Quantitative Trading from Udacity

What's inside

Syllabus

Welcome to the exciting world of Quantitative Trading! Say hello to your instructors and get an overview of the program.

You are starting a challenging but rewarding journey! Take 5 minutes to read how to get help with projects and content.

What to do if you have questions about your account or general questions about the program.

Learn about stocks and common terminology used when analyzing stocks.

Learn about how modern stock markets function, how trades are executed and prices are set. Study market behavior, and analyze price and volume data to identify potential trading signals.

Learn how to adjust market data for corporate actions, include fundamental information in your analysis and compute technical indicators.

Learn how to calculate stock returns, and log returns in particular. Learn why log returns are used to analyze financial data.

Learn about alpha signals, and how they can be applied to a long/short trading strategy. Learn about momentum, a common alpha signal used in trading strategies.

Learn to implement a trading strategy on your own and test to see if it has the potential to be profitable.

Learn about the overall quant workflow, including alpha signal generation, alpha combination, portfolio optimization, and trading.

Learn the importance of outliers and how to detect them. Learn about methods designed to handle outliers.

Learn about regression, and related statistical tools that pre-process data before regression analysis. See how regression relates to trading and other more advanced methods.

Learn about advanced methods for time series analysis, including ARMA, ARIMA, Kalman Filters, Particle Filters, and recurrent neural networks.

Learn about stock volatility, and how the GARCH model analysis volatility. See how volatility is used in equity trading.

Learn about pairs trading, and study the tools used in identifying stock pairs and making trading decisions.

Implement the breakout strategy, find and remove outliers, and test to see if it can be a profitable strategy.

Gain an overview of stocks, indices and funds. Also learn how to construct an index.

Learn about Exchanged Traded Funds (ETFs) and how they are used by investors and fund managers.

Learn the fundamentals of portfolio theory, which are key to designing portfolios for mutual funds, hedge funds and ETFs.

Learn how to optimize portfolios to meet certain criteria and constraints. Get hands on experience in optimizing a portfolio with the cvxpy Python library.

Build a smart beta portfolio against an index and optimize a portfolio using quadratic programming.

In the next 7 lessons and project, learn about factor investing and alpha research. These lessons and the project were designed by Jonathan Larkin, equities trader and quant investor.

Learn the theory of factor models, distinguish between alpha and risk factors, and get an overview of types of factors.

Learn how to model portfolio risk using factors.

Learn about two important types of risk models: time series and cross-sectional risk models.

Learn about Principle Component Analysis and how it's used to build risk factor models.

Learn about alpha generation and evaluation from a practitioner's perspective.

Learn about alpha research from a practitioner's perspective.

Learn about portfolio optimization using alpha factors and risk factor models.

Research and implement alpha factors, build a risk factor model. Use alpha factors and risk factors to optimize a portfolio.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Employs instructors who are recognized in quantitative trading

Teaches students to develop trading strategies, construct models, and optimize portfolios using Python

Provides hands-on experience through projects and labs, fostering practical skills development

Covers a wide range of topics, from beginner-level concepts to advanced trading techniques

Prepares students for roles in quantitative trading, financial analysis, and portfolio management

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 Quantitative Trading with these activities:

Read 'Quantitative Trading: Risk and Performance Analysis' by Ernie Chan

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Gain a comprehensive understanding of quantitative trading concepts, risk management, and performance evaluation techniques.

View Quantitative Trading on Amazon

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Acquire the book and set aside dedicated time for reading.
Read each chapter thoroughly, taking notes and highlighting key concepts.
Apply the knowledge gained to your own trading strategies or research projects.
Engage in discussions or write a summary to reinforce your understanding.
Reference the book as needed to refresh your knowledge or address specific questions.

Practice stock price prediction with historical data

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Improve your understanding of stock price movements and develop your ability to predict future prices.

Browse courses on Stock Price Prediction

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Gather historical stock data from a reputable source.
Clean and preprocess the data to remove outliers and missing values.
Apply machine learning algorithms, such as linear regression or decision trees, to predict stock prices.
Evaluate the performance of your models using metrics such as mean absolute error or R-squared.
Repeat the process for different stocks and time periods to improve your skills.

Develop a blog or website on quantitative trading strategies

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Deepen your understanding of quantitative trading concepts and share your knowledge with others.

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Research and gather information on different quantitative trading strategies.
Design and implement a blog or website to present your findings.
Write articles or create videos that explain the strategies in detail.
Provide examples and case studies to illustrate the practical application of the strategies.
Receive feedback from other traders and experts to improve your content.

One other activity

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Design and implement a multi-factor risk model

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Enhance your understanding of risk management and portfolio construction by developing a robust risk model.

Browse courses on Portfolio Optimization

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Gather data on a wide range of factors that influence asset returns.
Explore different statistical and machine learning techniques to identify and quantify the relationships between factors and asset returns.
Develop a multi-factor risk model that captures the systemic and idiosyncratic risk of a portfolio.
Validate the risk model using historical data and assess its accuracy in predicting risk.
Apply the risk model to optimize portfolios and improve risk-adjusted returns.

Career center

Learners who complete Quantitative Trading will develop knowledge and skills that may be useful to these careers:

Quantitative Analyst

Quantitative Analysts model and analyze financial data. This course may be useful in developing the necessary skills for this role, with its focus on statistical methods, data analysis, and machine learning techniques. It also provides hands-on experience with Python, which is widely used in quantitative finance.

See salaries and explore the career path for Quantitative Analyst

Quantitative Researcher

Quantitative Researchers develop and implement mathematical and statistical models to analyze financial data. This course can help develop the skills needed for this role, as it provides training in data analysis, machine learning, and statistical modeling. The hands-on experience with Python and financial data is also valuable.

See salaries and explore the career path for Quantitative Researcher

Software Engineer

Software Engineers design, develop, and maintain software systems. This course may be useful in developing the skills needed for this role, as it provides training in data analysis, software development, and machine learning. The hands-on experience with Python is also valuable.

See salaries and explore the career path for Software Engineer

Machine Learning Engineer

Machine Learning Engineers design, develop, and maintain machine learning models. This course can help develop the skills needed for this role, as it provides training in data analysis, machine learning, and software development. The hands-on experience with Python is also valuable.

See salaries and explore the career path for Machine Learning Engineer

Financial Analyst

Financial Analysts gather data on companies and industries to identify prospective investments. This course can help one develop the analytical and modeling skills necessary for this role. It covers topics such as financial statement analysis, valuation, and risk assessment.

See salaries and explore the career path for Financial Analyst

Portfolio Manager

Portfolio Managers oversee investment portfolios, making decisions on asset allocation and risk management. This course may be useful in developing the skills needed for this role, as it provides training in portfolio optimization, risk modeling, and data analysis. The hands-on experience with Python and financial data is also valuable for this role.

See salaries and explore the career path for Portfolio Manager

Risk Manager

Risk Managers identify and assess potential financial risks. This course can help develop the skills needed for this role, as it provides training in risk modeling, data analysis, and portfolio optimization. The hands-on experience with Python is also valuable for this role.

See salaries and explore the career path for Risk Manager

Financial Engineer

Financial Engineers design and develop financial products and services. This course can help develop the skills needed for this role, as it provides training in financial modeling, risk assessment, and data analysis. The hands-on experience with Python and financial data is also valuable.

See salaries and explore the career path for Financial Engineer

Trader

Traders buy and sell financial instruments on behalf of clients or their own accounts. This course can help develop the skills needed for this role, as it provides training in financial analysis, risk management, and data analysis. The hands-on experience with Python and financial data is also valuable.

See salaries and explore the career path for Trader

Data Scientist

Data Scientists use data to solve business problems. This course can help develop the skills needed for this role, as it provides training in data analysis, machine learning, and statistical modeling. The hands-on experience with Python and financial data is also valuable for this role.

See salaries and explore the career path for Data Scientist

Hedge Fund Manager

Hedge Fund Managers manage investment funds that use advanced investment strategies. This course can help develop the skills needed for this role, as it provides training in portfolio optimization, risk modeling, and data analysis. The hands-on experience with Python and financial data is also valuable.

See salaries and explore the career path for Hedge Fund Manager

Statistician

Statisticians collect, analyze, and interpret data to solve problems. This course can help develop the skills needed for this role, as it provides training in data analysis, statistical modeling, and machine learning. The hands-on experience with Python is also valuable.

See salaries and explore the career path for Statistician

Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. This course can help develop the skills needed for this role, as it provides training in data analysis, statistical modeling, and machine learning. The hands-on experience with Python is also valuable.

See salaries and explore the career path for Data Analyst

Actuary

Actuaries assess and manage financial risks. This course can help develop the skills needed for this role, as it provides training in risk modeling, data analysis, and financial mathematics.

See salaries and explore the career path for Actuary

Investment Banker

Investment Bankers provide financial advice to businesses and governments. This course may be useful in developing the skills needed for this role, as it provides training in financial analysis, valuation, and risk assessment. The hands-on experience with Python and financial data is also valuable.

See salaries and explore the career path for Investment Banker