Learn Algorithmic Trading with Python: Build Automated Electronic Trading Systems using Python
Autor Jamal Sinclair O’Garroen Limba Engleză Paperback – 14 ian 2022
What You'll Learn
- Analyze financial
data
with
Pandas
- Use Python libraries to perform statistical reviews Review algorithmic trading strategies
- Assess risk management with NumPy and StatsModels Perform paper and Live Trading with IB Python API
- Write unit tests and deploy your trading system to the Cloud
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Specificații
ISBN-10: 1484249348
Pagini: 335
Dimensiuni: 155 x 235 mm
Ediția:1st ed.
Editura: Apress
Colecția Apress
Locul publicării:Berkeley, CA, United States
Cuprins
Chapter 01: Finance Flavored Python
- The Case for Python for Finance
- Strings, Lists and Tuples
- Loops and Conditionals
- Programming
- Introduction to NumPy
- Exploring Financial Data with Pandas
- Visualizing Time-series Data with Matplotlib
- Financial Market Overview
- Electronic Trading Systems
- Key Trading Concepts
- Introduction to Statistics
- Using Python libraries
- MPT Concepts (Alpha, Beta, Sharpe Ratio)
- Algorithmic Trading Platforms
- Working with Data
- Using Programming Logic
- Trading Strategies
- Testing Strategies
- Choosing Libraries for back-testing
- Role of Correlation and Diversification
- Risk Mitigation Techniques
Chapter 08: Portfolio Risk Management
- Risk Analysis
- Key Risk Metrics
- Managing Portfolio Performance
- Factor Analysis
- Regression Models
- Improving Algorithm Performance
- Setting up a trading environment
- Working with IB Python API
- Live Trade Execution
- Importance of Unit Testing
- Adding Test Coverage
- Setting up Web Server
- Tornado Python Framework
- Deploying your Trading System with AWS
- Logging and Exception Handling
- Book Summary
- Continuous Learning
Notă biografică
Jamal Sinclair O’Garro is a full-stack Python and Node.js developer with over 10 years of experience working at several top-tier bulge-bracket investment banks and asset managers including Goldman Sachs, Morgan Stanley, JPMorgan, BlackRock Financial Management, a multi-billion dollar hedge fund, and a major securities market maker. His primary focus is designing and building electronic trading software systems. He has experience developing semi-systematic trading, algorithmic trading, backtesting and data visualization programs on Wall Street.
Jamal is also heavily involved in the NYC tech scene and runs two of New York City's largest tech meetups. He has been invited to and has spoken at President Barack Obama's White House, the United Nations, and New York University. Jamal has been featured or quoted in major media outlets such as Fortune, Forbes, CNN/Money and TechCrunch. He has also taught software engineering and web development courses at the New Jersey Institute of Technology and Columbia University. In his spare time he likes to shoot photography, learn new functional programming languages, give tech talks, and teach others how to code.
Textul de pe ultima copertă
- Analyze financial data with Pandas
- Use Python libraries to perform statistical reviews
- Review algorithmic trading strategies
- Assess risk management with NumPy and StatsModels
- Perform paper and Live Trading with IB Python API
- Write unit tests and deploy your trading system to the Cloud
Caracteristici
Descriere
What You'll Learn
- Analyze financial data with Pandas
- Use Python libraries to perform statistical reviews
- Review algorithmic trading strategies
- Assess risk management with NumPy and StatsModels
- Perform paper and Live Trading with IB Python API
- Write unit tests and deploy your trading system to the Cloud
Software developers, data scientists, or students interested in Python and the SciPy ecosystem