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Momentum-Based Trading

Course

In this course, learners will explore how to design, backtest, and optimize a working momentum-based ML trading strategy.

In this course, learners will explore how to design, backtest, and optimize a working momentum-based ML trading strategy.

  • Advanced

  • 3 weeks

  • Last Updated November 16, 2024

Skills you'll learn:

Automated plan optimizationBacktesting

Prerequisites:

Statistics proficiencyIntermediate PythonFinancial tradingBasic calculusBasic SQL

Advanced

3 weeks

Last Updated November 16, 2024

Skills you'll learn:

Automated plan optimization • Backtesting • Feature engineering • Financial analysis with AI

Prerequisites:

Statistics proficiency • Intermediate Python • Financial trading

Course Lessons

Lesson 1

What is Momentum-Based Trading

Normal distribution and geometric Brownian motion are key to momentum trading. Shapiro-Wilk’s and Student’s t-tests are useful statistical tools for developing momentum-based trading strategies.

Lesson 2

Identifying and Extracting Momentum Features

Explore geometric Brownian motion for stock price modeling, calibration, forecasting, and confidence intervals, followed by deriving and coding the Black-Scholes formula for European option pricing.

Lesson 3

Constructing a Momentum Trading Model

Building a momentum-based trading program using MySQL/SQLite, Python, and geometric Brownian motion for price forecasting, confidence intervals, and Monte-Carlo simulation for scenario analysis.

Lesson 4

Backtesting and Optimization Techniques

The lesson covers back-testing momentum strategies, evaluating with Sharpe ratio and maximum drawdown, and quantitative risk management using Value-at-Risk (VaR) and Expected Shortfall (ES) in Python.

Lesson 5 • Project

Project: Build a Momentum-Based Algorithmic Trading Program

Build a momentum-based strategy to trade the S&P 500 index. You can later expand and customize you project to suit your needs. You will use the Python packages numpy, scipy and sqlite3, among others.

Taught By The Best

Photo of Xiaolei Xie

Xiaolei Xie

Senior Quant Modeler at London Stock Exchange Group

Xiaolei Xie is a senior quant modeler at London Stock Exchange Group. He has worked on various areas of financial mathematics, statistics and algorithmic trading, such as stochastic differential equations, time series models, quantitative risk management, etc. He has years of experience in Python and C++ programming.

The Udacity Difference

Combine technology training for employees with industry experts, mentors, and projects, for critical thinking that pushes innovation. Our proven upskilling system goes after success—relentlessly.

Demonstrate proficiency with practical projects

Projects are based on real-world scenarios and challenges, allowing you to apply the skills you learn to practical situations, while giving you real hands-on experience.

  • Gain proven experience

  • Retain knowledge longer

  • Apply new skills immediately

Top-tier services to ensure learner success

Reviewers provide timely and constructive feedback on your project submissions, highlighting areas of improvement and offering practical tips to enhance your work.

  • Get help from subject matter experts

  • Learn industry best practices

  • Gain valuable insights and improve your skills

Enroll in Momentum-Based Trading. Choose the plan that works for you

All Access monthly

  • Cancel Anytime

  • Unlimited access to our top-rated courses

  • Hands-on projects with expert feedback

  • Personalized career coaching and interview prep

  • Program Certificates

Best Value

All Access bundle1

  • All the same great benefits as our monthly plan

  • The most cost-effective way to develop the skills you want

  1. 1Discount applies to the first 4 months of membership, after which plans are converted to month-to-month.

Your subscription also includes:

C++

(809)

3 months

Intermediate

SQL

(288)

2 months

Beginner

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