財務預測專題
Special Topics on Financial Forecasting
| 節 | 週四 |
|---|---|
A 18:30–19:20 | 財務預測專題 MB405 3 節連堂 |
B 19:30–20:20 | |
C 20:30–21:20 |
* 根據陽明交大上課時間表所列
This course is designed for the students who wants to improve their current financial prediction experimental results to the level of journal publication. Financial technology (FinTech) is an interdisciplinary research fields which apply novel information technology to solve financial applications. In current highly-competitive financial markets, to analyze the big data, such as the trading information, financial statements, and economic statistics, effectively and efficiently is an important issue for real-time decision making. This course focuses on the practical knowledge about the key factors of intelligent investment. We want to let the participant students understand the real view and thinking principals of the modern financial operations, no matter in value investment, speculation, hedging, or arbitrage. The course materials include two major parts: new forecasting algorithms study and real financial cases discussion. The heavy paper reading is required for the students to understand the state-of-the-art forecasting theory and methodology. These machine learning and pattern recognition algorithms cover several new prediction models, classification algorithms and clustering methods. All the selected papers are collected from high-impacted journal, such as IEEE Trans. on Pattern Analysis and Machine Intelligence, IEEE Trans. on Neural Networks and Learning Systems, Journal of Forecasting, and Information Management. The students should also demonstrate their implementation and improvement of these models in real financial applications.
Intelligence-Oriented Management Decision Systems Intelligent Financial Decision Analysis Systems Solid programming skills and financial knowledge
1. Oral presentation and project implementation 30% 2. Journal-level term paper writing 50% 3. Financial case study and discussion 20%
- Overview
- Artificial Intelligence Algorithms
- Forecasting and Financial Investment Decision
| 週次 | 主題 |
|---|---|
| 第 1 週 | Course overview |
| 第 2 週 | Introduction to the modern financial investment management system 1/2 |
| 第 3 週 | Introduction to the modern financial investment management system 22 |
| 第 4 週 | Paper reading and discussion: binary classification |
| 第 5 週 | Paper reading and discussion: artificial neural networks |
| 第 6 週 | Paper reading and discussion: support vector machines |
| 第 7 週 | Paper reading and discussion: AdaBoost algorithm |
| 第 8 週 | Paper reading and discussion: Clustering methods |
| 第 9 週 | Mid-term presentation and report |
| 第 10 週 | Paper reading and discussion: Sparse Coding |
| 第 11 週 | Paper reading and discussion: Affinity Propagation |
| 第 12 週 | Paper reading and discussion: Deep Learning algorithms |
| 第 13 週 | Financial case study: Intelligent investment and Speculation |
| 第 14 週 | Financial case study: Intelligent investment and Hedging |
| 第 15 週 | Financial case study: Intelligent investment and Arbitrage |
| 第 16 週 | Final Presentation |
| 第 17 週 | Final Presentation |
| 第 18 週 | Final Presentation |
1. Financial Forecasting, Analysis and Modelling: A Framework for Long-Term Forecasting (The Wiley Finance Series) Kindle Edition – January 20, 2015 2. Machine Learning In Computational Finance: Practical algorithms for building artificial intelligence applications Paperback – May 14, 2012 3. 陳安斌(總編著),陳明琪、李曜旭、姜林杰祐、黃建華(四人協編),「投資學-新金融實驗教學之財務金融資訊系統與投資管理」,新陸書局,2005年2月
- 地點
- 上課教室
- 時間
- Monday 9:00~12:00
- 聯絡方式
- szuhaohuang@gmai.com