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Easy Learning with Deep Learning for Trading with LSTM: Smarter Than Signals
Finance & Accounting > Investing & Trading
1.5 h
£14.99 Free for 3 days
4.3 ★★★★★
6129 students

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Language: English

Sale Ends: 12 Nov

Master Algorithmic Trading with AI: LSTM & Deep Learning Strategies

What you will learn:

  • Understand the transformative impact of AI on algorithmic trading
  • Construct effective predictive features from raw financial data
  • Train and fine-tune LSTM models for precise buy/sell/hold signals
  • Master techniques for handling imbalanced datasets using oversampling and focal loss
  • Utilize accuracy, precision, recall, confusion matrices to evaluate trading performance
  • Visualize predicted trading signals on dynamic charts for clear analysis
  • Backtest trading strategies using portfolio simulation for robust assessment
  • Calculate Sharpe Ratio, Drawdown, and Returns for comprehensive risk analysis

Description

Revolutionize your trading approach with the power of artificial intelligence!

This intensive course empowers you to design, implement, and rigorously evaluate sophisticated algorithmic trading strategies using cutting-edge Python libraries and deep learning techniques. Whether your background is in finance or technology, you'll master the art of transforming market data into actionable trading signals. We'll explore a wide spectrum of AI methodologies, from the foundational principles of algorithmic trading to advanced deep learning architectures such as Long Short-Term Memory (LSTM) networks, Convolutional Neural Networks (CNNs), and cutting-edge Reinforcement Learning techniques.

Throughout the course, you'll gain hands-on experience working with real-world Apple stock data, constructing crucial predictive features via technical indicators, and handling the complexities of imbalanced datasets using innovative methods such as focal loss. You'll build LSTM models from the ground up, learning to interpret and refine your results through comprehensive performance metrics. Our curriculum includes backtesting simulations, allowing you to assess the robustness of your strategies using key indicators like the Sharpe Ratio and maximum drawdown.

This comprehensive program goes beyond theoretical knowledge; you’ll build a fully operational AI-driven trading bot, complete with the ability to generate buy, sell, and hold signals, visualize your performance on interactive charts, and perform a thorough risk assessment. The skills you acquire will be readily transferable to various asset classes, including stocks, ETFs, and cryptocurrencies.

What awaits you:

  • Master the fundamentals of algorithmic trading and its AI-powered transformation.
  • Develop predictive features from raw market data with proven techniques.
  • Build high-performance LSTM models for accurate buy/sell/hold predictions.
  • Tackle imbalanced datasets using robust methods like oversampling and focal loss.
  • Evaluate trading strategies through key metrics: precision, recall, accuracy, confusion matrices, Sharpe ratio, and drawdown.
  • Visualize your trading strategies and their performance on interactive charts.
  • Backtest and fine-tune your strategies using advanced portfolio simulation techniques.
  • Deploy your AI-powered trading strategy with confidence.

Enroll now and unlock your potential in the world of AI-powered algorithmic trading!

Curriculum

Introduction to Algorithmic Trading and AI

This introductory section lays the groundwork for understanding algorithmic trading and the role of AI. Lectures cover the market size and different markets used in algorithmic trading, explore how it works, outline key strategies, and delve into the significance and impact of AI in this field. You'll be introduced to traditional machine learning techniques, deep learning, reinforcement learning, genetic algorithms, sentiment analysis, and ensemble methods, giving you a broad overview of the technological landscape before moving on to more focused LSTM model building in later sections.

Building and Deploying Your LSTM Trading Strategy

This section focuses on the practical application of LSTM models for algorithmic trading. You'll learn how to build an AI-driven trading strategy using LSTM, understand the provided dataset, create predictive features from raw price data, and generate accurate labels for your training data. The section covers handling class imbalances using oversampling and focal loss for optimal model performance. The process of defining, training, and evaluating your LSTM model will be explained, along with backtesting your strategy using simulated trading signals. The final part of this section walks you through applying this knowledge to predict signals (buy, sell, hold), simulate trades, and ultimately achieve live trading capabilities.

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