Python for Finance: Investment Fundamentals and Data Analytics

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365 Careers Ltd.

7:08:26

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00001 What Does the Course Cover.mp4

04:12

00002 Python.mp4

00:32

00003 Why Python.mp4

05:07

00004 Jupyter.mp4

00:31

00005 Setting Up the Environment.mp4

01:24

00006 Programming Explained in 5 Minutes.mp4

05:04

00007 Why Jupyter.mp4

03:29

00008 Installing Anaconda.mp4

04:00

00009 Jupyter s Interface the Dashboard.mp4

03:10

00010 Jupyter s Interface Prerequisites for Coding.mp4

06:09

00011 Jupyter - Using Shortcuts.mp4

03:07

00012 Jupyter - Handling Error Messages.mp4

05:52

00013 Jupyter - Restarting the Kernel.mp4

02:17

00014 Python Variables.mp4

04:52

00015 Understanding Numbers and Boolean Values.mp4

03:05

00016 Strings.mp4

05:40

00017 The Arithmetic Operators of Python.mp4

03:23

00018 What is the Double Equality Sign.mp4

01:33

00019 How to Reassign Values.mp4

01:08

00020 How to Add Comments.mp4

01:34

00021 Understanding Line Continuation.mp4

00:49

00022 How to Index Elements.mp4

01:18

00023 How to Structure Your Code with Indentation.mp4

01:44

00024 Python Comparison Operators.mp4

02:10

00025 Python s Logical and Identity Operators.mp4

05:35

00026 Getting to Know the IF Statement.mp4

03:01

00027 Adding an ELSE statement.mp4

02:45

00028 Else if for Brief ELIF.mp4

05:34

00029 An Additional Explanation of Boolean Values.mp4

02:13

00030 How to Define a Function in Python.mp4

02:02

00031 How to Create a Function with a Parameter.mp4

03:49

00032 Another Way to Define a Function.mp4

02:36

00033 How to Use a Function within a Function.mp4

01:49

00034 Use Conditional Statements and Functions Together.mp4

03:06

00035 How to Create Functions that Contain a Few Arguments.mp4

01:16

00036 Built-In Functions in Python Worth Knowing.mp4

03:56

00037 Introduction to Lists.mp4

04:02

00038 Using Methods in Python.mp4

03:19

00039 What is List Slicing.mp4

04:30

00040 Working with Tuples.mp4

03:11

00041 Python Dictionaries.mp4

04:04

00042 Using For Loops.mp4

02:56

00043 Using While Loops and Incrementing.mp4

02:25

00044 Use the range Function to Create Lists.mp4

03:49

00045 Combine Conditional Statements and Loops.mp4

03:11

00046 All In Conditional Statements Functions and Loops.mp4

02:27

00047 How to Iterate over Dictionaries.mp4

03:07

00048 Object-Oriented Programming.mp4

05:00

00049 Modules Packages and the Python Standard Library.mp4

04:24

00050 Importing Modules.mp4

03:24

00051 What is Software Documentation.mp4

03:57

00052 The Python Documentation.mp4

06:14

00053 Must-Have Packages Fin DSc.mp4

04:53

00054 Arrays.mp4

06:02

00055 Generating Random Numbers.mp4

02:52

00056 Using Financial Data in Python.mp4

02:39

00057 Importing Data Part I.mp4

03:44

00058 Importing Data Part II.mp4

07:01

00059 Importing Data Part III.mp4

04:19

00060 Changing the Index of Your Time-Series Data.mp4

03:17

00061 Restarting the Jupyter Kernel.mp4

02:17

00062 Considering Both Risk and Return.mp4

02:27

00063 What are We Going to See Next.mp4

02:34

00064 Calculating a Security s Rate of Return.mp4

05:31

00065 Simple Returns Part I.mp4

05:23

00066 Simple Returns Part II.mp4

03:28

00067 Log Returns.mp4

03:39

00068 Portfolio of Securities and Calculating Rate of Return.mp4

02:39

00069 Calculating the Rate of Return of a Portfolio of Securities.mp4

08:34

00070 Popular Stock Indices.mp4

03:31

00071 Calculating the Return of Indices.mp4

05:03

00072 How Do We Measure a Security s Risk.mp4

06:05

00073 Calculating a Security s Risk in Python.mp4

05:55

00074 The Benefits of Portfolio Diversification.mp4

03:28

00075 Calculating the Covariance between Securities.mp4

03:34

00076 Measuring the Correlation between Securities.mp4

03:59

00077 Calculating Covariance and Correlation.mp4

05:00

00078 Considering the Risk of Multiple Securities.mp4

03:19

00079 Calculating Portfolio Risk.mp4

02:38

00080 Understanding Systematic Versus Idiosyncratic Risk.mp4

02:58

00081 Calculating Diversifiable and NonDiversifiable Risk.mp4

04:28

00082 Simple Regression Analysis.mp4

03:55

00083 Running a Regression in Python.mp4

06:35

00084 How to Distinguish Good Regressions.mp4

04:55

00085 Computing Alpha Beta and R2 in Python.mp4

06:14

00086 Markowitz Portfolio Theory.mp4

06:34

00087 Obtaining the Efficient Frontier Part I.mp4

05:35

00088 Obtaining the Efficient Frontier Part II.mp4

05:18

00089 Obtaining the Efficient Frontier Part III.mp4

02:07

00090 The Intuition Behind the CAPM.mp4

04:44

00091 Understanding and Calculating Beta.mp4

04:14

00092 Calculating the Beta of a Stock.mp4

03:38

00093 The CAPM Formula.mp4

04:20

00094 Calculating the Expected Return of a Stock.mp4

02:16

00095 Introducing the Sharpe Ratio.mp4

02:21

00096 Obtaining the Sharpe Ratio in Python.mp4

01:22

00097 Measuring Alpha.mp4

04:13

00098 Multivariate Regression Analysis.mp4

05:42

00099 Running a Multivariate Regression in Python.mp4

06:20

00100 The Essence of Monte Carlo Simulations.mp4

02:31

00101 Monte Carlo in Corporate Finance.mp4

02:30

00102 MC Predicting Gross Profit Part I.mp4

06:03

00103 MC Predicting Gross Profit Part II.mp4

02:56

00104 Forecasting Stock Prices with an MC Simulation.mp4

04:27

00105 MC Forecasting Stock Prices Part I.mp4

03:39

00106 MC Forecasting Stock Prices Part II.mp4

04:38

00107 MC Forecasting Stock Prices Part III.mp4

04:17

00108 An Introduction to Derivative Contracts.mp4

06:32

00109 The Black Scholes Formula.mp4

04:51

00110 MC Black Scholes Merton Updated.mp4

06:00

00111 MC Euler Discretization Part I.mp4

06:21

00112 MC Euler Discretization Part II.mp4

02:09

Description

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

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365 Careers Ltd.

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365 Careers’ courses have been taken by more than 203,000 students in 204 countries. People working at world-class firms such as Apple, PayPal, and Citibank have completed 365 Careers trainings. By choosing 365 Careers, you make sure you will learn from proven experts who have a passion for teaching, and can take you from beginner to pro in the shortest possible amount of time. If you want to become a financial analyst, a finance manager, an FP&A analyst, an investment banker, a business executive, an entrepreneur, a business intelligence analyst, a data analyst, or a data scientist, 365 Careers’ courses are the perfect place to start.

PacktPub

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Packt is a publishing company founded in 2003 headquartered in Birmingham, UK, with offices in Mumbai, India. Packt primarily publishes print and electronic books and videos relating to information technology, including programming, web design, data analysis and hardware.