Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022)最新文献_第6页

Response to COVID-19: Assessment of the Bubbles in U.S. Stock Market 应对COVID-19:对美国股市泡沫的评估

Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022) Pub Date : 1900-01-01 DOI: 10.2991/aebmr.k.220307.300

Hua Bai, Jing He, Ruorong Liu, Jing Sun, Di Wu

{"title":"Response to COVID-19: Assessment of the Bubbles in U.S. Stock Market","authors":"Hua Bai, Jing He, Ruorong Liu, Jing Sun, Di Wu","doi":"10.2991/aebmr.k.220307.300","DOIUrl":"https://doi.org/10.2991/aebmr.k.220307.300","url":null,"abstract":"At present, COVID-19 pandemic has profound influence on every aspect of human society. Due to economic globalization, the pandemic exert negative impact on real economy of all countries, and inevitably lead to higher unemployment rate. International stock market also fluctuate frequently. However, uncommon phenomenon has been noticed in the U.S. stock market. After 3 days' market crash in March, 2020, the US stock has kept trading higher. Therefore, this research identifies the current stock market's opportunities and risks under the background of the global pandemic situation. Some investors contend that in the stock market there lies great opportunities, owing to the negative effects of periodicity and pandemic, while others claim that it is the fake boom that releases wrong signals for investors due to the Fed’s policy. Through the research on GDP and employment rate under pandemic, FED’s intervention under pandemic and further impacts, the impact of real estate on the stock market, and stock index, this study aims to explore whether there lies a potential stock market bubble under its current prosper appearance. The results indicate that the U.S. is suffering from a high unemployment rate, potential great GDP loss, stock market bubbles, high inflation rate, the risk of overvaluing, etc. This study reveals that a bubble exists in the U.S. stock market. Therefore, the investors need to recognize the potential risks and conduct a reasonable portfolio.","PeriodicalId":333050,"journal":{"name":"Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134076604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Influence of Financial Derivatives on Innovation Behavior of Listed Companies 金融衍生工具对上市公司创新行为的影响

Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022) Pub Date : 1900-01-01 DOI: 10.2991/aebmr.k.220307.061

Heng Xiao, Yunfei Wu

引用次数: 0

Comparison and Analysis of Machine Learning Models to Predict Hotel Booking Cancellation 预测酒店预订取消的机器学习模型的比较与分析

Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022) Pub Date : 1900-01-01 DOI: 10.2991/aebmr.k.220307.225

Yiying Chen, Chuhan Ding, Hanjie Ye, Yuchen Zhou

{"title":"Comparison and Analysis of Machine Learning Models to Predict Hotel Booking Cancellation","authors":"Yiying Chen, Chuhan Ding, Hanjie Ye, Yuchen Zhou","doi":"10.2991/aebmr.k.220307.225","DOIUrl":"https://doi.org/10.2991/aebmr.k.220307.225","url":null,"abstract":"Hotel booking cancellation prediction is crucial in conducting revenue and resource management for hotels. This paper provides three possible substitutes for the neural network including logistic regression, k -Nearest Neighbor ( k -NN), and CatBoost, whereas CatBoost, is the most suitable model for hotels to do the prediction. The advantages of them are effectiveness, high accuracy, and lower cost. The dataset used in this paper was adapted from Kaggle, a set of the booking data from two types of hotels (resort hotel and city hotel) in Portugal, and the corresponding customers’ information. We select some key variables as the predictor to train and test the prediction models based on three machine learning algorithms. After preprocessing the raw data, i.e., standardizing, dealing with missing data, recoding some variables, and scaling, we conduct the prediction and compare each model through three metrics (confusion matrix, accuracy score, and 1 F -score). The result indicates that CatBoost has the best performance in predicting hotel booking cancellation because it has the greatest number of correct prediction samples and the highest accuracy score. We focus on the efficiency and economy of doing cancellation prediction in the hospitality industry to form a basis for future revenue and resource management for hotels.","PeriodicalId":333050,"journal":{"name":"Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134178180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Application Status of Intelligent Investment Consultant Based on Artificial Intelligence in China 基于人工智能的智能投资顾问在中国的应用现状

Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022) Pub Date : 1900-01-01 DOI: 10.2991/aebmr.k.220307.127

M. Chen

引用次数: 1

A Model Combining LightGBM and Neural Network for High-frequency Realized Volatility Forecasting 基于LightGBM和神经网络的高频实现波动率预测模型

Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022) Pub Date : 1900-01-01 DOI: 10.2991/aebmr.k.220307.473

Xiang Zhang

引用次数: 3

Analysis of the Business Model of e-commerce Companies under COVID-19: Taking Alibaba as an Example 新冠疫情下电子商务企业商业模式分析——以阿里巴巴为例

Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022) Pub Date : 1900-01-01 DOI: 10.2991/aebmr.k.220307.437

Hongyi Chen, Yueqiao Feng

引用次数: 1

A Study of Stock Portfolio Strategy Based on Machine Learning 基于机器学习的股票投资组合策略研究

Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022) Pub Date : 1900-01-01 DOI: 10.2991/aebmr.k.220307.013

Zhuoyuan Ouyang

{"title":"A Study of Stock Portfolio Strategy Based on Machine Learning","authors":"Zhuoyuan Ouyang","doi":"10.2991/aebmr.k.220307.013","DOIUrl":"https://doi.org/10.2991/aebmr.k.220307.013","url":null,"abstract":"At present, artificial intelligence is a hot topic in the field of finance. With the continuous development of domestic quantitative investment technology, it is increasingly difficult to obtain excess returns from traditional quantitative investment methods. Artificial intelligence, as a new data analysis and forecasting tool, has excellent processing capability for high-dimensional and serial data in the field of quantitative investment. As a result, quantitative investment has become one of the key areas where artificial intelligence is empowering the financial industry. In this paper, the data of listed companies in the New York Stock Exchange was used as the fundamental dataset. Twelve factors were selected as input variables for machine learning training. In terms of research methodology, portfolios were first selected based on different model algorithms, then the actual performance of each algorithm was back-tested, and investors were simulated to hold the portfolios for a long period. To ensure that the conclusions are better guided in practice, this paper attempts to apply the emerging machine learning algorithms and classical machine learning algorithms to the study of New York stock market returns, and to compare and discuss the predictive power of the algorithms on portfolio performance. The results of the study show that the portfolios selected by support vector regression and neural networks outperform the Dow Jones Index in the face of high noise and small sample space. In contrast, the emerging machine learning algorithms Adaboost regression and Bayesian Ridge regression performed slightly worse than the Dow Jones Index.","PeriodicalId":333050,"journal":{"name":"Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133057101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Summary of Research on Urban Commercial Fitness Space from the Perspective of Space Justice 空间正义视角下的城市商业健身空间研究综述

Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022) Pub Date : 1900-01-01 DOI: 10.2991/aebmr.k.220307.542

Yabo Li, Yanmei Deng, Zulong Li, Yuxi Fan

引用次数: 0

The Analysis of the Current Stage about Level and Market Development in Chinese Street Dance 中国街舞水平与市场发展的现状分析

Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022) Pub Date : 1900-01-01 DOI: 10.2991/aebmr.k.220307.113

You-ye Zhang

引用次数: 1

Investment Potential Analysis on Chinese Stock Market in Metaverse- Take VR Industry as a Sample 中国股票市场的投资潜力分析——以虚拟现实行业为例

Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022) Pub Date : 1900-01-01 DOI: 10.2991/aebmr.k.220307.165

Yurui Qin

引用次数: 3