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

What you will 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.

Description

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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.


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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.
English
language

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