Financial Analytics with Python Program

Enroll in Zeblearns Financial Analytics with Python (CPFA) course to master the essential skills for leveraging Python programming language in financial analytics. Learn how to use Python libraries such as pandas, NumPy, and scikit-learn for financial data manipulation, analysis, and modeling. Gain hands-on experience through practical exercises and real-world projects focused on financial analytics applications. Prepare for industry-recognized certifications and equip yourself with the skills needed to make informed financial decisions using Python. Register now for comprehensive training with Zeblearn.

Programming Explained in 5 Minutes

Why Python?

Why Jupyter?

Installing Python and Jupyter

Jupyter’s Interface – the Dashboard

Jupyter’s Interface – Prerequisites for Coding

Jupyter’s Interface

Python 2 vs Python 3: What's the Difference?

Variables

Numbers and Boolean Values

Strings

Arithmetic Operators

The Double Equality Sign

Reassign Values

Add Comments

Line Continuation

Indexing Elements

Structure Your Code with Indentation

Comparison Operators

Logical and Identity Operators

Introduction to the IF statement

Add an ELSE statement

Else if, for Brief – ELIF

A Note on Boolean Values

Defining a Function in Python

Creating a Function with a Parameter

Another Way to Define a Function

Using a Function in another Function

Combining Conditional Statements and Functions

Creating Functions Containing a Few Arguments

Notable Built-in Functions in Python

Functions

Lists

Using Methods

List Slicing

Tuples

Dictionaries

For Loops

While Loops and Incrementing

Create Lists with the range() Function

Use Conditional Statements and Loops Together

All In – Conditional Statements, Functions, and Loops

Iterating over Dictionaries

Object Oriented Programming

Modules and Packages

The Standard Library

Importing Modules

Must-have packages for Finance and Data Science

Working with arrays

Generating Random Numbers

A Note on Using Financial Data in Python

Sources of Financial Data

Accessing the Notebook Files

Importing and Organizing Data in Python

Considering both risk and return

Calculating a security's rate of return

Calculating a Security’s Rate of Return in Python – Simple Returns

Calculating a Security’s Return in Python – Logarithmic Returns

What is a portfolio of securities and how to calculate its rate of return

Calculating a Portfolio of Securities' Rate of Return

Popular stock indices that can help us understand financial markets

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 stocks

Calculating Covariance and Correlation

Considering the risk of multiple securities in a portfolio

Calculating Portfolio Risk

Understanding Systematic vs. Idiosyncratic risk

The fundamentals of simple regression analysis

Running a Regression in Python

Are all regressions created equal? Learning how to distinguish good regressions

Computing Alpha, Beta, and R Squared in Python

Markowitz Portfolio Theory - One of the main pillars of modern Finance

Obtaining the Efficient Frontier in Python

The intuition behind the Capital Asset Pricing Model (CAPM)

Understanding and calculating a security's Beta

Calculating the Beta of a Stock

The CAPM formula

Calculating the Expected Return of a Stock (CAPM)

Introducing the Sharpe ratio and how to put it into practice

Obtaining the Sharpe ratio in Python

Measuring alpha and verifying how good (or bad) a portfolio manager is doing

Multivariate regression analysis - a valuable tool for finance practitioners

Running a multivariate regression in Python

The essence of Monte Carlo simulations

Monte Carlo applied in a Corporate Finance context

Monte Carlo: Predicting Gross Profit

Forecasting Stock Prices with a Monte Carlo Simulation

Monte Carlo: Forecasting Stock Prices

An Introduction to Derivative Contracts

The Black Scholes Formula for Option Pricing

Monte Carlo: Black-Scholes-Merton

Monte Carlo: Euler Discretization

Financial Analytics with Python Program

Check Your Course Fee

KEY POINTS

90+

18+

1500+

5+

ZebLearn Certification Partners – Globally Recognized Credentials!

Course content

Why Should You Learn Financial Analytics with Python Training?

Request more information

What you will get at Zeblearnindia Learning?

() 60 Minutes WEBINAR with CERTIFICATE

Explore Our Courses Across India - Flexible batches

DSP & Microcontrollers

Computer Hardware

Cisco

Cisco & Networking Certifications

Financial Analytics with Python Program

Check Your Course Fee

KEY POINTS

90+

18+

1500+

5+

ZebLearn Certification Partners – Globally Recognized Credentials!

Course content

# Introduction to programming with Python

# Python Variables and Data Types

# Basic Python Syntax

# Python Operators Continued

# Conditional Statements

# Python Functions

# Python Sequences

# Using Iterations in Python

# Advanced Python tools

# PART II FINANCE: Calculating and Comparing Rates of Return in Python

# PART II Finance: Measuring Investment Risk

# PART II Finance - Using Regressions for Financial Analysis

# PART II Finance - Markowitz Portfolio Optimization

# Part II Finance - The Capital Asset Pricing Model

# Part II Finance: Multivariate regression analysis

# PART II Finance - Monte Carlo simulations as a decision-making tool

Why Should You Learn Financial Analytics with Python Training?

Request more information

What you will get at Zeblearnindia Learning?

() 60 Minutes WEBINAR with CERTIFICATE

Explore Our Courses Across India - Flexible batches