Python for Financial Analysis and Algorithmic Trading
4.7 /5- Offered byUDEMY
Python for Financial Analysis and Algorithmic Trading at UDEMY Overview
Duration | 17 hours |
Total fee | ₹599 |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Go to Website  |
Credential | Certificate |
Python for Financial Analysis and Algorithmic Trading at UDEMY Highlights
- Compatible on Mobile and TV
- Earn a Cerificate on successful completion
- Get Full Lifetime Access
- Learn from Jose Portilla
Python for Financial Analysis and Algorithmic Trading at UDEMY Course details
- Someone familiar with Python who wants to learn about Financial Analysis!
- Use NumPy to quickly work with Numerical Data
- Use Pandas for Analyze and Visualize Data
- Use Matplotlib to create custom plots
- Learn how to use statsmodels for Time Series Analysis
- Calculate Financial Statistics, such as Daily Returns, Cumulative Returns, Volatility, etc..
- Use Exponentially Weighted Moving Averages
- Use ARIMA models on Time Series Data
- Calculate the Sharpe Ratio
- Optimize Portfolio Allocations
- Understand the Capital Asset Pricing Model
- Learn about the Efficient Market Hypothesis
- Conduct algorithmic Trading on Quantopian
- Welcome to Python for Financial Analysis and Algorithmic Trading! Are you interested in how people use Python to conduct rigorous financial analysis and pursue algorithmic trading, then this is the right course for you! This course will guide you through everything you need to know to use Python for Finance and Algorithmic Trading! We'll start off by learning the fundamentals of Python, and then proceed to learn about the various core libraries used in the Py-Finance Ecosystem, including jupyter, numpy, pandas, matplotlib, statsmodels, zipline, Quantopian, and much more! We'll cover the following topics used by financial professionals:Python FundamentalsNumPy for High Speed Numerical ProcessingPandas for Efficient Data AnalysisMatplotlib for Data VisualizationUsing pandas-datareader and Quandl for data ingestionPandas Time Series Analysis TechniquesStock Returns AnalysisCumulative Daily ReturnsVolatility and Securities RiskEWMA (Exponentially Weighted Moving Average)StatsmodelsETS (Error-Trend-Seasonality)ARIMA (Auto-regressive Integrated Moving Averages)Auto Correlation Plots and Partial Auto Correlation PlotsSharpe RatioPortfolio Allocation Optimization Efficient Frontier and Markowitz OptimizationTypes of FundsOrder BooksShort SellingCapital Asset Pricing ModelStock Splits and DividendsEfficient Market HypothesisAlgorithmic Trading with QuantopianFutures Trading
Python for Financial Analysis and Algorithmic Trading at UDEMY Curriculum
Course Introduction
Introduction to Course
Course Overview Lecture (DON'T SKIP THIS!)
Did you skip the last lecture? Please go back and view it!
Course FAQ
Course Materials and Set-up
Course Installation Help Notes
Course Installation Guide
Python Crash Course
Welcome to the Python Crash Course
Introduction to Crash Course
Python Crash Course Part One
Python Crash Course Part Two
Python Crash Course Part Three
Python Crash Course Exercises
Python Crash Course Exercise Solutions
NumPy
Welcome to NumPy
Introduction to NumPy
NumPy Arrays
Numpy Operations
Numpy Indexing
NumPy Review Exercise
Numpy Exercise Solutions
General Pandas Overview
Welcome to Pandas
Introduction to Pandas
Series
DataFrames
DataFrames Part Two
DataFrames Part Three
Missing Data
Group By with Pandas
Merging, Joining, and Concatenating DataFrames
Pandas Common Operations
Data Input and Output
General Pandas Review Exercises
General Pandas Exercise Solutions
Visualization with Matplotlib and Pandas
Welcome to Visualization
Introduction to Visualization in Python
Matplotlib Basics - Part One
Matplotlib Basics - Part Two
Matplotlib Part Three
Matplotlib Exercise
Matplotlib Exercise Solutions
Pandas Visualization Overview
Pandas Time Series Visualization
Pandas Visualization Exercise Overview
Pandas Visualization Exercise Solutions
Data Sources
Introduction to Data Sources
Note on Pandas Datareader
Pandas DataReader
Quandl
Pandas with Time Series Data
Welcome to Pandas for Time Series
Introduction to Time Series with Pandas
Datetime Index
Time Resampling
Time Shifts
Pandas Rolling and Expanding
Capstone Stock Market Analysis Project
Welcome to the Capstone Project!
Stock Market Analysis Project
Stock Market Analysis Project Solutions Part One
Python Stock Market Analysis Solutions - Part Two
Stock Market Analysis Project Solutions Part Three
Stock Market Analysis Project Solutions Part Four
Time Series Analysis
Welcome to Time Series Analysis
Introduction to Time Series
Time Series Basics
Introduction to Statsmodels
ETS Theory
EWMA Theory
EWMA Code Along
ETS Code Along
ARIMA Theory
ACF and PACF
ARIMA with Statsmodels
Quick Note on Second Milk Difference!
ARIMA Code Part Two
ARIMA Code Part Three
ARIMA Code Part Four
Discussion on choosing PDQ
Python Finance Fundamentals
Welcome to Finance Fundamentals
Introduction to Python Finance Fundamentals
Sharpe Ratio Slides
Portfolio Allocation Code Along Part One
Portfolio Allocation Code Along Part Two
Portfolio Optimization
Portfolio Optimization Code Along One
Portfolio Optimization Code Along Two
Portfolio Optimization Code Along Three
Key Financial Topics
Types of Funds
Order Books
Short Selling
CAPM - Capital Asset Pricing Model
CAPM Code Along
Stock Splits and Dividends
EMH
Basics of Algorithmic Trading with Quantopian
Welcome to the Quantopian Section
Introduction to Quantopian
Note on get_fundamentals
Quantopian Research Basics
Quantopian Algorithms Basics Part One
Quantopian Algorithms Basics Part Two
First Trading Algorithm - Part One
First Trading Algorithm - Part Two
Trading Algorithm Exercise
Trading Algorithm Exercise Solutions Part One
Trading Algorithm Exercise Solutions Part Two
Quantopian Pipelines Factors
Quantopian Pipelines Filters
Quantopian Pipeline - Masking and Classifiers
Advanced Quantopian and Trading Algorithms
Under Construction
Welcome to Trading Algorithms
Pipeline Trading Algorithm Example - Code Along - Part One
Pipeline Trading Algorithm - Code Along - Part Two
Quick note
Pipeline Trading Algorithm Code along Part Three
Leverage
Hedging
Hedging- Part Two
Portfolio Analysis with PyFolio
Stock Sentiment Analysis Project
What are Futures?
Futures on Quantopian
Futures on Quantopian Part Two
BONUS SECTION: THANK YOU!
Bonus Lecture:
Other courses offered by UDEMY
Student Forum
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