Python Algo Stock Market Trading Automation

Elevate stock market trading through Python automation. Craft tailored algorithmic strategies for smart trading decisions based on real-time data, technical indicators, and market trends. Leverage Pandas, NumPy, and TA-Lib libraries for precise data manipulation and indicator calculations. Shape trading approaches and models using your ingenuity while seamlessly integrating APIs from financial data providers for live updates. Validate strategies using historical data and optimise portfolios for risk management. A secure cloud deployment ensures round-the-clock trading. Python’s versatility fosters innovative, data-driven trading solutions, enhancing your trading prowess.

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Python Algo Stock Market Trading Automation - Curriculum

  • Understanding the history and importance of Python
  • Setting up Python on your computer (IDEs, virtual environments)
  • Basic Python syntax and data types (variables, numbers, strings, lists)
  • if, elif, and else statements
  • for and while loops
  • Conditional expressions (ternary operator)
  • Flow control and code indentation
  • Defining and calling functions
  • Function arguments and return values
  • Scope and lifetime of variables
  • Importing and using modules
  • Lists, tuples, and sets
  • Dictionaries and their methods
  • List comprehensions
  • Introduction to OOP concepts
  • Classes and objects
  • Inheritance and polymorphism
  • Encapsulation and abstraction
  • Reading and writing files
  • Using context managers (with statement)
  • Handling exceptions (try, except, finally)
  • Creating custom exceptions
  • Introduction to popular Python libraries (NumPy, pandas, Matplotlib)
  • Introduction to web frameworks (Flask, Django)
  • How to use external libraries in your projects
  • Basics of technical analysis in trading
  • Calculating indicators with NumPy and TA-Lib
  • Integrating indicators into trading strategies
  • Understanding price action patterns
  • Incorporating price action analysis into strategies
  • Developing strategies based on price movement
  • Exploring candlestick chart patterns
  • Identifying reversal and continuation patterns
  • Integrating candlestick patterns into trading decisions
  • Connecting to financial data APIs
  • Retrieving, processing live market data
  • Seamlessly integrating real-time data into strategies
  • Preprocessing historical market data for model or indicator development.
  • Handling issues such as missing data and outliers.
  • Timeframe considerations for model development.
  • Implementing the chosen model or indicator using Python libraries (e.g., NumPy, Pandas).
  • Testing and fine-tuning the model or indicator on historical data.
  • Creating buy/sell signals or predictions.
  • Analyzing market conditions and trends.
  • Identifying potential trading opportunities.
  • Defining the core idea behind the trading strategy.
  • Setting specific goals and objectives for the strategy.
  • Selecting relevant historical market data.
  • Preprocessing and cleaning data for strategy development.
  • Implementing the trading strategy logic using Python.
  • Handling buy/sell signals and position management.
  • Understanding broker APIs and integration
  • Placing trades programmatically
  • Managing orders and positions through Python
  • Introduction to TradeView and its features
  • Integrating TradeView Strategies and indicators
  • Introduction to Chartink and its capabilities
  • Utilizing Chartink to screen stocks based on criteria
  • Incorporating screened stocks into trading strategies
  • Importance of paper trading for skill development
  • Setting up paper trading environments
  • Practicing and refining strategies in simulated environments
  • Components of a robust trading framework
  • Integrating strategies, APIs, visualizations, and simulations
  • Creating a user-friendly interface for strategy management
  • Role of backtesting in algorithmic trading
  • Designing robust backtesting frameworks
  • Analyzing performance using historical data
  • Understanding risk and rewards
  • Implementing risk management strategies
  • Optimizing portfolios for diversified trading
  • Adapting the framework to various market conditions
  • Incorporating machine learning models
  • Building adaptive and intelligent trading models
  • Overview of multi-timeframe analysis
  • Advantages and disadvantages
  • Setting up your development environment (Python, libraries)
  • Develop a multi-user based trading
  • Use websockets  to enable real-time updates .
  • Deploying strategies on cloud platforms
  • Ensuring uninterrupted 24/7 automation
  • Real-time monitoring, dynamic adjustments

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Python Algo Stock Market Trading Automation - Projects

Python Algo Stock Market Trading Automation - Key Features

Python Algo Stock Market Trading Automation - Key Features

Customer Service
Job Assistence & Support

We'd do everything in our power to make sure you excelled at work.

24 Hours Support
24x7 Support

Multiple options (Email,Phone or Live Chat)exist to guarantee that your problem is resolved as soon as possible.

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Job Oriented Curriculum

Best-in-class curriculum is totally adaptable to meet your needs and prepareyou for the job and certification.

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Real world projects

Best-in-class instructors will lead trainees through exercies based on real-world projects.

Python Algo Stock Market Trading Automation - Upcoming Batches

  • Weekday
  • Week-end

Tab 1

20 June 2024

8:00 AM IST

27 June 2024

8:00 AM IST

4 July 2024

8:00 AM IST

Tab 2

22 June 2024

8:00 AM IST

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Python Algo Stock Market Trading Automation - Training Options

Live Online Training
Live Online Training
  • Interact live with industrial experts.
  • Flexible Schedule
  • Customizable Curriculum
1:1 Live Online Training
live online 1 to 1 training
  • Dedicated Trainer for you
  • 1:1 Total Online Training
  • Life-time LMS Access
  • Life-time LMS Access
Self-Paced E-Learning
Self-Paced E-Learning
  • Get E-Learning Videos
  • Learn Whenever & Wherever
  • Lifetime free Upgrade
Corporate Training
Corporate Training
  • Customized Training
  • Live Online/Classroom/Self-paced
  • 10+ years Industrial Expert Trainers

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Python Algo Stock Market Trading Automation - FAQS

  • General
  • Self-Paced
  • Online
  • Corporate

Tab 1

  • Through our LMS, you can access the recording of the missed lesson.
  • Yes, we have a customised training curriculum and programme to complete.
  • There are, in fact, both group and referal discounts available.
  • The instructor will give you with all the required resources and guidance to obtain certification independently 
  • Yes, our trainer will assist you in drafting the ideal resume for your desired position.
  • Yes, we provide placement assistance by conducting simulated interviews, crafting resumes, and emailing your profile to our corporate clients.

Tab 2

  • You can change your training mode, however the cost will be prorated depending on whatever option you first choose.
  • Training at your own speed allows you to study whenever you like, with no time constraints.
  • Yes, it varies from course to course.
  • No

Tab 3

  • yes
  • yes. only first 3 sessions
  • very few times, and depends on the Trainer
  • Yes, we will arrange another trainer if that is acceptable; if not, you can receive a refund.

Tab 4

  • Yes, we can provide resources if they are available.
  • Yes, we can tailer t the course content and schedule the sessions to fit the needs of your project.
  • No, we provide assistance