Published 11/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.91 GB | Duration: 4h 3m
Learn to Analyze Financial Markets using Python, Data Science, Machine Learning and Technical Analysis.
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 MarketsCommodity MarketForex TradingCryptocurrencyTechnical AnalysisFinancial DerivativesFuturesOptionsTime Value of MoneyModern Portfolio TheoryEfficient Market HypothesisStock Price Prediction using Machine LearningStock Price Prediction using LSTM Neural Networks (Deep Learning)Gold Price Prediction using Machine LearningDevelop and Backtest Trading Strategies in PythonTechnical 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.
Overview
Section 1: Introduction and Course Overview
Lecture 1 Introduction and Welcome Video
Lecture 2 What will you Learn in this Course ?
Section 2: Financial Markets
Lecture 3 Introduction to Financial Markets Part 1
Lecture 4 Introduction to Financial Markets Part 2
Lecture 5 Type Of Analysis in Financial Markets
Lecture 6 Time Value of Money
Lecture 7 Capital Asset Pricing Model (CAPM)
Lecture 8 Modern Portfolio Theory (MPT)
Lecture 9 Efficient Market Hypothesis
Lecture 10 Random Walk Theory
Lecture 11 Correlation in Finance
Lecture 12 Stock Correlation Matrix
Lecture 13 Artbitrage Trading
Lecture 14 Pair Trading
Lecture 15 Algo Trading
Lecture 16 Kelly Criterion
Lecture 17 Sharpe Ratio
Section 3: Python For Finance
Lecture 18 Working with OHLC Data for Stocks
Lecture 19 Plot CandleStick Chart with Python
Lecture 20 Simple Moving Average (SMA) in Python
Lecture 21 Exponential Moving Average (EMA) in Python
Section 4: Financial Derivates
Lecture 22 Introduction to Financial Derivatives
Lecture 23 Futures (Financial Derivatives)
Lecture 24 Options (Financial Derivatives)
Lecture 25 Black Scholes Model
Section 5: Technical Analysis
Lecture 26 Introduction to Technical Analysis
Lecture 27 Finding Support and Resistance
Lecture 28 Chart Patterns
Lecture 29 Moving Average
Lecture 30 Relative Strength Index (RSI) Indicator
Lecture 31 Dow Theory
Section 6: Develop and Backtest Trading Strategies in Python
Lecture 32 Practical Case Study on Amazon Stock
Section 7: Machine Learning in Finance
Lecture 33 Gold Price Prediction using Machine Learning
Lecture 34 Stock Price Prediction using Machine Learning
Lecture 35 Apple Stock Prediction using Linear Regression
Section 8: Stock Price Prediction using LSTM
Lecture 36 Microsoft Stock Price Prediction using LSTM
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.
Homepage
https://www.udemy.com/course/quantitative-finance-with-python/
Download From 1DL
DOWNLOAD FROM 1DL.NET
DOWNLOAD FROM 1DL.NET
DOWNLOAD FROM RAPIDGATOR.NET
DOWNLOAD FROM RAPIDGATOR.NET
DOWNLOAD FROM UPLOADGIG.COM
DOWNLOAD FROM UPLOADGIG.COM
DOWNLOAD FROM NITROFLARE.COM
DOWNLOAD FROM NITROFLARE.COM