Introduction to Python for Quantitative finance and investing

From 79.98 C$ /h

Python is one of the most powerful programming/scripting tools of our times. However, learning from textbooks or online can become time consuming and inefficient, since we easily lose focus. In this class, we learn by doing. As you learn new techniques and concepts, you will immediately use them to build tools that will help you become a data-driven and informed investor or trader. At the end of the class, you are left with a basic understanding of what python can do, but also with a template code that you can later use to build you own strategies on top.

The class in a nutshell:

(1) How to extract market data with python, such as: OHLC quotes, volume, dividend history, financial history etc.
(2) How to store and handle data efficiently.
(3) How to build and group your own portfolio based on any custom metric (e.g. P/E ratio, Debt/Equity ratio, dividend etc)
(4) How to build future paths of a stock in our portfolio, via Monte Carlo simulations, based on your own beliefs (e.g. optimistic/pessimistic).

Extra information

A laptop with a connection to the internet is required. The rest can be worked out.

Location

Online from Netherlands

About Me

I come from Greece, but I moved in the Netherlands more than five years ago where I studied and obtained my PhD in High Energy Astrophysics. Since then, I have been working as a quantitative analyst for a big bank in the Netherlands. I have ample experience in building algorithms and quantitative tools for trading and investing using python. My main focus is derivative (option) trading and valuation, but that is a long discussion.The environment in my classes is very friendly and not formal at all, and I always welcome a nice conversation about the financial markets, philosophy or life in general.

Education

BSc, Physics ( Aristotle University of Thessaloniki, Greece)
MSc, Computational Physics ( Aristotle University of Thessaloniki, Greece)
PhD, Computational Astrophysics (University of Groningen & University of Southampton)

Experience / Qualifications

Blockchain application developer ( IT ), Groningen, the Netherlands
Quantitative analyst ( IT, Banking) , Utrecht, the Netherlands

Age

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Intermediate

Duration

60 minutes

The class is taught in

English

Greek

Skills

Finance

Investing

Python

Availability of a typical week

(GMT -05:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

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File handling (read/write files)
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Basic game development (with Pygame)

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OpenAI API (ChatGPT-4)
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Node.js/NestJS backend
Secure API key management
Cost optimization (don't waste money on API calls)

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With experience in surgical precision

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Basics and improvement of Price Action

ICT & Smart Money Concepts (SMC) methodologies

Analysis via Volume Profile and Liquidity Zones

Reading chart patterns and market structures

Risk Management and Trading Psychology

Application on CFDs on Shares and Stock Indices

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👨‍🏫 Format:

Online courses (video conferencing, screen sharing, live case studies)

Step-by-step monitoring and support

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Book Your First Lesson:

Start your journey to Python mastery now by booking your first lesson. Whether you aspire to enter the development field or hone your existing skills, these courses are designed for you.

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Courses Offered

1. Basic Python Programming
This course is designed for beginners who want to build a solid foundation in Python.
Topics include:
Introduction to Python and environment setup
Variables and data types
Operators and expressions
Conditional statements
Types of loops and loop control
Functions and scope
Data structures: lists, tuples, sets, and dictionaries
Mini projects and problem-solving exercises

2. Advanced Python Programming
This course is designed for learners who already know the basics of Python and want to explore its advanced features.
Topics include:
Lambda functions and list comprehensions
Generators, yield, and closures
Decorators
Object-Oriented Programming (classes, inheritance, polymorphism, encapsulation)
File handling and exception handling
Mini projects integrating multiple concepts

3. Data Analysis Using Python (NumPy and Pandas)
This course introduces essential tools for data manipulation and analysis using Python libraries.
Topics include:
Working with NumPy arrays
Using Pandas DataFrames and Series
Data cleaning, filtering, and transformation
Handling missing values and duplicates
Grouping, aggregation, and pivot tables
Exporting data to CSV and Excel
Real-world exercises with sample datasets