留学党请注意！！！香港中文大学（深圳）高等金融研究院（以下简称“深高金”）依托研究生教育优势，开设国际研究生预备课程，提供金融和经济等商科研究生基础教育，为满足海外硕士学位课程严苛的申请条件及顺利完成硕士课程做好充足的准备，于2020年3月9日开启国际研究生预备课程报名申请系统！

项目简介

该项目为期4周，全英文授课；学员通过学习经过考试拿到一定学分后，将获得香港中文大学（深圳）高等金融研究院的结业证书和成绩单；更有机会获得授课老师推荐信；深港两地知名企业参访！

课程安排：

Quantitative methods 数量方法 (课程代码：SFI5301)

Introduction to Economics 经济学导论(课程代码：SFI5302)

Accounting for Finance 金融会计(课程代码：SFI5303)

 Introduction to Python Python课程（选修）(课程代码：SFI5311)

✴数量方法、经济学导论（中级）、金融会计为全英文授课，Python课程为中文授课；

优秀师资

刘民教授

杜克大学博士

香港中文大学（深圳）高等金融研究院 副院长

高层管理教育项目主任

香港中文大学  金融财务MBA 课程主任

教学/研究方向：投资、房地产金融、衍生品市场、计量经济学

李宏毅教授

俄亥俄州立大学   博士

香港中文大学决策科学与企业经济学系任教，并担任博士生导师

教学/ 研究方向：经济与金融時间序列计量分析 、宏观经济增長和收入分配理论，以及中国经济等诸多方面; 曾在清华大学、武汉大学、西安交通大学、新加坡南洋理工大学等大学讲授MBA和EMBA课程。

Mark E. Koznarek

宾夕法尼亚大学沃顿商学院 MBA

威斯康星大学 硕士

香港中文大学（深圳）金融学理学硕士项目执行主任

研究方向：从事机构股票研究分析（或者“华尔街分析师”）超过20年；曾任职于美国最大的资产管理公司之一的 Alliance Bernstein L.P. ，同时也是两家股票研究公司的创始人。

申请流程：

申请要求：

1. 大学本科二年级及以上本科学生，不限专业；
2. 英语水平要求：英语四级不低于450分；或英语六级不低于420分；或雅思（学术类）不低于5.5分；或其它可证明英文水平的考试。

申请材料：

1. 申请表；
2. 个人简历（中英文）；
3. 扫描：相关英语能力资格证书复印件，如英语四级、六级、托福、雅思、GMAT等；
4. 扫描：其他证明材料，如已发表的论文复印件、奖状复印件、各类证书复印件等。

开课时间：

1. 第一个班：2020年7月13开课；
2. 第二个班：2020年7月27开课。

*最终开课时间，以录取邮件为准！

课程信息

Introduction to Economics

经济学导论（中级）

The course covers the basic concepts of Intermediate Microeconomics with a moderate degree of sophistication.  This course will be useful to students who plan to take international master degree’s programs as well as students who want to get a solid understanding of economics principles required to understand finance and economics applications. The linkage between economics models and applications is emphasized throughout. Bearing in mind that students are transitioning both from studying in a Chinese setting to that of an international setting and from undergraduate study to graduate study, I have structured the course so that students would benefit most from the learning process.  

Quantitative Methods

数量方法

The objective of this course is to address mathematical techniques required for analysing issues in finance and economics. As a pre-master course, it is intended to both refresh and consolidate basic concepts, and then go further to expand students’ knowledge of these topics, as preparation for the more rigorous core courses of the MSc Program. There are two parts of the course, fundamental methods of mathematical economics which help you to understand financial & economic models; probability and statistics which help you to conduct empirical analysis in the areas. Apart from teaching the mathematical principles, there is also an emphasis on showing the relevant applications in finance & economics for these mathematical techniques.

Accounting for Finance

金融会计

This course is designed to provide students contemplating post-graduate financial study with an understanding of, and competency in, the language and processes of accounting. Our emphasis is on understanding the inputs to financial statements, so that students understand the benefits and limitations of financial statements. In particular, we focus on use of the financial statements to address financial questions. The overall aims of this course include the following:

• Provide a broad introduction to accounting and it’s key principles.
• Introduce the role of accounting and how accounting captures information about the economics of an entity.
• Develop the skills to read and understand Financial Statements.
• Develop the skills to identify and record accounting transactions.
• Develop the skills to prepare basic financial statements including the Statement of Financial Position, Statement of Comprehensive Income, and Statement of Changes in Equity.
• Enable students to understand the ‘story’ told by financial statements and the implications for the story when different choices are made.
• Develop skills in financial statement analysis using real-world company financials.

Introduction to Python

Python入门课程

The course covers topics including, Python setup and familiarization with the environment, writing basic programs in Python, Python development support data structures and libraries including Numpy, exploratory data analysis using libraries such as Pandas, predictive model design including regression analysis, decision tree and other prediction models, visualizations using Matplotlib, and implementation project to practice the concepts learned during the course. An outline of the topics includes:

• Python Setup and Basics
• Writing simple Python Programs
• Data Structures and Libraries
• Control Flow in Python
• Exploratory Analysis in Python
• Predictive Model Design
• Data Visualization
• Course Project

如需了解报名详情及费用情况，或更深层次地了解该课程项目的信息，点击参与免费的“留学评估”或拨打全国免费热线400-6652-485进行报名咨询！