Python for Finance: Investment Fundamentals and Data Analytics [Video]
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Free ChapterWelcome! Course Introduction
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Introduction to Jupyter and Programming with Python
-
Python Variables and Data Types
-
Basic Python Syntax
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More on Python Operators
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Conditional Statements
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Python Functions
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Python Sequences
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Using Iterations in Python
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Advanced Python Tools
- Object-Oriented Programming
- Modules, Packages, and the Python Standard Library
- Importing Modules
- What is Software Documentation
- The Python Documentation
- Must-Have Packages Fin DSc
- Arrays
- Generating Random Numbers
- Using Financial Data in Python
- Importing Data Part I
- Importing Data Part II
- Importing Data Part III
- Changing the Index of Your Time-Series Data
- Restarting the Jupyter Kernel
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PART II FINANCE - Calculating and Comparing Rates of Return in Python
- Considering Both Risk and Return
- What are We Going to See Next?
- Calculating a Security's Rate of Return
- Simple Returns Part I
- Simple Returns Part II
- Log Returns
- Portfolio of Securities and Calculating Rate of Return
- Calculating the Rate of Return of a Portfolio of Securities
- Popular Stock Indices
- Calculating the Return of Indices
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PART II Finance - Measuring Investment Risk
- How Do We Measure a Security's Risk?
- Calculating a Security's Risk in Python
- The Benefits of Portfolio Diversification
- Calculating the Covariance between Securities
- Measuring the Correlation between Securities
- Calculating Covariance and Correlation
- Considering the Risk of Multiple Securities
- Calculating Portfolio Risk
- Understanding Systematic Versus Idiosyncratic Risk
- Calculating Diversifiable and NonDiversifiable Risk
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PART II Finance - Using Regressions for Financial Analysis
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PART II Finance - Markowitz Portfolio Optimization
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PART II Finance - The Capital Asset Pricing Model
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PART II Finance - Multivariate Regression Analysis
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PART II Finance - Monte Carlo Simulations as a Decision-Making Tool
- The Essence of Monte Carlo Simulations
- Monte Carlo in Corporate Finance
- MC Predicting Gross Profit Part I
- MC Predicting Gross Profit Part II
- Forecasting Stock Prices with an MC Simulation
- MC Forecasting Stock Prices Part I
- MC Forecasting Stock Prices Part II
- MC Forecasting Stock Prices Part III
- An Introduction to Derivative Contracts
- The Black Scholes Formula
- MC Black Scholes Merton Updated
- MC Euler Discretization Part I
- MC Euler Discretization Part II
About this
video
This course will take you on a journey where you will learn how to code in Python. You will learn how to use Python in a real working environment and explore how Python can be applied in the world of finance to solve portfolio optimization problems.
The first part of the course is ideal for beginners and people who want to brush up on their Python skills. Once we have covered the basics, we will be ready to tackle financial calculations and portfolio optimization tasks. The finance block of this course will teach you in-demand, real-world skills employers are looking for. This explains topics such as how to work with Python’s conditional statements, functions, sequences, and loops, build investment portfolios, and more.
The code bundle for this video course is available at https://github.com/PacktPublishing/Python-for-Finance-Investment-Fundamentals-and-Data-Analytics
- Publication date:
- October 2018
- Publisher
- Packt
- Duration
- 7 hours 9 minutes
- ISBN
- 9781789618976