Based on the above research, people can provide a good stop trading strategy for individual investors. This strategy can be called as a board chasing strategy, which can help investors to get high investment returns in a short period of time.
A Comparative Study of LSTM and BP Models in Supply Chain Finance Risk Assessment of A-stock Listed Steel Companies
The iron and steel industry faces the high-risk management challenges in the supply chain finance due to its capital-intensive characteristics and complex supply chain structure. Based on the financial data of 26 iron and steel companies in A-stock, this study uses Long Short-Term Memory (LSTM) neural network and the Back-Propagation (BP) models to assess and compare supply chain finance risks. A multidimensional assessment system covering corporate creditworthiness, supply chain capability, and risk level is established by analyzing the financial data from 2020-2023. The results show that although the LSTM model is good at dealing with long-time series data, the BP model outperforms the LSTM and better fits the actual data when the sample size is small. Therefore, the BP model is preferred when the amount of data is limited, while the LSTM model may perform better when the amount of data increases significantly to improve prediction accuracy and decision support.
An Exploration of Different Strategies and Applications of Quantitative Investment under Different Models
With the rapid development of financial markets and the surge in data volume, quantitative investment has gradually become an important tool for investment decision-making. Traditional investment strategies often rely on experience and qualitative analysis, which is difficult to cope with complex market environments. Therefore, exploring quantitative investment models based on machine learning and deep learning has become a hot topic of research. This study aims to analyze the different applications of various models in quantitative investment, focusing on areas such as factor models, statistical arbitrage, and sentiment analysis. Through a comprehensive analysis of relevant literature in recent years, the results show that the future development of quantitative investment will increasingly rely on advanced algorithms and big data analysis techniques. Under the application of different models, there are diverse ideas and tools for the analysis and decision-making of financial markets. The combination of these models will promote the diversity and flexibility of investment strategies. At the same time, policymakers and financial institutions need to pay attention to the transparency and interpretability of the model to reduce potential risks. Looking forward, further research can focus on the combination optimization of models and the improvement of real-time data processing capabilities to cope with the changing market environment and provide stronger support for the practice of quantitative investment.