bluuebunny/crossref_metadata_2025 huggingface dataset:
Price Prediction of Bitcoin Using LSTM Neural Network
Authors: Lin Qilan
Published: March 2023

Contemporarily, cryptocurrency has a high market value, and the price of cryptocurrency fluctuates dramatically. This article analyzes the parameters effects of the LSTM model on Bitcoin price prediction accuracy based on Python and modules of Numpy, Pandas, Keras, Tensorflow, and Sklern. The analysis clarifies the relationship between the accuracy of Bitcoin price prediction and different parameters in the LSTM model. It is discovered that when larger batch sizes are supplied at minor epochs, the accuracy of Bitcoin price prediction declines. Meanwhile, the number of neurons affects the accuracy. In addition, compared to lengths of 14, 30, and 60, the prediction error grows greater when a single time sequence is 7 in length. Apart from that, at present, using closing prices from the past two years rather than the past 1 year, 3 years, or 5 years can make predictions more accurate. These findings shed light on recommendations for adjusting various parameters in the development of the LSTM model for Bitcoin price prediction.
Subway in China Fast-food Marketing
Authors: Li Zhenxu
Published: March 2023

Nowadays fast-food restaurant is becoming a common choice for people’s need due to different reasons. This research aimed to investigate Subway's 4ps (Product, Promotion, Place, and Price) marketing approach in the Chinese market due to the intense rivalry in the fast-food business in China, and also revealed the reason why Subway is less competitive in China other than in the U.S. and Europe. Subway must continue to strive for improved performance to strengthen customer loyalty and attract new consumers to outcompete its competitors. Therefore, Subway's marketing 4P (product, pricing, promotion, and place) was discussed using the SWOT analysis method to guarantee that the company may get a competitive edge in the market. The data suggested that marketing 4Ps tactics are the most significant predictor of a company's success. Possible recommendations are provided by summarizing the different Ps to help Subway better survive in the Chinese market. Contributions and limitations were discussed at the end of this paper.
Evaluating Various Machine Learning Techniques in Credit Risk Area
Authors: Li Dongtan
Published: March 2023

Implementing machine learning techniques to credit scoring is a popular method, which is widely used by many financial institutions and banks at present. As the fast development of machine learning tools, these technologies could provide people more accurate predictions and help enterprises avoid future risk. A supervised machine learning technique is utilized in this research as the classification approach. In this experiment, several machine learning algorithms will be compared in order to present the performance by evaluating the type of credit risk. The data is about assessing customers of a German banking systems from the UCI Machine Learning Repository, which contains 5000 instances and 21 attributes. The final result of this research shows the comparison of 12 scenarios among different combinations of balancing methods, feature selection methods, and predictive algorithms, which finally presents that the collection of Adaptive Synthetic, Boruta and k-Nearest Neighbor receives the highest accuracy score.
Analysis of the Development Prospect of China's Used Automobile Market
Authors: Ma Xinyu
Published: March 2023

The development of automobile industry shows that the growth of automobile sales in a country will inevitably lead to the growth of used car market transactions. "With the further development of China's automobile market, the number of new cars is increasing, and consumers' demand for car replacement is increasing significantly. In the future, the gap between used car transaction and new car sales will be further narrowed." Although, since the outbreak of COVID-19 in early 2020, the growth rate of China's domestic automobile consumption market has slowed down, consumer consumption expectations have declined, and the market has cooled significantly. Despite this, China's used car trading has achieved impressive results in the face of the overall car trading market. This article through to the development of China's used-car market present situation, used car trading, such as consumer preference for the data analysis, the rapid development of the used-car market in China in the future. The prospect of making a forecast and judgment, it is concluded that in the future China's used-car market size will continue to expand, huge market potential in the future; The used car trading system will be improved, and the market will become more standardized and transparent. The service quality of used car trading platform will continue to improve.
Dynamic Changes in US Technical Company under Uncertain Market
Authors: Zhang Yifan
Published: March 2023

Since the outbreak of the COVID-19 epidemic, great changes have taken place in the world's economic situation. The interest rate increase by the Federal Reserve has become one of the most influential actions. Researchers have found that the Fed's interest rate hike not only has an impact on the American financial market but also on the world economic situation to a certain extent. Therefore, this paper collects the share price of US dollar and the exchange rate between US dollar and RMB since June, 2021, and uses VAR model and ARMA-GARCH model to model and analyze the data, to examine how the Fed's interest rate hike will affect the dollar's value and Apple's share price, and to predict the future exchange rate and the development trend of Apple's share price in the case of the Fed's interest rate increase, so as to further study the dynamic changes of American technology companies in the uncertain market.
The Impact of the Fed's Rate Hike on the Japanese Gaming Company - Square Enix
Authors: Ruan Zhenwen
Published: March 2023

The Fed's rate hike affects global stock markets in the short run. The volatility of Square Enix's earnings during the window period is analyzed by examining the net effect of Fed rate hikes on the stock price of Square Enix, a Japanese listed company, through VAR and GARCH model. The results show that the net capital outflow dominates the current period when the dollar appreciates relative to the yen in period t=0; Square Enix is the beneficiary of the current round of successive interest rate hikes under the change in cumulative effect. In addition, the impulse response shows that the change of return is basically in line with the "J-curve" effect. The capital outflow effect dominates in the first few periods of the exchange rate increase, and the export effect dominates over time. The coefficients of the logarithmic exchange rate and its lagged term show that the increase in the exchange rate has a significant effect on Square Enix volatility, and the effect is lagged. From the full model, the magnitude of the negative effect is smaller than the positive effect, and therefore, the exchange rate increase has a significant positive effect on the volatility of Square Enix returns. The study argues that Japan should maintain macro policy sustainability, avoid large fiscal deficits, and set aside sufficient policy space to address internal and external risk challenges.
Analysis of ICBC
Authors: Lin Yongyuan
Published: March 2023

With the development of recent years, China's industry of banking already entered the development level of stable operation, in China's unprecedented changes in a century, the "change" of the banking industry is particularly critical. Based on the company's business strategy, combined with the financial analysis method, SWOT analysis method to comprehensively evaluate the advantages, risks, and business conditions of ICBC, hoping to have a certain practical significance for the future strategic trend of ICBC, and the development of China's banking industry.
Through a Keynesian Theory to Analyze the Economic Impact under the Outbreak of COVID-19 in China
Authors: Feng Xi , Yan Yuxuan , Zuo Zhongqing
Published: March 2023

With the outbreak of COVID-19 pandemic, Chinese economy was hit severely and this disease brought a significant challenge for China. This was particularly the case for unemployment, the variation of GDP and the shrinking of small and medium-sized enterprises. The objective of this research is to investigate the impacts of COVID-19 in China, evaluating economic approaches being applied for different countries and point out the suitable method to boost the recovery of the Chinese economy from economic depression. The study used the fundamental concept of Keynesian theory to conclude the most effective approaches and showed that according to Keynesian theory, the Chinese government should implement expansionary policies to sustain economic growth by raising effective demand and solving unemployment problems. Therefore, the Chinese government can encourage the whole economy through fiscal and monetary policy.
The Impact of COVID-19 on Chinese Economy - Curb Consumer Demand, Chinese Policy and the Prediction of Future Trend
Authors: Song Keting
Published: March 2023

In 2020, a coronavirus named COVID-19 suddenly broke out in China, which intensively disrupted the Chinese economy. Then it spread globally. The government have tried to set up lots of policies to help with the controlling of spread of the pandemic, so cities were locked down and people were confined at home. As a result, people lose tremendous opportunities to consume. Consumers, as an indispensable part in economy, their demand for goods and services in the market was seriously curbed. However, the epidemic in China is improving year by year and the economy steps into recovery stage. Several economic policies had been put into effect to stimulate the recovery and growth of China’s economy. The paper investigates the impact of COVID-19 on the demand side of China and aims to figure out the effectiveness of Chinese policies during the recovery stage. Also, the paper gives some prediction of the future trend of Chinese economy based on the literature review.
Wage Rigid: The Relationship between Real Output and Wage with or without Monetary Policy
Authors: Cho Yu Yiu
Published: March 2023

The relationship between real wage and output is a major area of interest within field of both macroeconomic and microeconomic. Labour market has intimate relationship with wage determination, and the wage level, representing individual’s earning and in turn affect level of poverty and living standard to some extent. This paper uses a series of regression econometric models to examine the relationship between real wage and real output level. This paper also assesses impact of different monetary policy on this relationship, either under interest target or free interest rate. Additionally, results from the economic models would be used to compare with that from Keynesian theory. Identify the relationship between wage and output would be helpful for the government to make policy decision. In a way to boost economic growth sustainably and raising living standard.
Trading Strategies for Cryptocurrencies Based on Machine Learning Scenarios
Authors: Gao Xiangyang , Hou Yuchen
Published: March 2023

A Cryptocurrency is a peer-to-peer digital exchange system in which cryptography is used to generate and distribute currency units. Bitcoin as the foremost digital currency, using asymmetric cryptographic algorithms, blockchain technology, was conceptualized by Satoshi Nakamoto in 2008 and born in 2009. In 14 years, digital currency has gone from being initially controversial and worthless to rapid increase in value. The huge fluctuations in its price have attracted worldwide attention, and more people have begun to pay attention to the investment strategy of digital currency. Starting from the attributes of Bitcoin, this paper objectively compares the application effect of arbitrage strategy and trend strategy in machine learning on Bitcoin, analyzes and summarizes and predicts the future of Bitcoin's investment. To be specific, the arbitrage strategy involves three methods, i. e. , cash arbitrage, cross-exchange arbitrage and related variety arbitrage; trend strategy involves two methods, i. e. , the timing method and the multi-factor method. These results shed light on guiding further exploration of potential of investing digital currencies, which provides an in-depth summary analysis of risk-free arbitrage and digital currency value forecasts.
The development trend of China's animation ip development-taking the ip development of Shanghai Art Film Studio as an example
Authors: Ding Wanqing
Published: March 2023

In recent years, Chinese animation has developed rapidly. At present, domestic animation has developed in the market. The box office of domestic animated films has generally risen, with box-office hits such as "Nezha" and "The Return of the Great Sage". Shanghai Fine Arts Film Studio is a very important part in the development history of Chinese animation. In the rapid development of "Internet +", relying on new communication technologies and methods, changes have taken place in various fields of film and animation creation, distribution and publication. In this way, the concept of IP was born, and now Shanghai Mei is constantly transforming from the traditional to the IP-oriented trend in its own way, and innovating the operation mode of the cultural industry in the new social and cultural environment. This paper aims to analyze the development trend of IP-based animation in China, rationally discuss the problems and challenges encountered in the development of IP-based animation in China, and attempt to describe the promotion methods and methods of “IP+”-based animation in China. future trends.
Business Research and Investment Value of Asymchem
Authors: Li Yuqian
Published: March 2023

With the COVID-19 background in the world, the higher level of the aging population and higher pressure in daily life. Whether it is COVID-19 drugs or other diseases that are easy to get in the elderly, and some other diseases have a higher incidence rate, so the demand for the drug was higher than before, and the business of CDMO company is to produce the API to the company which produces the finished drug. So, the whole industry has obtained a significant improvement. I use the SWOT analytical method to research whether the Asymchem company is a company with good operating and financial performance.  And obtain the research report from the Research reports of securities companies and industry white papers. As the result, the operating and financial performance of Asymchem are both great, and there is a continuing trend showing the CDMO industry and Asymchem would get great development in the future.
Fault Detection in Semiconductor Industry: ABCtronics
Authors: Fang Yi
Published: March 2023

The high prevalence of electronic devices over the past fifty years has fueled the extraordinary rise of the semiconductor industry. The manufacture of semiconductor wafers is a time-consuming and delicate process in which defects might arise and cause the failure of the entire circuit. As more complicated devices generate flaws that are tiny and harder to detect [8], innovations in wafer defect inspection technologies are in high demand. Traditional machine learning approaches, such as univariate and multivariate analyses, have been utilized for a long time as a method for developing defect detection models [3][4]. The virtual firm and data resource are provided by case of virtual company ABCtronics. Nonetheless, obstacles provide possibilities for creativity. In the face of the development of technology, a company's troubles have equal potential to completely wipe it out and propel it to success. The focus of this investigation is on the limitations of the technologies currently used in semiconductor manufacture. The research concludes that loyal clients lead to successful businesses.
Spillover Effect of US-China Trade War: Case Study of Vietnam and Malaysia
Authors: Dong Yunqi
Published: March 2023

This paper focuses on the comparison of the spillover effects brought by the US-China trade conflict on industrialized and emerging economies classified by different sectors and research of possible policies that would improve FDI absorption abilities of emerging economies. The proposed method to solve the problem is through desk research on secondary sources and import and export data of each country provided by the World Bank. The results obtained in this research include Japan and Germany lost the most in automobile industries while Vietnam and Malaysia reaped profits from diverted demand of commodity manufacturing and foreign direct investment.
The Role of High-end Manufacturing in Sino US Trade Friction
Authors: Du Gengzhe
Published: March 2023

Since the end of 2017, the US China policy has undergone major changes, and trade friction and technological competition have gradually become the focus of bilateral relations. China strives to strengthen its independent innovation capability, master key core technologies, and become an innovative country. The United States suppressed China on the grounds that "China forces us enterprises to transfer technology and steals US intellectual property rights.". Advanced technology has become the main stage of competition and contest between China and the United States. And high-end manufacturing enterprises play an extremely important role. From the perspective of the economic development of China and the United States, this paper looks for the causes of Sino US trade frictions and the underlying internal logic. Finally, from the perspective of high-end manufacturing development, the paper analyzes the advantages and possible problems of the development of China and the United States.
Several Characteristics of Supermarket Industry from Financial Statement -- Simple Analysis Based on Walmart, etc.
Authors: Wan Ruyi
Published: March 2023

In modern society, “supermarket” is not an alien concept. Supermarkets appear everywhere and bring convenience to people. When searching and calculating the financial data of supermarket industry and learning it as a kind of business models, some characteristics of their financial data can be seen, which are very different from the normal figures of other industries. However, seldom specialized studies can be found directly. In this article, the author is trying to discuss several categories of financial data briefly, for the analysis on evaluating a company’s performance. Taking Walmart as a major example, the article mainly focuses on the profitability and liquidity of the Company, and choose some typical ratios to explain the differences. For the supermarkets, according to the special strategies and operating methods, the ROS and ROE data are not as high as other industries. Besides, for those large retailers, the current ratio and quick ratio data are far lower than average. Whereas, the inventory holding periods and working capital cycles are much shorter. When these characteristics are shown, it may indicate that the supermarket has well cost control, good profitability, strong power of bargain and high operating efficiency. However, they are not the only-needed elements. It is still necessary for people to take other measurement as evaluating a company.
The Applications of Big Data Analysis in the Credit Business of Commercial Banks
Authors: Xie Huilin
Published: March 2023

As big data technology becomes more and more mature, its applications in the finance industry become more widespread. Big data technology can address some issues in the traditional credit business in commercial banks and expand the scope of business. This study focuses on the characteristics of big data analysis in the credit business of commercial banks and the corresponding strategies of risk management. To be specific, this paper summarizes current studies on the topic through careful analysis and points out advice for improvement in big data analysis in the credit business. According to the analysis, big data techniques can play a role in target marketing and the development of customized services based on customers’ images. Furthermore, big data applications can significantly reduce manual labor. In addition, big data technology helps in early identification of risks and risk control since banks can know the borrowers better through it. These results shed light on guiding further exploration of implementation big data analysis to bring competitive advantages to commercial banks.
Global Asset Allocation Based on Principal Component Risk Parity Model
Authors: Yong Yuhan
Published: March 2023

Contemporarily, as the economy enters the new normal, Chinese real estate prices that rose almost unilaterally in the past will be difficult to appear again. With just break, the high yield of wealth management products will no longer be the scene. Therefore, the importance of risk diversification among different assets, i.e., the allocation decision of major assets, becomes more and more prominent. This paper mainly investigates the application of principal component risk parity model in asset allocation. Specifically, the article focuses on the result of the experiment and the importance of this model. In the experiment, the principal component risk parity model is compared with the traditional risk parity model. At the same time, the principal component parity risk model is further analyzed and compared with other models from the related formulae derivation. Finally, the corresponding conclusions are drawn, and the advantages and necessity of rational usage of risk parity model in asset allocation are put forward. Overall, these results shed light on guiding further exploration of finding efficient models to help with asset allocation.
An Overall Analyses of PayPal
Authors: Xie Mengyao
Published: March 2023

PayPal Company is the leading aerospace company in contemporary times. As a result of pandemics recently, the global aviation industry has been severely impacted, and the operational risks faced by PayPal have also expanded. Based on the business strategy and profit model of PayPal Company in recent years, this paper analyzes the dangers that the PayPal Company has experienced in its operations and growth from the standpoint of the interaction between its resources, operations, and financial data over the last three years, in order to forecast its future growth.
How to Stand Out from We Media with Cultural Communication as Medium: Take Li Ziqi as an Example
Authors: Bai Tianyi
Published: March 2023

We Media is a way for the general public to disseminate their facts and news to the outside world through Internet or other means. It is a way for the general public to provide and share their information after being connected to the global knowledge system. This study is to explore the communicators, the content and effect of the dissemination of We Media. The dissemination of traditional culture not only provides the audience with rich cultural knowledge but also has great importance in shaping their values. From the cases of Li Ziqi and Dianxi Xiaoge, we can find that this strategy requires the vloggers to master a combination of skills, not only in filming and editing but also in cultural understanding and learning ability.
Government response and Talent Stickiness: What Causes the Location Transfer of High-Tech Industries
Authors: Zhou Jingran
Published: March 2023

Location selection of high-tech enterprises is one of the key topics in current research. The researchers discovered that Chinese Internet companies have a long tradition of positioning and development in prime cities. In the last few years, more and more Internet businesses have opted to leave the top cities. Through collecting and sorting relevant literature, this paper uses the empirical research method by Process-Tracing Method in a case study to discuss why Huawei's headquarters officially moved from Shenzhen to Dongguan. However, with The Times's development, the city's location advantage has changed. Shenzhen's policies and geographical position are no longer sufficient to attract Huawei's high-tech industry. With the development of the city, Shenzhen has brought increasing production costs for high-technology companies and industries. Compared with Shenzhen, the enterprise will develop better when the factory is relocated to Dongguan. The real estate cost of the enterprise will be significantly reduced, and talent stickiness will also be greatly improved.
Can the Development of Total Factor Productivity Help Middle-income Countries to Overcome the Middle-Income Trap?
Authors: Wang Weibo
Published: March 2023

Falling into the middle-income trap is a common phenomenon experienced by most middle-income countries. The key characteristics of countries fallen into the middle-income trap is that their GDP per capita, instead of rising, is constant throughout the years. A dominant explanation to this problem is that middle-income countries’ total factor productivity is slowing, leading to slow technological development and application. This caused reduced international competitiveness of the developing countries in a sense that neither can they compete against low-income countries or other newly emerged middle-income countries over low level manufacturing as their workers’ wages had risen, nor can they compete against other developed economies over research and development as these middle-income countries lacked the TFP for improvements. Another school of thought asserted that middle-income countries struggling in the middle-income trap is mainly due to the extractive institutions and the misallocation of resources that result in an inefficient growth of TFPs. This study aims to utilize the historic researches and country-specific cases to examine how countries can escape such trap as well as policy implications to boost TFP and reform institutions. The findings of this research suggests that on one hand, middle-income countries should improve their education and research and development. However, TFP growths cannot be fully achieved without improvements in institution. So, on the other hand, they should allocate more resources to the domestic industries to achieve maximum TFP growths and to reduce reliance on multinational enterprises and foreign high-income countries to minimum the effect of extractive institutions.
Report on Macroeconomic overview of Nigeria and related policy analysis with technology of information
Authors: Wu Jialun , Li Wenda , Li Ziang
Published: March 2023

In recent years, the coming of COVID-19 has put numerous countries, like Nigeria, in financial crisis. In this paper, six indicators including GDP, Foreign Direct Investment, GNI, Inflation, Unemployment Rate and Economic growth are used to study the Economic changes and influencing factors in Nigeria in the past 20 years with the technology of information. By studying the changes of fiscal policies, monetary policies and exchange rate policies in the past decade, the adverse consequences and shortcomings of these policies are summarized. By analyzing the financial of Nigerian government in the past 20 years, it is stated that GDP is related to international oil prices, but per capita GDP is not high. In addition, the destruction of oil industry has led to higher unemployment.
BTC, ETH and Dogecoin Price Prediction Based on OLS, Random Forest and XGBoost
Authors: Hou Ruhan
Published: March 2023

In recent years, the digital world is fast speeding developed from decentralised concept to blockchain, then to cryptocurrency. Especially, cryptocurrency is a popular trending in recent decades that attracts different experts from various field. Its high volatility has been attracted plenty of investors while also brings the difficulty for realizing the price forecasting. On this basis, this study uses public cryptocurrency dataset and three analytical models to predict the direction of cryptocurrency’s price. To be specific, three underlying assets covering large proportion in cryptocurrency are selected, i.e., Bitcoin, Ethereum and Dogecoin. According to the analysis, the prediction results of different models and approaches will be presented. At the end of study, it gains that the optional model with appropriate hyperparameters based on the judgement of metrics values, which offers relevant suggestions for future works. These results shed light on guiding further exploration of cryptocurrency price prediction in terms the state-of-art machine learning scenarios.
Price Prediction of Cude oil, Gold, and Cotton Based on OLS, Random Forest, and Lightgbm
Authors: Chen Yutong
Published: March 2023

Contemporarily, the predicted price becomes a necessary step for investors in order to gain extra returns. This study applies three regression models (i.e., OLS, Random Forest, and Lightgbm) to forecast the future prices of three products (i.e., crude oil, gold, and cotton) The 0.3 rates is used to split the train and test set. Comparing each graph of errors, two obvious lines representing the original data and predicted data tell the direct result of the advantages and disadvantages of the three models. In the experiment, it is found that the Random Forest model takes part in an important role to predict these three prices. The Random Forest model has less error between the three metrics and displays a closer graph between the original data and predicted data. According to the results, Random Forest model predicts the futures prices accurately and other models can also play the same role for specific futures to some extent. These results shed light on guiding further exploration of future price prediction.
Stock Price Prediction Based on Simple Decision Tree Random Forest and XGBoost
Authors: Wu Yifan
Published: March 2023

Stock price prediction is the process of using a variety of methods and techniques to forecast the future performance of the stock. It is helpful for investors and traders to make decisions before and during trading. In this study, three stock prediction models depending on the decision tree algorithm are developed (i.e., Decision Tree, Random Forest and XGBoost) To be specific, their performances are compared to select the best prediction approach. Both accuracy and mean squared error (MSE) are utilized as metrics to evaluate the performances of models. By comparing the results and the metrics calculated according to the predictions, the random forest model is the best model with the highest accuracy and the smallest MSE. However, the XGBoost was the least accurate since this algorithm is too sensitive to the scale of the input variables. These results offer suggestions for choosing stock price prediction models and shed light on improving the models.
Option Pricing Based on Black-Scholes Model, Monte Carlo Method and Binomial Tree Model
Authors: Xiao Yutong
Published: March 2023

Contemporarily, option is one of the widely implemented underlying assets to hedge the risk of portfolio and satisfy certain trading motivation for investors. To obtain extra return based on investment, it is crucial to utilize and apply an accuracy and suitable tool to price option. On this basis, this study focused on comparing and applying different model to achieve the goal of option pricing. To be specific, the Python code was used to help make calculations and list the results, with three functions to price options with three diverse methods. This paper chose Alphabet Inc., Amazon, Meta Platforms, Spotify, Sunrun, and Tesla, Inc. and priced the options using the historical market data from July 20, 2022, to October 20, 2022. Reasonable results for each option are achieved with differences between each method, offering price ranges for the options. These results offer a guideline for applying different methods to option pricing and compare the effectiveness of the three methods.
Portfolio Construction in Terms of APPL Based on Fama and French Five-factor Model
Authors: Shi Yu
Published: March 2023

In the contemporary world, research has been working towards creating a model that can better explain the relationship between financial investment and risk. Iterative financial models such as CAPM, Fama French three factor model (FF3F) are strengthening the explanatory power of the extra investment risk of portfolio investments. Nevertheless, due to the global pandemic, the variability of the explanatory power of financial analysis models in the stock market has become more fickle. The objective of this paper is to analyze the portfolio investment data of Apple, one of the world's largest high technology companies, from 2017 to 2022 using the Fama French five factor model (FF5F) to determine whether the model still has strong explanatory power on the stock market during the pandemic. According to the analysis, the FF5F model coefficients still robust in explaining Apple's stock markets over five-year global pandemic period. It seems as if the epidemic and similar force majeure factors do not affect the explanatory efficiency of the model, but it is unknown that whether the actual impact is not captured by the FF5F model. The results of this study based on the FF5F model shed lights for reducing portfolio investment risks.
Promotion of business administration to financial and economic development in big data environment
Authors: Bai Yun
Published: March 2023

In order to avoid various problems in the process of financial and economic development, such as vicious competition and monopoly operation, which hinder the stable development of the market, the author puts forward an analysis on the promotion of business administration to financial and economic development in the big data environment. The analysis results clearly point out that business administration can effectively supervise and improve the Chinese market, and change the corresponding management concept according to the actual situation, at the same time, it can also promote the development of financial economy through corresponding ways. With the improvement of the market, business administration will be in a more important position, the healthy and orderly development of the market depends on the guidance and maintenance of business administration. Therefore, enterprises should attach importance to business administration. Although there are various problems in China's current market, through the continuous improvement of management and relevant systems, it can, to a certain extent, promote market entities to prevent business risks, solve development problems, and in the process of continuous coordination, it will play an effective role in supervision and management, and promote all relevant market entities to jointly create a fair and just development environment, so that China's market economic environment will continue to improve and develop.
Portfolio Construction Based on Mean Variance Portfolio Theory
Authors: Yin Haokai
Published: March 2023

Asset allocation is considered an important task and is highly regarded, people are eager to earn attractive profits through the correct allocation of investment assets. In this paper, an optimal portfolio of five stocks under different conditions is constructed to calculate and predict the expected return of this portfolio. When constructing a portfolio with equal weights for different underlying symbols, the Sharpe ratio is 1.14, which means that the portfolio return is higher than the volatility risk. Based on the evaluations, Tesla is more volatile, its yield has risen a lot recently. The efficient frontier is obtained by means of Monte-Carlo concepts with random weights arrangement. The results of two different cases with different optimal conditions are presented. In the end, the conclusion is that choose the portfolio with the largest Sharpe ratio, The risk premium per unit of risk is the highest, and it's worth it. Get a possible optimal investment portfolio by analyzing data, so that people can have a deeper understanding of asset allocation theory. Overall, these results offer new insights on portfolio construction and provide guidelines for construction of portfolio.
Analysis on the Status Quo of China's Agricultural Foreign Direct Investment
Authors: Cui Yinglan
Published: March 2023

The scale of China's agricultural foreign direct investment continues to grow, and the enthusiasm of agricultural enterprises for foreign direct investment continues to increase. With the rapid development of China's foreign direct investment activities, the implementation of the "the Belt and Road Initiative" and agricultural "going-out" strategy, the foreign direct investment of Chinese agricultural enterprises has ushered in a wave of development. However, at present, there are problems such as concentrated investment location, single investment method and small scale of investment enterprises in foreign direct investment of agricultural enterprises. Thus, while realizing the sharing of investment information, we should also enhance the endogenous power of enterprises, boost the joint development of enterprises, and accelerate the cultivation of international competitiveness of agricultural enterprises.
The Upgrading of CAPM Model: from Fama-French 3 Factors to Multi-factors
Authors: He Tianchi
Published: March 2023

In general, financial theorem has always been particularly interested in the trade-off for dynamics of associated risk and expected return. This mystery had remained convoluted for decades until William Sharpe and John Lintner developed the first practical framework of the Capital Asset Pricing Models (CAPM). As a matter of fact, CAPM is founded on the idea that asset prices are influenced by inherent, risk free and market risk returns, and diversification of portfolios also benefited the investor for risk reduction. Since this finding, many advancements have been made beyond the initial models of CAPM such as the ICAPM and Fama French models. Thus, this paper presents founding theorems of the Capital Asset Pricing Model, discusses its historical advancements into different equations and demonstrate its potential limitations and future outlooks. To be specific, the principle and adding factors for the Fama French model of three factors, five factors and other quantity factors are discussed with the implementations and applications. Overall, these results provide historical summary as well as new insights for further exploration of assets pricing scenarios based on multi factorial concepts.
Digital Inclusive Finance and Regional Innovation Output
Authors: Liu Jiaxuan
Published: March 2023

This paper systematically sorts out the internal mechanism of the development of digital inclusive finance affecting regional innovation output, and uses the panel data of 31 provinces in mainland China from 2011 to 2020. From the provincial level, the individual fixed effect model and channel test are used to test the promotion effect of digital inclusive finance on the improvement of regional innovation output. The study found that the development of digital inclusive finance, its coverage, depth and degree of digitalization help to improve regional innovation capacity. The empirical results show that the development of digital inclusive finance is conducive to alleviating financing constraints and directly promoting regional innovation output; The analysis of intermediary mechanism shows that digital inclusive finance can increase external demand by promoting industrial upgrading, and then indirectly promote regional innovation output. This provides policy inspiration for relevant government departments to evaluate regional development conditions, expand the scope of financial services, and improve regional innovation systems and mechanisms.
The Impact of Macro-Economic Environment on Probability of Non-Performing Loans in Financial Institutions
Authors: Han Xiao
Published: March 2023

The rise in mortgage defaults in the banking industry highlights the connections between financial and macroeconomic shocks as well as the risk of financial instability created by credit market friction. The percentage of non-performing loans in the banking industry is assessed in this study in connection to the effects of the global economy. In order to do a regression analysis, three American banks are chosen, and the variables GDP growth, unemployment rate, real interest rate, and CPI are taken into account. The study found a significant correlation between the percentage of non-performing loans and the unemployment rate (NPL). The results of Wells Fargo indicates that there is no obvious link between GDP and NPL. There is an association between GDP expansion and the percentage of non-performing loans for Citi Bank and Bank of America. Real interest rates and NPL do not significantly affect one another. Therefore, even though some factors might not affect such probabilities, changes in the economic climate may have an impact on banks' likelihood of non-performing loans.
Which Types of Vehicle Companies Are More Worth to Invest In, Conventional or Electric?
Authors: Chen Zhige
Published: March 2023

In the contemporary century, carbon neutrality has become a fierce topic worldwide. The main energy resource is fossil fuels, dramatically damaging our environment and health. On this occasion, electric vehicles have become popular. This paper aims to analyse the information of conventional and electric vehicle companies, including data and literature, and illustrate the investment suggestion. There are two parts mainly focused on, the ability to gain profit and the risk of investing. Two companies are chosen to present the two different types, conventional and electric. After calculation, the risk level is similar, both of them are safe from liquidation. However, the ability to profit for conventional companies worsened, unlike the electric companies. Statistically, electric vehicles have a more prospective future, but many things, such as policies and customer preference, besides data, are essential to consider. After calculation, electric cars are more likely to bring profit to investors than conventional vehicle companies but more information still is needed to be analysed.
Analysis On the Influencing Factors of Housing Price in China
Authors: Cai Wenxuan , Chen Shiyu , Wang Yiru
Published: March 2023

In order to recognize and analyze the influencing factors of housing price, based on the previous literature, this paper mainly examined 3 major factors: Supply Factors, Demand factors, and Government Policy Intervention in Chinese Housing system. It was indicated that, for supply factors, development investment in the real estate market has a considerable impact on the supply and price of real estate. While for the Demand respect, we further divided it into two factors including population and level of urbanization. The results showed that although total population has no clear relation with the housing price, population aging was a positive relation with the real estate. Also, the level of urbanization only has positive relations with some parts of China. Government policy intervention is unique in China, therefore, the results of this paper could provide some useful information for the investors and governors in analyzing Monetary policy, Housing credit system, Land system, and Taxation system. Generally speaking, our paper generates a better reasoning of Chinese Housing Price.
Cause and Control of the Main Risks for Financial Derivatives
Authors: Ge Qinyan , Lou Yunjie , Sun Yiheng
Published: March 2023

With the development of the economy, the risks of financial derivatives derived from traditional financial products have gradually become apparent. Based on published papers, this paper analyzed three main risks of financial derivatives, namely credit risk, liquidity risk and market risk, and to seek ways to avoid them. According to the research findings, countermeasures including improving the transparency of derivatives markets, establishing internal management systems, strengthening risk monitoring and developing human resources can be used to avoid risks to a certain extent. However, finding effective ways to avoid risks is still a long-term and difficult task in front of the general economic workers.
Progress Of the Study on The Impact of Investor Sentiment on Stock Returns
Authors: Yu Qi
Published: March 2023

Traditional pricing models do not reckon investor sentiment as a systematic factor of stock returns. However, past market events around the world have shown considerable return anomalies that are unexplainable by well-known market factors alone. It has inspired researchers to develop behavioral finance, that is, the study of investor irrationality and how it influences the stock market in a less efficient setting. This essay reviews three popular methods to research the impact of investor sentiment on stock returns in stock markets: conventional regression models, the GARCH model family, and the DSSW model, proposed by De Long et al. It is found that conventional regressions links investor sentiment with a significant effect on stock returns, with different patterns that reflect past data and predict future prices. The GARCH family explores the sentiment-return relationship in more detail, considering factors such as volatility, while the DSSW model gives a more behavioral account and captures the complexity of such patterns of effect. In the research of this paper, investor sentiment does influence stock returns as well as volatility in both markets, which implies a deeper understanding of the stock markets and calls for attention of retail investors, institutional investors, and financial regulators.
The Impact of Investor Sentiment on Stock Prices in The Developed and Developing Countries
Authors: Xie Zixuan
Published: March 2023

The study of causal relationship of investor sentiment on stock prices has got more and more attention. This paper examines the impact of investor sentiment on investment behavior and thus on stock prices in four different countries including two developed countries (United States and United Kingdom), and two developing countries (China and India). Due to different levels of development, different countries have different measures of consumer sentiment. Therefore, the author enumerates in detail the measures of sentiment index for each studied country. By comparing representatives of investor indices, the index accuracy was analyzed as a function of market spacing. In addition, the differences between the conclusions of developing countries and developed countries are also compared. Meanwhile, the mutual influence of investor sentiment was summarized among developed countries. The empirical findings show that the study about exploring the causal relationship of the investor sentiment on the stock prices plays an important role in formulating detailed investor strategies. In other words, investors who are familiar with the impact of emotions on stock prices can be more successful in stock investing and their investment risk can be reduced than those who are not.
The Risk Management of Commercial Banks
Authors: Chen Sirui
Published: March 2023

Commercial banks are not only the largest service sector of the real economy, but also the "bellwether" of financial industry in various countries. Their risk management has always been the focus of academic attention and hot discussion. The article reviews eight studies and discusses four main risks with their managements existed in commercial banks. The review of the four risks, interest risk, credit risk, liquidity risk and operational risk, summarizes the different methods and factors on the risk managements in commercial banks. Diverse risks have quite different methods. Some of these methods are well-established in the field of economics, whereas others are innovative, which can be examined in conjunction with other disciplines, but still need adequate empirical evidence to support them. These novel models are deserving of research and application to various forms of risk management. Moreover, some authors proposed correspondingly specific measures of risk management for commercial banks and government policymakers, while others did not.