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Tucker Balch
and
Arpan Chakraborty
Take Udacity's Machine Learning for Trading course and implement machine learning based strategies to make trading decisions using real-world data. Learn online with Udacity.
Register for this course and see more details by visiting:
OpenCourser.com/course/8zzjf4/udacity
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What's inside
Syllabus
00-00 Introduction
01-01 Reading and plotting stock data
01-02 Working with multiple stocks
01-03 The power of NumPy
Read more
Syllabus
00-00 Introduction
01-01 Reading and plotting stock data
01-02 Working with multiple stocks
01-03 The power of NumPy
Read more
01-04 Statistical analysis of time series
01-05 Incomplete data
01-06 Histograms and scatter plots
01-07 Sharpe ratio and other portfolio statistics
01-08 Optimizers: Building a parameterized model
01-09 Optimizers: How to optimize a portfolio
02-01 So you want to be a hedge fund manager?
02-02 Market Mechanics
02-03 What is a company worth?
02-04 The Capital Assets Pricing Model (CAPM)
02-05 How hedge funds use the CAPM
02-06 Technical Analysis
02-07 Dealing with Data
02-08 Efficient Markets Hypothesis
02-09 The Fundamental Law of active portfolio management
02-10 Portfolio optimization and the efficient frontier
03-01 How Machine Learning is used at a hedge fund
03-02 Regression
03-03 Assessing a learning algorithm
03-04 Ensemble learners, bagging and boosting
03-05 Reinforcement learning
03-06 Q-Learning
03-07 Dyna
Interview with Tammer Kamel
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Taught by experts, Tucker Balch and Arpan Chakraborty, who are recognized for their contribution to Machine Learning and Trading
Provides hands-on experience in implementing machine learning algorithms for trading strategies using real-world data
Covers advanced concepts such as Reinforcement Learning and Q-Learning, which are gaining popularity in Trading
Introduces essential concepts like the Efficient Markets Hypothesis and the Fundamental Law of active portfolio management
Offers practical insights into how hedge funds use machine learning to enhance their investment strategies
May require some prior technical background in machine learning and finance
Save this course
Save Machine Learning for Trading to your list so you can find it easily later:
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Reviews summary
Finance enthusiasts love it
Machine Learning for Trading is well-regarded among students who typically are completely new to the field, in particular those transitioning from computer science into finance. Students appreciate the course's introduction to fundamental financial concepts, however some are disappointed that later portions of the course focus on theory, not on practical applications.
Early portions of course praised.
"I think the course was really interesting."
"this course was great in the first and second"
"The combination of theory and practical coding was great in the first third of the course, and I really learned a lot!"
Great for learners new to finance and ML.
"very easy introduction to finance world and basic machine learning"
Lack of coding in later modules frustrates some.
"It is indeed very frustrating and it doesn't provide a glimpse into how to implement those ideas or even a starting point to develop them further."
"no more Python and no more practical examples."
"I enjoyed learning about how machine learning applies to trading strategy, but was very disappointed that mini-courses 2 and 3 included no coding assignments!"
Course takes a theoretical approach.
"If you are expecting practical lessons on how to actually use machine learning for trading don't waste your time with this course."
"All that was left was just tedious examples of extremely basic financial theory."
"Parts 2 and 3 only give very vague theoretical description of some machine learning methods, without any data or example."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Machine Learning for Trading with these
activities:
Review Linear Regression
Show steps
Strengthen your understanding of linear regression, a fundamental machine learning technique.
Browse courses on
Linear Regression
Show steps
-
Review the concepts of linear regression.
-
Refresh your knowledge on fitting a linear regression model.
-
Practice interpreting the results of a linear regression analysis.
Join a Study Group
Show steps
Collaborate with other students to reinforce concepts and discuss trading strategies.
Show steps
-
Find a group of students who are also taking the course.
-
Meet regularly to discuss the course material.
-
Work together on practice problems and assignments.
Practice Sharpe Ratio Calculations
Show steps
Sharpen your ability to calculate and interpret the Sharpe ratio.
Browse courses on
Sharpe Ratio
Show steps
-
Review the formula for the Sharpe ratio.
-
Gather historical data for a stock or portfolio.
-
Calculate the expected return and standard deviation of the investment.
-
Calculate the Sharpe ratio using the formula.
-
Interpret the Sharpe ratio to assess the risk-adjusted performance of the investment.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Read 'Quantitative Trading' by Ernie Chan
Show steps
Gain a deep understanding of quantitative trading concepts and techniques.
View
Algorithmic Trading: Winning Strategies and...
on Amazon
Show steps
-
Read each chapter thoroughly.
-
Take notes and highlight important concepts.
-
Work through the practice problems at the end of each chapter.
Practice Building Momentum Indicator
Show steps
Become more comfortable calculating and utilizing the Momentum Indicator.
Browse courses on
Technical Analysis
Show steps
-
Review the formula for the Momentum Indicator.
-
Gather historical price data for a stock.
-
Calculate the Momentum Indicator for each period.
-
Plot the Momentum Indicator on a chart.
-
Analyze the Momentum Indicator to identify trading opportunities.
Learn About Hedge Fund Strategies
Show steps
Gain insights into how hedge funds use advanced trading strategies.
Browse courses on
Investment Strategies
Show steps
-
Watch videos and read articles about hedge fund strategies.
-
Follow hedge fund managers on social media and financial news outlets.
-
Attend webinars and conferences on hedge fund investing.
-
Join online forums and discussion groups for hedge fund investors.
Attend a Technical Analysis Workshop
Show steps
Gain practical insights into technical analysis techniques.
Browse courses on
Technical Analysis
Show steps
-
Find a technical analysis workshop that aligns with your interests.
-
Register for the workshop.
-
Attend the workshop and actively participate in the discussions.
-
Apply the techniques you learn to your own trading strategies.
Develop a Trading Algorithm
Show steps
Apply machine learning techniques to create a trading algorithm that can identify profitable trading opportunities.
Browse courses on
Machine Learning Algorithms
Show steps
-
Choose a trading strategy.
-
Gather historical data for training and testing the algorithm.
-
Clean and prepare the data.
-
Select and train a machine learning model.
-
Backtest the algorithm.
-
Deploy the algorithm on a live trading platform.
Review Linear Regression
Show steps
Strengthen your understanding of linear regression, a fundamental machine learning technique.
Browse courses on
Linear Regression
Show steps
Show steps
Show steps
- Review the concepts of linear regression.
- Refresh your knowledge on fitting a linear regression model.
- Practice interpreting the results of a linear regression analysis.
Join a Study Group
Show steps
Collaborate with other students to reinforce concepts and discuss trading strategies.
Show steps
Show steps
Show steps
- Find a group of students who are also taking the course.
- Meet regularly to discuss the course material.
- Work together on practice problems and assignments.
Practice Sharpe Ratio Calculations
Show steps
Sharpen your ability to calculate and interpret the Sharpe ratio.
Browse courses on
Sharpe Ratio
Show steps
Show steps
Show steps
- Review the formula for the Sharpe ratio.
- Gather historical data for a stock or portfolio.
- Calculate the expected return and standard deviation of the investment.
- Calculate the Sharpe ratio using the formula.
- Interpret the Sharpe ratio to assess the risk-adjusted performance of the investment.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Read 'Quantitative Trading' by Ernie Chan
Show steps
Gain a deep understanding of quantitative trading concepts and techniques.
View
Algorithmic Trading: Winning Strategies and...
on Amazon
Show steps
Show steps
Show steps
- Read each chapter thoroughly.
- Take notes and highlight important concepts.
- Work through the practice problems at the end of each chapter.
Practice Building Momentum Indicator
Show steps
Become more comfortable calculating and utilizing the Momentum Indicator.
Browse courses on
Technical Analysis
Show steps
Show steps
Show steps
- Review the formula for the Momentum Indicator.
- Gather historical price data for a stock.
- Calculate the Momentum Indicator for each period.
- Plot the Momentum Indicator on a chart.
- Analyze the Momentum Indicator to identify trading opportunities.
Learn About Hedge Fund Strategies
Show steps
Gain insights into how hedge funds use advanced trading strategies.
Browse courses on
Investment Strategies
Show steps
Show steps
Show steps
- Watch videos and read articles about hedge fund strategies.
- Follow hedge fund managers on social media and financial news outlets.
- Attend webinars and conferences on hedge fund investing.
- Join online forums and discussion groups for hedge fund investors.
Attend a Technical Analysis Workshop
Show steps
Gain practical insights into technical analysis techniques.
Browse courses on
Technical Analysis
Show steps
Show steps
Show steps
- Find a technical analysis workshop that aligns with your interests.
- Register for the workshop.
- Attend the workshop and actively participate in the discussions.
- Apply the techniques you learn to your own trading strategies.
Develop a Trading Algorithm
Show steps
Apply machine learning techniques to create a trading algorithm that can identify profitable trading opportunities.
Browse courses on
Machine Learning Algorithms
Show steps
Show steps
Show steps
- Choose a trading strategy.
- Gather historical data for training and testing the algorithm.
- Clean and prepare the data.
- Select and train a machine learning model.
- Backtest the algorithm.
- Deploy the algorithm on a live trading platform.
Career center
Learners who complete Machine Learning for Trading will develop knowledge and skills
that may be useful to these careers:
Portfolio Manager
Portfolio Manager
Portfolio Managers manage investment portfolios for individuals and institutions. This course will be extremely useful for those interested in this career as it covers topics such as portfolio optimization, risk management, and performance measurement. These concepts are essential for building and managing successful investment portfolios.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts develop and implement mathematical models to analyze financial data and make investment decisions. This course will be extremely useful to those interested in this career as it provides a strong foundation in machine learning techniques, including regression, ensemble learning, and reinforcement learning. These techniques are essential for building predictive models and making data-driven investment decisions.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. This course will be extremely useful for those interested in this career as it provides a strong foundation in machine learning, including topics such as regression, ensemble learning, and reinforcement learning. These techniques are essential for building predictive models and developing machine learning solutions.
Data Scientist
Data Scientist
Data Scientists use machine learning and other techniques to extract insights from data. This course will be extremely useful for those interested in this career as it provides a strong foundation in machine learning, including topics such as regression, ensemble learning, and reinforcement learning. These techniques are essential for building predictive models and making data-driven decisions.
Investment Banker
Investment Banker
Investment Bankers provide financial advice to corporations and governments on mergers and acquisitions, capital raising, and other financial transactions. This course may be useful for those interested in this career as it covers topics such as financial modeling, valuation, and capital markets. These concepts are essential for understanding financial markets and developing sound financial strategies.
Financial Analyst
Financial Analyst
Financial Analysts provide guidance to investment clients for the purpose of maximizing return on investments. This course may be useful in building a foundation for this career as it covers topics such as statistical analysis of time series, optimizers, and portfolio optimization. These concepts are essential for understanding how financial markets work and how to make sound investment decisions.
Actuary
Actuary
Actuaries use mathematical and statistical techniques to assess and manage financial risks. This course may be useful for those interested in this career as it covers topics such as probability, statistics, and financial modeling. These concepts are essential for understanding financial risks and developing sound risk management strategies.
Risk Manager
Risk Manager
Risk Managers assess and manage financial risks for businesses. This course may be useful for those interested in this career as it covers topics such as risk identification, risk assessment, and risk mitigation. These concepts are essential for understanding financial risks and developing effective risk management strategies.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. This course may be useful for those interested in this career as it covers topics such as statistical analysis, data visualization, and probability. These concepts are essential for understanding data and making informed decisions.
Financial Adviser
Financial Adviser
Financial Advisers provide financial advice to individuals and businesses. This course may be useful for those interested in this career as it covers topics such as investment planning, retirement planning, and estate planning. These concepts are essential for understanding financial markets and developing sound financial plans.
Business Analyst
Business Analyst
Business Analysts analyze business processes and develop solutions to improve efficiency and effectiveness. This course may be useful for those interested in this career as it covers topics such as data analysis, process modeling, and requirements gathering. These concepts are essential for understanding business processes and developing effective solutions.
Economist
Economist
Economists study the economy and make recommendations on economic policy. This course may be useful for those interested in this career as it covers topics such as economic growth, inflation, and unemployment. These concepts are essential for understanding the economy and developing sound economic policies.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course may be useful for those interested in this career as it covers topics such as data structures, algorithms, and object-oriented programming. These concepts are essential for building software applications.
Product Manager
Product Manager
Product Managers are responsible for the development and management of software products. This course may be useful for those interested in this career as it covers topics such as user experience design, agile development, and product marketing. These concepts are essential for developing and launching successful software products.
Management Consultant
Management Consultant
Management Consultants advise businesses on how to improve their operations and achieve their goals. This course may be useful for those interested in this career as it covers topics such as strategic planning, financial analysis, and organizational change. These concepts are essential for understanding business operations and developing effective strategies.
For more career information including salaries, visit:
OpenCourser.com/course/8zzjf4/udacity
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Machine Learning for Trading.
Provides a comprehensive overview of the latest advances in financial machine learning, including deep learning.
Provides a comprehensive introduction to statistical learning.
Provides a more detailed look at how machine learning is used in asset management.
Save
Provides a comprehensive overview of deep learning.
Provides a unique perspective on the financial markets from one of the world's most successful investors.
Provides a good overview of the microstructure of financial markets.
Save
Provides a detailed overview of machine learning algorithms.
Provides a comprehensive introduction to reinforcement learning.
Is another classic in the field of investing and provides a more in-depth look at security analysis.
Save
Provides a simple and straightforward approach to investing for the long term.
Classic in the field of investing and provides a good foundation for understanding the basics of financial markets.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/8zzjf4/udacity
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Via
Udacity
Instructors
Tucker Balch
Arpan Chakraborty
Language
English
Good to know
Taught by experts, Tucker Balch and Arpan Chakraborty, who are recognized for their contribution to Machine Learning and Trading
Provides hands-on experience in implementing machine learning algorithms for trading strategies using real-world data
Covers advanced concepts such as Reinforcement Learning and Q-Learning, which are gaining popularity in Trading
Introduces essential concepts like the Efficient Markets Hypothesis and the Fundamental Law of active portfolio management
Offers practical insights into how hedge funds use machine learning to enhance their investment strategies
May require some prior technical background in machine learning and finance
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