What is a James Python for Traders MasterclassΒ for Cheap?
The course is designed to be highly practical. Youβll learn through hands-on projects and real-world examples, enabling you to apply Python skills directly to trading scenarios. Each module includes practical exercises to reinforce the concepts taught.
- 8 Modules
- 4 Projects
- 105 Lessons
- 248 Code Examples
- 34 Hours of Content
ONE Program to Take You from Total Amateur to Algo Trader
What Youβll Learn In The Python for Traders Masterclass
- Python Fundamentals for Finance
Starting with basic Python, youβll progress to advanced concepts and dive into data science. Learn essential tools like pandas, numpy, matplotlib, statsmodels, and scikit-learn, key for data analysis and machine learning in finance. This course is your streamlined path to mastering Python in the financial industry.
- Working with Financial Data in Python
Youβll learn about various financial data types, how to clean and acquire data, and dive into time series analysis. Understand stationarity, practice time series forecasting, and conduct exploratory data analysis to uncover insights.
- Trading Algorithm Design Principles
Youβll learn what trading algorithms are and their core design principles. Explore modules on data management, signal generation, risk and trade execution, and portfolio management. Then, dive into backtesting, including basics, software, and advanced techniques, and finish with optimization and parameter tuning for enhancing your trading strategies.
- Automation & Analysis
Youβll learn how to source financial data effectively. This includes working with common formats like CSVs and JSON. Youβll also gain skills in scraping data from APIs and websites, followed by techniques for persisting data using files and databases. The section concludes with a summary that reinforces these key data collection methods.
- Analyzing Fundamentals
Youβll learn about fundamental data in finance, including its types and how to gather and clean it. The section covers automated methods for screening and filtering this data, techniques for statistical analysis, and using natural language processing to analyze annual reports.
- Options & Derivatives Pricing
Youβll learn about options and derivatives, basic option pricing, and delve into models like Binomial and Black-Scholes-Merton. Explore Monte Carlo simulations, exotic options, interest rate derivatives, and finite difference methods for pricing. The section also covers volatility concepts, including implied volatility, and offers advanced topics for further exploration.
- HFT and Market Making
Youβll explore βHigh Frequency Trading (HFT)β and understand how to handle high-frequency tick data. Learn about latency measurement and simulation, the strategies behind HFT market making, and the concept of statistical arbitrage with high-frequency data. Dive into signal processing specific to HFT and real-time news processing.
About Author
James is a quant trader and software engineer with years of experience in the world of algorithmic trading. With past experience at a major research lab and top tech company, heβs been independently trading equities and crypto using automated strategies since 2018. His passion for teaching and firsthand experience with the struggles that traders face when learning to code for the first time motivated him to create Python for Traders, knowing that there must be a better way to help his fellow traders turn better technology into better profits.
James Python for Traders MasterclassΒ Index:
Β Β Β π SalesPage.txt (49.00 B)
Β Β Β π Capstone Project Coding a Simple HFT Market Making Bot
π 1.jpg (53.84 KB)
π Project Overview Building a Simple Market Making Bot Python for Traders.htm (209.08 KB)
π Project Summary Python for Traders.htm (213.91 KB)
π Solution Add Alpha to the Pricing Strategy Python for Traders.htm (216.20 KB)
π Solution Define a System and Class Architecture Class Architecture Python for Traders.htm (211.69 KB)
π Solution Define the Event Loop Solution Define the Event Loop Python for Traders.htm (210.25 KB)
π Solution Implement the Data Feeds Python for Traders.htm (208.30 KB)
π Solution Implement the Order Manager Python for Traders.htm (211.57 KB)
π Step 1 Define a System and Class Architecture Python for Traders.htm (205.35 KB)
π Step 2 Define the Event Loop Python for Traders.htm (208.36 KB)
π Step 3 Implement the Data Feeds Python for Traders.htm (208.69 KB)
π Step 4 Implement the Order Manager Python for Traders.htm (211.04 KB)
π Step 5 Add Alpha to the Pricing Strategy Python for Traders.htm (212.99 KB)
Β Β Β π Module 2 Python Fundamentals for Finance
π 1.jpg (42.70 KB)
π 2.1. Python Installation and Setup UsageLesson Summary Python for.htm (139.67 KB)
π 2.10. Key library Statsmodels Hypothesis TestingRegressionsTime Series AnalysisLesson Summary Python for.htm (146.02 KB)
π 2.11. Key library Scikit-learn Lesson Summary Python for.htm (154.31 KB)
π 2.3. Basic Python ExpressionsVariables ConditionalsLoopsLesson Summary Python for.htm (148.90 KB)
π 2.3.1.mp4 (7.99 MB)
π 2.3.2.mp4 (10.58 MB)
π 2.3.3.mp4 (6.89 MB)
π 2.3.4.mp4 (16.00 MB)
π 2.4. Intermediate Python FunctionsClassesData StructuresSummary Python for.htm (151.36 KB)
π 2.4.1.mp4 (5.92 MB)
π 2.6. Data Science in Python Python for.htm (128.13 KB)
π 2.7. Key library Pandas Diving Deeper into pandas.DataFramesExample Loading Stock Data from Yahoo! FinanceLesson Summary Python for.htm (146.90 KB)
π 2.8. Key library NumPy Example Computing Stock ReturnsLesson Summary Python for.htm (145.40 KB)
π 2.9. Key library Matplotlib Lesson Summary Python for.htm (152.35 KB)
π 22RUNN~1.HTM (138.04 KB)
π 25ADVA~1.HTM (175.34 KB)
Β Β Β π Module 3 Working with Financial Data
π 1.jpg (33.89 KB)
π 3.1. Introduction to Financial Data Time Series and Cross-Sections Time Series DataLesson Summary Python for Traders.htm (174.02 KB)
π 3.2. Data Acquisition and Cleaning Lesson Summary Python for Traders.htm (170.39 KB)
π 3.2.1.mp4 (28.46 MB)
π 3.2.2.mp4 (14.32 MB)
π 3.3. Time Series Analysis Components of Time SeriesLesson Summary Python for Traders.htm (166.53 KB)
π 3.3.1.mp4 (1.83 MB)
π 3.3.2.mp4 (9.99 MB)
π 3.3.3.mp4 (7.13 MB)
π 3.3.4.mp4 (6.60 MB)
π 3.4. Understanding Stationarity Lesson Summary Python for Traders.htm (144.50 KB)
π 3.4.1.mp4 (9.83 MB)
π 3.4.2.mp4 (4.64 MB)
π 3.4.3.mp4 (4.22 MB)
π 3.5. Time Series Forecasting Lesson Summary Python for Traders.htm (159.45 KB)
π 3.6. Exploratory Data Analysis Lesson Summary Python for Traders.htm (144.96 KB)
π 3.7. Section summary Python for Traders.htm (140.59 KB)
Β Β Β π Module 4 How to Code and Backtest a Trading Algorithm
π 1.jpg (51.68 KB)
π 4.1. So what is a trading algorithm History of Algorithmic TradingLesson Summary Python for Traders.htm (151.47 KB)
π 4.10. Advanced Backtesting Techniques OverfittingCross-ValidationLesson Summary Python for Traders.htm (163.95 KB)
π 4.11. Optimization and Parameter Tuning Lesson Summary Python for Traders.htm (161.55 KB)
π 4.2. Algorithm Design Principles Lesson Summary Python for Traders.htm (148.14 KB)
π 4.3. Data Management Module Lesson Summary Python for Traders.htm (152.38 KB)
π 4.3.1.mp4 (25.25 MB)
π 4.4. Signal Generation Module Python for Traders.htm (151.26 KB)
π 4.4.1.mp4 (36.28 MB)
π 4.5. Risk Management Module Python for Traders.htm (152.17 KB)
π 4.5.1.mp4 (27.49 MB)
π 4.6. Trade Execution Module Python for Traders.htm (153.42 KB)
π 4.6.1.mp4 (23.22 MB)
π 4.7. Portfolio Management Module Python for Traders.htm (155.19 KB)
π 4.7.1.mp4 (24.50 MB)
π 4.8. Backtesting Basics Lesson Summary Python for Traders.htm (158.34 KB)
π 4.9. Backtesting Software Zooming In QuantConnect Python for Traders.htm (152.81 KB)
Β Β Β π Module 5 Automated Data Collection, Cleaning, and Storage
π 1.jpg (32.65 KB)
π 5.1. Sourcing financial data Stock data Cryptocurrency exchanges Python for Traders.htm (163.69 KB)
π 5.1.1.mp4 (13.55 MB)
π 5.2. Working with CSVs Lesson Summary Python for Traders.htm (169.81 KB)
π 5.3. Working with JSON Reading from a Stock Data API Lesson Summary Python for Traders.htm (168.68 KB)
π 5.4. Scraping data from APIs Data Scraping Python for Traders.htm (173.15 KB)
π 5.4.1.mp4 (13.93 MB)
π 5.4.2.mp4 (28.01 MB)
π 5.4.3.mp4 (9.48 MB)
π 5.4.4.mp4 (45.89 MB)
π 5.4.5.mp4 (7.00 MB)
π 5.4.6.mp4 (19.96 MB)
π 5.5. Scraping data from websites Extracting Data from HTMLExample Code BeautifulSoup4 Python for Traders.htm (170.16 KB)
π 56PERS~1.HTM (184.06 KB)
π 57SECT~1.HTM (164.49 KB)
Β Β Β π Module 6 Analyzing Fundamentals in Python
π 1.jpg (42.64 KB)
π 6.2. Types of Fundamental Data Financial StatementsLesson Summary Python for Traders.htm (185.11 KB)
π 6.3. Gathering & Cleaning Fundamental Data AutomationLesson Summary Python for Traders.htm (184.49 KB)
π 6.4. Automated Screening & Filtering Python for Traders.htm (169.15 KB)
π 6.5. Statistical Analysis of Fundamental Data Lesson Summary Python for Traders.htm (178.93 KB)
π 6.6. Natural Language Processing on News Articles Alpaca News APIGetting Historical News Data Python for Traders.htm (204.60 KB)
π 6.7. Natural Language Processing on Annual Reports Lesson Summary Python for Traders.htm (201.26 KB)
π 6.8. Using LLMs for Natural Language Processing Python for Traders.htm (180.11 KB)
π 61STRU~1.HTM (173.93 KB)
Β Β Β π Module 7 Options & Derivatives Pricing Models
π 1.jpg (49.75 KB)
π 7.1. Introduction to Options & Derivatives Lesson Summary Python for Traders.htm (181.40 KB)
π 7.10. Advanced Topics and Modern Developments (Optional) Stochastic Volatility Models Python for Traders.htm (186.54 KB)
π 7.2. Basics of Option Pricing Lesson Summary Python for Traders.htm (190.32 KB)
π 7.3. The Binomial Options Pricing Model Lesson Summary Python for Traders.htm (186.28 KB)
π 7.4. The Black-Scholes-Merton Model Lesson Summary Python for Traders.htm (186.92 KB)
π 7.5. Monte Carlo Simulation for Option Pricing Lesson Summary Python for Traders.htm (188.75 KB)
π 7.6. Introduction to Exotic Options Lesson Summary Python for Traders.htm (187.35 KB)
π 7.7. Interest Rate Derivatives and Term Structure Term Structure and Yield CurveLesson Summary Python for Traders.htm (199.81 KB)
π 7.8. Implementing Finite Difference Methods for Option Pricing Lesson Summary Python for Traders.htm (187.91 KB)
π 7.9. Volatility and Implied Volatility Lesson Summary Python for Traders.htm (189.34 KB)
Β Β Β π Module 8 Introduction to High-Frequency Trading
π 1.jpg (42.30 KB)
π 8.1. What is High Frequency Trading (HFT) Lesson Summary Python for Traders.htm (207.93 KB)
π 8.2. Handling High-Frequency Tick Data Lesson Summary Python for Traders.htm (209.37 KB)
π 8.3. Latency Measurement and Simulation Lesson Summary Python for Traders.htm (215.74 KB)
π 8.4. Understanding the HFT Market Making Strategy Lesson Summary Python for Traders.htm (210.04 KB)
π 8.5. Understanding Statistical Arbitrage with High-Frequency Data Lesson Summary Python for Traders.htm (214.01 KB)
π 8.6. Signal Processing for HFT Lesson Summary Python for Traders.htm (212.60 KB)
π 8.7. Real-time News Processing Lesson Summary Python for Traders.htm (203.99 KB)
π 8.8. Section summary Python for Traders.htm (197.14 KB)
Β Β Β π Project 1 Research & Backtest a Realistic Trading Algorithm
π 1.jpg (40.55 KB)
π Project OverviewΒ 2.mp4 (9.98 MB)
π Project Overview 1.mp4 (4.55 MB)
π Project Overview Python for Traders.htm (153.28 KB)
π Project Summary Python for Traders.htm (157.83 KB)
π Solution 4 Run a Backtesting Analysis Python for Traders.htm (156.20 KB)
π Solution Develop the Algorithm Python for Traders.htm (165.81 KB)
π Solution Formulate a Strategy Python for Traders.htm (157.03 KB)
π Step 1 Getting Started on QuantConnect Python for Traders.htm (160.09 KB)
π Step 1.mp4 (20.63 MB)
π Step 2 Formulate a Strategy Python for Traders.htm (154.48 KB)
π Step 3 Develop the Algorithm Python for Traders.htm (156.38 KB)
π Step 4 Run a Backtesting Analysis Python for Traders.htm (157.62 KB)
Β Β Β π Project 2 Volatility Surface Analysis Tool
π 1.jpg (33.89 KB)
π Project Overview Python for Traders.htm (180.26 KB)
π Project Summary Python for Traders.htm (195.35 KB)
π Solution Calculating Implied Volatilities Python for Traders.htm (190.85 KB)
π Solution Fetching Options Data Python for Traders.htm (185.79 KB)
π Solution Plot a 3D Volatility Surface Python for Traders.htm (185.93 KB)
π Step 1 Fetching Options Data Python for Traders.htm (183.23 KB)
π Step 2 Calculating Implied Volatilities Python for Traders.htm (185.51 KB)
π Step 3 Plot a 3D Volatility Surface Python for Traders.htm (187.36 KB)
Β Β Β π Project 3 Design & Build a Limit Order Book
π 1.jpg (34.21 KB)
π Project Overview What is a Limit Order Book Python for Traders.htm (198.50 KB)
π Project Summary Python for Traders.htm (210.58 KB)
π Solution Add Functionality Python for Traders.htm (204.62 KB)
π Solution Design the Data Structure Breakdown Python for Traders.htm (199.93 KB)
π Solution Simulate Live Orders Python for Traders.htm (203.91 KB)
π Step 1 Design the Data Structure Python for Traders.htm (197.78 KB)
π Step 2 Add Functionality Python for Traders.htm (201.04 KB)
π Step 3 Simulate Live Orders Python for Traders.htm (202.45 KB)
π¬ Feel free to REACH OUT to our CHATΒ support for personalized assistance and detailed information tailored to your needs.Β Weβre here to help!
Reviews
There are no reviews yet.