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For teaching - Jupyter notebooks on financial engineering. Course at Budapest Technical University / Institute of Physics.

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## Financial Engineering, BMETE15MF78

### (A) Grading:

Please see https://physics.bme.hu/BMETE15MF78_kov?language=en

### (B) Topic Description:

1. Business goals usually combine many factors: responsible behavior, application of best industry practices in the interest of the client, product flexibility and stability, continuity of business, risk management, continuous development, speed, profit, and many others.

2. Accordingly, Financial Engineering is a mix of several different approaches :
   - **Finance:** Markets, Products
   - **Math:** Modeling, Data analysis
   - **Coding:** Software implementation and testing

3. Similarly to other fields, finance also has its own extensive **technical language**. Examples: spread, fixing, leg.

### (C) Purpose of this course:

Show by examples how Finance, Math and Coding are connected.

Note that all **code in these notebooks is illustration purposes only**. It is very far from production-level code.

### (D) Structure of each lesson:

1. New material is presented. You must guide the lecturer with your questions.

2. Problems are solved together.

### (E) How to use the jupyter notebooks on your computer:

1. Download the files from this github repository to your computer
   * either download all files in a single zip package or git clone the repo

2. Install **miniconda** on your computer, please see https://www.anaconda.com/download/success for the download.

3. Open an anaconda prompt on your computer and install the conda environment
   * 3.1 change into the directory where you downloaded (or git cloned) the files of this repo
   * 3.2 execute this command: `conda env create -f fin_course_env.yml`
 
4. Activate the installed conda environment with
   * `conda activate fin_course_env`

5. Start using the notebooks in your default browser:
   * type `jupyter notebook` at your anaconda prompt

6. Several notebooks will ask you to download free data that they process.
   * 6.1. Please create your local subfolder called `data` within the folder that contains this README file.
   * 6.2. Download the requested files to this local subfolder.

### (F) Possible further items related to the course:

1. Courses:
   * 1.1 Arzu Ozoguz: Global Financial Markets and Instruments<br/>
       https://www.coursera.org/learn/global-financial-markets-instruments
   * 1.2 Damir Filipovic: Interest Rate Models<br/>
       https://www.coursera.org/learn/interest-rate-models
   * 1.3 Martin Haugh and Garud Iyengar: Financial Engineering and Risk Management Part I, also Part II<br/>
       https://www.coursera.org/learn/financial-engineering-1

2. Alex Kuznetsov: The Complete Guide to Capital Markets for Quantitative Professionals

3. Talk to Gemini

4. Emanuel Derman and Paul Wilmott: The Financial Modelers' Manifesto

5. John Hull: Options, Futures, and Other Derivatives

### (G) Outlook. Less related to the current course:

1. The Executive Summary (pages 3 and 4) at [the 2030 jobs outlook](https://reports.weforum.org/docs/WEF_Four_Futures_for_Jobs_in_the_New_Economy_AI_and_Talent_in_2030_2025.pdf) of the World Economic Forum.

### (H) Acknowledgements:

I thank all who found the time to teach me.

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