加拿大Enbridge油气运输公司-201406_Financial & Strategic Update_ Conference_Call_By_CEO.pdf

Financial Reporting and Analysis(6th) 英文无水印pdf 第6版 pdf所有页面使用FoxitReader和PDF-XChangeViewer测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 本资源转载自网络，如有侵权，请联系上传者或csdn删除

这本书适合本科生，低年级博士生学习，是用数学研究金融领域的一本很好的教材。

2018年9月16日，在第27期智能金融沙龙上，中科院自动化所陈玉博老师的演讲报告为《事件抽取与金融事件图谱构建》，以下附上该报告全文，方便相关研究人员下载学习。

SOFE AFE - Accredited Financial Examiner认证考试题库

一个简单的系统，有兴趣的可以看看JAVA+SQL SERVER项目开发实践 //登录类： import javax.swing.*; import java.awt.*; import java.awt.event.*; import javawork.jdbc.*; public class Login extends JFrame implements ActionListener{ public static void main(String ary[]){ new Login("home financial management system"); } private JButton login=new JButton("登陆"); private JButton register=new JButton("注册"); private JButton cancel=new JButton("取消"); private JPanel panelsouth=new JPanel(new FlowLayout(new FlowLayout().CENTER)); private JPanel paneluser=new JPanel(new FlowLayout(new FlowLayout().CENTER)); private JPanel panelpassword=new JPanel(new FlowLayout(new FlowLayout().CENTER)); private JPanel panelcenter=new JPanel(new GridLayout(2,1)); private JLabel user=new JLabel("用户名: "); private JLabel title=new JLabel(" 家庭财务管理系统"); private JLabel password=new JLabel("密 码: "); private JTextField userT=new JTextField(10); private JPasswordField passwordT=new JPasswordField(10); public Login(String title){ super(title); this.setResizable(false); this.addWindowListener(new WindowAdapter(){ public void windowClosing(WindowEvent e){System.exit(0);} });阅读全文请下载

在这篇综述中，我们尝试着提供一个已经开发好的，可用在金融应用当中的深度学习模型。我们不仅根据模型的实现进行了分类，还对这些深度学习模型进行了分析。此外，我们还旨在确定未来深度学习模型在金融领域有可能的实现，以及强调了该领域正在进行的研究。

全球首个链上隐私技术落地，金融级财团区块链的机密性支持，蚂蚁金服团队发表在顶会SIGMOD 2020

从网络收集财务数据 从ju-chao网站收集财务数据并可以从中下载pdf文件的python脚本，更重要的是它可以使用pdfplumber从pdf文件中解析您想要的数据。 平台： win10 anaconda python3.7 pdfplumber == 0.5.12 （如果您已经安装了pdfplumber，请不要安装pdfminer，因为pdfplumber使用pdfminer的另一个版本作为后端，它会破坏环境） original_data dir ：准备进行测试的测试文件，您可以通过修改.py文件中的文件路径来使用它们 download_files目录：下载目录，用于保存来自网络的下载文件 output_files dir：输出文件的目录，您可以在此处找到在.py文件中创建的文件 download_filesFromcsv_wyk.py可以根据.csv文件中的url链接从Web下载文

Artificial Intelligence in Financial Markets: Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics (New Developments in Quantitative Trading and Investment) 2017 | ISBN: 1137488794 | English | 344 pages | PDF | 8 MB As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.