Quantitative Finance with Python

Quantitative Finance with Python

Quantitative Finance with Python

Learn to Analyze Financial Markets using Python, Data Science, Machine Learning and Technical Analysis.

Language: english

Note: 0/5 (0 notes) 2,577 students  New course 

Instructor(s): Raj Chhabria

Last update: None

What you’ll learn

  • Develop a solid understanding about different Financial Markets like Stock Market, Forex Market, Bond Market and Commodity market.
  • Learn to Predict Stock Prices and Market Trends using Machine Learning.
  • You will learn to analyze different Financial Assets using the tools and concepts of Technical Analysis like support, resistance and moving averages.
  • Manage Risk and learn the art of optimal money management and portfolio diversification using Kelly Criterion.
  • This course will teach you about different Financial Theories like Efficient Market Hypothesis, Random Walk Theory and Modern Portfolio Theory.
  • Learn to Evaluate the risk and volatility adjusted return of a portfolio using Sharpe Ratio.
  • Learn to Predict Stock Prices using LSTM Neural Network.
  • Learn the complex concepts of Financial Derivatives like Futures and Options in a simplified manner.
  • Learn to develop and backtest trading strategies in python.
  • This course will explain the advanced concepts of pair trading, arbitrage and algorithmic trading in a simple manner.

 

Requirements

  • This course expects viewers to have some basic knowledge of Python, Data Science and Machine Learning.
  • No knowledge or background in Finance is assumed.

 

Description

Interested in a lucrative and rewarding position in quantitative finance? Are you a professional working in finance or an individual working in Data Science and want to bridge the gap between Finance and Data Science and become a full on quant?

The role of a quantitative analyst in an investment bank, hedge fund, or financial company is an attractive career option for many quantitatively skilled professionals working in finance or other fields like data science, technology or engineering. If this describes you, what you need to move to the next level is a gateway to the quantitative finance knowledge required for this role that builds on the technical foundations you have already mastered.

This course is designed to be exactly such a gateway into the quant world. If you succeed in this course you will become a master of quantitative finance and the financial engineering.

This Course covers a variety of topics like:

  • Stock Markets

  • Commodity Market

  • Forex Trading

  • Cryptocurrency

  • Technical Analysis

  • Financial Derivatives

  • Futures

  • Options

  • Time Value of Money

  • Modern Portfolio Theory

  • Efficient Market Hypothesis

  • Stock Price Prediction using Machine Learning

  • Stock Price Prediction using LSTM Neural Networks (Deep Learning)

  • Gold Price Prediction using Machine Learning

  • Develop and Backtest Trading Strategies in Python

  • Technical Indicators like Moving Averages and RSI.

  • Algorithmic Trading.

  • Advanced Trading Methodologies like Arbitrage and Pair Trading.

  • Random Walk Theory.

  • Capital Asset Pricing Model.

  • Sharpe Ratio.

  • Python for Finance.

  • Correlation between different stocks and asset classes.

  • Candle Stick Charts.

  • Working with Financial and OHLC Data for stocks.

  • Optimal Position Sizing using Kelly Criterion.

  • Diversification and Risk Management.

 

Who this course is for

  • Anyone who wants to learn about Quantitative Finance using Python, Data Science and Machine Learning.
  • People preparing for CFA and FRM exams will find this course helpful.
  • Investors and Traders looking to level up their Financial Analysis game by leveraging the power of Data Science.

 

Course content

  • Introduction and Course Overview
    • Introduction and Welcome Video
    • What will you Learn in this Course ?
  • Financial Markets
    • Introduction to Financial Markets Part 1
    • Introduction to Financial Markets Part 2
    • Type Of Analysis in Financial Markets
    • Time Value of Money
    • Capital Asset Pricing Model (CAPM)
    • Modern Portfolio Theory (MPT)
    • Efficient Market Hypothesis
    • Random Walk Theory
    • Correlation in Finance
    • Stock Correlation Matrix
    • Artbitrage Trading
    • Pair Trading
    • Algo Trading
    • Kelly Criterion
    • Sharpe Ratio
  • Python For Finance
    • Working with OHLC Data for Stocks
    • Plot CandleStick Chart with Python
    • Simple Moving Average (SMA) in Python
    • Exponential Moving Average (EMA) in Python
  • Financial Derivates
    • Introduction to Financial Derivatives
    • Futures (Financial Derivatives)
    • Options (Financial Derivatives)
    • Black Scholes Model
  • Technical Analysis
    • Introduction to Technical Analysis
    • Finding Support and Resistance
    • Chart Patterns
    • Moving Average
    • Relative Strength Index (RSI) Indicator
    • Dow Theory
  • Develop and Backtest Trading Strategies in Python
    • Practical Case Study on Amazon Stock
  • Machine Learning in Finance
    • Gold Price Prediction using Machine Learning
    • Stock Price Prediction using Machine Learning
    • Apple Stock Prediction using Linear Regression
  • Stock Price Prediction using LSTM
    • Microsoft Stock Price Prediction using LSTM

 

Quantitative Finance with Python

IBM Cybersecurity Analyst [Coursera with IBM]

Time remaining or 424 enrolls left

 

Don’t miss any coupons by joining our Telegram group 

Udemy Coupon Code 100% off | Udemy Free Course | Udemy offer | Course with certificate