Python for Financial Analysis and Algorithmic Trading Price
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
- Some knowledge of programming (preferably Python)
- Ability to Download Anaconda (Python) to your computer
- Basic Statistics and Linear Algebra will be helpful
Python for Financial Analysis and Algorithmic Trading: Description
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
Who is the target audience?
Someone familiar with Python who wants to learn about Financial Analysis!
The program targets All Levels and has a duration of 17 hours divided on 119 sessions and has 12 supplementary learning materials. This course has been initially developed by Jose Portilla / Inst. Title, as part of a partnership with Udemy ®.
Description. This course is just one of a series about ‘Python ’, which introduces you to the complete skills and tools you need to study effectively about Python for Financial Analysis and Algorithmic Trading online.
Become an effective online learner and develop your online communication skills, explore new interests and career opportunities and learn to code or develop your programming skills by having this online development course, from beginner to advanced level.