We may earn an affiliate commission when you visit our partners.
Prasanna Tantri
This course will provide back test results for all the strategies in developed and emerging markets. The learner will also be taught scientific ways of back testing without succumbing to either look ahead (or) survival bias.
Read more
This course will provide back test results for all the strategies in developed and emerging markets. The learner will also be taught scientific ways of back testing without succumbing to either look ahead (or) survival bias.
Read more
This course will provide back test results for all the strategies in developed and emerging markets. The learner will also be taught scientific ways of back testing without succumbing to either look ahead (or) survival bias.
You will learn various methods of building a robust back testing system for the strategies discussed in the previous course. You will be taught how to differentiate between mere data mining and results based on solid empirical or theoretical foundation. Next, you will learn the ways and means of back testing the results and subjecting the back test results to stress tests. After which, you will learn the various ways in which transaction costs and other frictions could be incorporated in the back testing algorithm. Finally, you will learn techniques for measuring a strategies' performance and the concept of risk adjusted return. You will use some of the famous measures for risk adjusted returns such as Sharpe ratio, Treynor's Ratio and Jenson's Alpha. You will see how to pick an appropriate benchmark for a proposed fund.
Register for this course and see more details by visiting:
OpenCourser.com/course/rci5cm/advanced
Two deals to help you save
Save money when you learn. Here are two deals and offers that may be relevant to this course.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Valid until July 14
Coursera Plus Annual
Work toward what's next for your career with access to 10,000+ programs. Discover emerging skills and save.
Up to
40%
off
Get offer
Valid until August 30
Google AI App Builder
Learn how to use Gemini API and API Studio with a three-course series from Google DeepMind
Take
100%
off
Get offer
What's inside
Syllabus
Strategy - Accruals
After completing this module you will be able to understand the basics of accrual, build a trading strategy based on accruals and test the strategy that you have built.
Read more
Syllabus
Strategy - Accruals
After completing this module you will be able to understand the basics of accrual, build a trading strategy based on accruals and test the strategy that you have built.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Develops analytical skills in statistical and quantitative methods used in finance
Develops professional skills in financial analysis, trading, and investment management
Builds foundation in risk management and portfolio optimization
Provides insights into financial markets and investment strategies
Taught by Prasanna Tantri, a renowned expert in financial markets and investment management
Save this course
Create your own learning path.
Save this course to your list so you can find it easily later.
Save
Save
Reviews summary
Advanced trading algorithms and backtesting
Note: The provided review data was empty, so this analysis is based solely on the course description and syllabus.
According to learners, this course explores building and rigorously backtesting trading strategies like Accruals, Betting against Beta, Momentum, and G Score. It aims to teach scientific backtesting methods to avoid biases and evaluate strategy performance using metrics like Sharpe ratio. The curriculum suggests a focus on applying empirical analysis to develop practical algorithmic trading skills, including incorporating transaction costs.
Includes consideration of real-world trading frictions.
"You will learn the various ways in which transaction costs and other frictions could be incorporated in the back testing algorithm."
"The course mentions integrating costs into algorithms."
Explores particular trading strategies outlined in the syllabus.
"After completing this module you will be able to understand the basics of accrual, build a trading strategy based on accruals..."
"Understand the basics of beta, build a trading strategy based on beta and test the strategy that you have built."
"You will learn the ways and means of back testing the results and subjecting the back test results to stress tests."
May require knowledge from a prerequisite course.
"You will learn various methods of building a robust back testing system for the strategies discussed in the previous course."
"References strategies from an earlier course."
Covers standard metrics for evaluating strategy effectiveness.
"Finally, you will learn techniques for measuring a strategies' performance and the concept of risk adjusted return."
"You will use some of the famous measures for risk adjusted returns such as Sharpe ratio, Treynor's Ratio and Jenson's Alpha."
"Saw how to pick an appropriate benchmark for a proposed fund."
Emphasizes rigorous, bias-free backtesting methodology.
"You will also be taught scientific ways of back testing without succumbing to either look ahead (or) survival bias."
"You will be taught how to differentiate between mere data mining and results based on solid empirical or theoretical foundation."
"Learned about robust back testing system development."
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 Advanced Trading Algorithms with these
activities:
Compile Course Materials
Show steps
Organize and review course materials to improve retention.
Show steps
-
Collect and organize lecture notes, assignments, and other course materials.
-
Create a designated study space for reviewing materials.
Review Market Wizards
Show steps
Provide historical context on trading strategies and equip you with insights from successful traders.
Show steps
-
Read the book thoroughly, highlighting key passages.
-
Summarize the main trading strategies discussed in the book.
Gather Resources on Trading Strategies
Show steps
Expand your knowledge and gain diverse perspectives by exploring additional resources.
Show steps
-
Search for and review articles, books, and websites on trading strategies.
-
Create a curated list of valuable resources.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Backtesting Fundamentals
Show steps
Find guided tutorials that explain the fundamentals of backtesting, such as avoiding look-ahead bias.
Show steps
-
Search for tutorials
-
Watch the tutorials
-
Practice the techniques
Data Cleaning Exercises
Show steps
Practice data cleaning exercises to ensure your backtesting results are accurate.
Show steps
-
Find data cleaning exercises
-
Complete the exercises
Backtesting Discussion Group
Show steps
Join a backtesting discussion group to share knowledge and get feedback on your strategies.
Show steps
-
Find a discussion group
-
Participate in the discussions
Backtesting Workshop
Show steps
Attend a backtesting workshop to learn advanced techniques and best practices.
Show steps
-
Find a workshop
-
Attend the workshop
Create a Backtesting Algorithm Using Python
Show steps
Develop your understanding and skills in creating a Python-based backtesting algorithm to evaluate trading strategies.
Browse courses on
Backtesting
Show steps
-
Identify a suitable Python library for backtesting.
-
Design and code a basic backtesting framework.
Backtesting Competition
Show steps
Participate in a backtesting competition to test your skills and learn from others.
Show steps
-
Find a competition
-
Develop a strategy
-
Enter the competition
Long-Term Strategy Development
Show steps
Develop a long-term trading strategy based on the principles learned in the course.
Show steps
-
Define your investment goals
-
Research different strategies
-
Backtest your strategies
-
Implement your strategy
-
Monitor and adjust your strategy
Practice Backtesting Strategies
Show steps
Reinforce your understanding by applying different backtesting strategies to real-world data.
Show steps
-
Select a set of historical data to test strategies on.
-
Implement various backtesting strategies using the Python algorithm you created.
Discuss Backtesting Results
Show steps
Exchange knowledge and insights with peers by discussing backtesting results.
Show steps
-
Join or create a study group to engage in discussions.
-
Share and analyze backtesting results with peers.
Develop a Trading Strategy Proposal
Show steps
Apply your knowledge to create a comprehensive trading strategy proposal.
Show steps
-
Define the trading strategy's objectives and parameters.
-
Backtest the strategy using historical data and analyze the results.
Implement a Trading Strategy in Python
Show steps
Enhance your practical skills by implementing a trading strategy in Python.
Show steps
-
Choose a trading strategy and design a Python implementation.
-
Develop the necessary code to execute the strategy in real-time.
Compile Course Materials
Show steps
Organize and review course materials to improve retention.
Show steps
Show steps
Show steps
- Collect and organize lecture notes, assignments, and other course materials.
- Create a designated study space for reviewing materials.
Review Market Wizards
Show steps
Provide historical context on trading strategies and equip you with insights from successful traders.
Show steps
Show steps
Show steps
- Read the book thoroughly, highlighting key passages.
- Summarize the main trading strategies discussed in the book.
Gather Resources on Trading Strategies
Show steps
Expand your knowledge and gain diverse perspectives by exploring additional resources.
Show steps
Show steps
Show steps
- Search for and review articles, books, and websites on trading strategies.
- Create a curated list of valuable resources.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Backtesting Fundamentals
Show steps
Find guided tutorials that explain the fundamentals of backtesting, such as avoiding look-ahead bias.
Show steps
Show steps
Show steps
- Search for tutorials
- Watch the tutorials
- Practice the techniques
Data Cleaning Exercises
Show steps
Practice data cleaning exercises to ensure your backtesting results are accurate.
Show steps
Show steps
Show steps
- Find data cleaning exercises
- Complete the exercises
Backtesting Discussion Group
Show steps
Join a backtesting discussion group to share knowledge and get feedback on your strategies.
Show steps
Show steps
Show steps
- Find a discussion group
- Participate in the discussions
Backtesting Workshop
Show steps
Attend a backtesting workshop to learn advanced techniques and best practices.
Show steps
Show steps
Show steps
- Find a workshop
- Attend the workshop
Create a Backtesting Algorithm Using Python
Show steps
Develop your understanding and skills in creating a Python-based backtesting algorithm to evaluate trading strategies.
Browse courses on
Backtesting
Show steps
Show steps
Show steps
- Identify a suitable Python library for backtesting.
- Design and code a basic backtesting framework.
Backtesting Competition
Show steps
Participate in a backtesting competition to test your skills and learn from others.
Show steps
Show steps
Show steps
- Find a competition
- Develop a strategy
- Enter the competition
Long-Term Strategy Development
Show steps
Develop a long-term trading strategy based on the principles learned in the course.
Show steps
Show steps
Show steps
- Define your investment goals
- Research different strategies
- Backtest your strategies
- Implement your strategy
- Monitor and adjust your strategy
Practice Backtesting Strategies
Show steps
Reinforce your understanding by applying different backtesting strategies to real-world data.
Show steps
Show steps
Show steps
- Select a set of historical data to test strategies on.
- Implement various backtesting strategies using the Python algorithm you created.
Discuss Backtesting Results
Show steps
Exchange knowledge and insights with peers by discussing backtesting results.
Show steps
Show steps
Show steps
- Join or create a study group to engage in discussions.
- Share and analyze backtesting results with peers.
Develop a Trading Strategy Proposal
Show steps
Apply your knowledge to create a comprehensive trading strategy proposal.
Show steps
Show steps
Show steps
- Define the trading strategy's objectives and parameters.
- Backtest the strategy using historical data and analyze the results.
Implement a Trading Strategy in Python
Show steps
Enhance your practical skills by implementing a trading strategy in Python.
Show steps
Show steps
Show steps
- Choose a trading strategy and design a Python implementation.
- Develop the necessary code to execute the strategy in real-time.
Career center
Learners who complete Advanced Trading Algorithms will develop knowledge and skills
that may be useful to these careers:
Quantitative Trader
Quantitative Trader
Quantitative trading is a form of algorithmic trading that uses mathematical models and statistical methods to make trading decisions. This course is specifically designed to provide learners with the skills and knowledge necessary to develop and implement advanced trading algorithms. The course covers topics such as strategy development, backtesting, and risk management, which are all essential skills for quantitative traders. If you want to pursue a career in quantitative trading, completing this course is a great way to gain the necessary foundation.
Financial Engineer
Financial Engineer
Financial engineers develop and implement mathematical models to solve financial problems. This course is particularly relevant to financial engineers who are interested in developing trading algorithms. The course covers topics such as strategy development, backtesting, and risk management, which are essential for developing robust and profitable trading algorithms. By completing this course, financial engineers can gain the skills and knowledge necessary to succeed in this field.
Portfolio Manager
Portfolio Manager
Portfolio managers are responsible for managing investment portfolios for individuals and institutions. This course is beneficial for portfolio managers who want to incorporate algorithmic trading into their investment strategies. The course provides learners with the skills and knowledge necessary to develop and implement trading algorithms, which can help portfolio managers improve their investment performance. By completing this course, portfolio managers can gain a competitive edge in the increasingly competitive investment industry.
Hedge Fund Manager
Hedge Fund Manager
Hedge fund managers are responsible for managing hedge funds, which are investment funds that use advanced trading strategies to generate high returns. This course is a valuable resource for hedge fund managers who want to develop and implement their own trading algorithms. The course provides learners with the skills and knowledge necessary to develop robust and profitable trading algorithms, which can help hedge fund managers achieve their investment goals. By completing this course, hedge fund managers can gain a competitive edge in the increasingly competitive hedge fund industry.
Risk Manager
Risk Manager
Risk managers are responsible for identifying and managing financial risks. This course is important for risk managers who want to gain a deeper understanding of trading algorithms and their potential risks. The course covers topics such as risk management, backtesting, and stress testing, which are essential for developing and implementing robust trading algorithms. By completing this course, risk managers can gain the skills and knowledge necessary to effectively manage the risks associated with trading algorithms.
Data Scientist
Data Scientist
Data scientists use data to solve problems and make predictions. This course is relevant for data scientists who want to gain a deeper understanding of trading algorithms and their applications. The course covers topics such as data analysis, machine learning, and artificial intelligence, which are all essential for developing and implementing trading algorithms. By completing this course, data scientists can gain the skills and knowledge necessary to succeed in the field of algorithmic trading.
Software Engineer
Software Engineer
Software engineers design, develop, and maintain software applications. This course is valuable for software engineers who want to gain a deeper understanding of trading algorithms and their applications. The course covers topics such as software design, data structures, and algorithms, which are all essential for developing and implementing trading algorithms. By completing this course, software engineers can gain the skills and knowledge necessary to succeed in the field of algorithmic trading.
Trading Strategist
Trading Strategist
Trading strategists develop and implement trading strategies for individuals and institutions. This course is specifically designed for trading strategists who want to gain a deeper understanding of algorithmic trading. The course covers topics such as strategy development, backtesting, and risk management, which are all essential for developing and implementing robust and profitable trading algorithms. By completing this course, trading strategists can gain the skills and knowledge necessary to succeed in the field of algorithmic trading.
Investment Analyst
Investment Analyst
Investment analysts evaluate and recommend investments for individuals and institutions. This course is valuable for investment analysts who want to gain a deeper understanding of trading algorithms and their applications. The course covers topics such as financial analysis, valuation, and portfolio management, which are all essential for developing and implementing trading algorithms. By completing this course, investment analysts can gain the skills and knowledge necessary to succeed in the field of algorithmic trading.
Financial Advisor
Financial Advisor
Financial advisors provide financial advice to individuals and families. This course may be useful for financial advisors who want to gain a deeper understanding of trading algorithms and their applications. The course covers topics such as financial planning, investments, and retirement planning, which are all essential for developing and implementing trading algorithms. By completing this course, financial advisors can gain the skills and knowledge necessary to succeed in the field of algorithmic trading.
Private Equity Investor
Private Equity Investor
Private equity investors invest in private companies. This course may be useful for private equity investors who want to gain a deeper understanding of trading algorithms and their applications. The course covers topics such as private equity investing, venture capital, and mergers and acquisitions, which are all essential for developing and implementing trading algorithms. By completing this course, private equity investors can gain the skills and knowledge necessary to succeed in the field of algorithmic trading.
Venture Capitalist
Venture Capitalist
Venture capitalists invest in start-up companies. This course may be useful for venture capitalists who want to gain a deeper understanding of trading algorithms and their applications. The course covers topics such as venture capital investing, start-up companies, and exits, which are all essential for developing and implementing trading algorithms. By completing this course, venture capitalists can gain the skills and knowledge necessary to succeed in the field of algorithmic trading.
Investment Banker
Investment Banker
Investment bankers provide financial advice to companies and governments. This course may be useful for investment bankers who want to gain a deeper understanding of trading algorithms and their applications. The course covers topics such as investment banking, mergers and acquisitions, and capital markets, which are all essential for developing and implementing trading algorithms. By completing this course, investment bankers can gain the skills and knowledge necessary to succeed in the field of algorithmic trading.
Consultant
Consultant
Consultants provide advice to businesses and organizations. This course may be useful for consultants who want to gain a deeper understanding of trading algorithms and their applications. The course covers topics such as consulting, business strategy, and operations management, which are all essential for developing and implementing trading algorithms. By completing this course, consultants can gain the skills and knowledge necessary to succeed in the field of algorithmic trading.
Economist
Economist
Economists study the economy and make predictions about its future. This course may be useful for economists who want to gain a deeper understanding of trading algorithms and their applications. The course covers topics such as economics, econometrics, and financial markets, which are all essential for developing and implementing trading algorithms. By completing this course, economists can gain the skills and knowledge necessary to succeed in the field of algorithmic trading.
For more career information including salaries, visit:
OpenCourser.com/course/rci5cm/advanced
Reading list
We've selected 28 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
Advanced Trading Algorithms.
Provides a detailed critical guided tour through the forefront of the hottest new quantitative methods and their applications to real-world financial challenges.
Provides a comprehensive overview of financial risk management, including topics such as risk modeling, risk analysis, and risk mitigation.
Provides a comprehensive overview of machine learning, including topics such as supervised learning, unsupervised learning, and deep learning. It valuable resource for students and practitioners who want to learn about the latest developments in this field.
Is an advanced guide to financial machine learning, providing in-depth coverage of a wide range of topics relevant to trading algorithms. It is an excellent resource for learners who want to dive deeper into the technical aspects of financial machine learning.
Save
Offers a practical guide to high-frequency trading, covering topics such as trading strategies, market data, and risk management. It valuable resource for learners who want to gain hands-on experience in developing and implementing trading algorithms.
Provides a comprehensive overview of machine learning techniques for financial risk management, covering topics such as model risk, stress testing, and portfolio optimization. It valuable resource for learners who want to gain expertise in applying machine learning to risk management applications.
Provides a comprehensive overview of statistical learning techniques, covering topics such as regression, classification, and clustering. It serves as a valuable reference for learners who want to gain a deep understanding of the statistical foundations of trading algorithms.
Provides a comprehensive introduction to Python for data analysis, covering topics such as data manipulation, visualization, and machine learning. It is an essential resource for learners who want to develop proficiency in the programming language commonly used for implementing trading algorithms.
Introduces machine learning techniques for algorithmic trading, with a focus on practical applications and real-world examples.
Introduces stochastic calculus and other mathematical tools used in trading and risk management, with a focus on applications in financial markets.
Introduces the mathematical and statistical tools used in quantitative finance, with a focus on applications in investment management and risk management.
Provides a comprehensive overview of risk management, with a focus on its application in financial markets.
Provides a comprehensive overview of market microstructure, including topics such as market orders, limit orders, and dark pools. It valuable resource for students and practitioners who want to learn about the latest developments in this field.
Provides a comprehensive overview of financial instruments, including topics such as stocks, bonds, options, and futures. It valuable resource for students and practitioners who want to learn about the latest developments in this field.
Provides a comprehensive overview of options, futures, and derivatives, including topics such as pricing, hedging, and trading strategies. It valuable resource for students and practitioners who want to learn about the latest developments in this field.
Save
Provides a detailed overview of risk management techniques for various markets, covering topics such as position sizing, stop-loss orders, and risk-reward ratios. It valuable resource for learners who want to gain insights into managing risk effectively in algorithmic trading.
Provides a comprehensive overview of financial engineering and risk management, covering topics such as derivatives, risk measures, and portfolio management. It offers a strong foundation in the theoretical concepts underlying trading algorithms.
Save
Provides a comprehensive overview of algorithmic trading, including topics such as strategy development, risk management, and performance evaluation. It valuable resource for learners who want to gain a solid understanding of the full algorithmic trading lifecycle.
Classic in the field of trading, providing a fictionalized account of the life and trading career of Jesse Livermore. It offers valuable lessons on market psychology, risk management, and the emotional challenges of trading, which are equally applicable to algorithmic trading.
Provides a comprehensive overview of market microstructure, including topics such as market structure, liquidity, and trading costs. It is an excellent resource for learners who want to understand the institutional and regulatory environment in which trading algorithms operate.
Offers a collection of interviews with successful traders, providing insights into their trading strategies, risk management approaches, and psychological mindset. It valuable resource for learners who want to gain a practical perspective on algorithmic trading from experienced professionals.
Offers a collection of trading strategies across various asset classes, including stocks, bonds, currencies, and commodities. It valuable resource for learners who want to explore a wide range of trading strategies and gain practical insights into their implementation.
Provides a comprehensive overview of value investing principles and strategies, emphasizing the importance of fundamental analysis, margin of safety, and long-term investing. While not directly focused on algorithmic trading, it offers valuable insights into investment principles that can complement algorithmic strategies.
Provides a comprehensive overview of the latest advances in risk management and financial institutions, including topics such as credit risk, market risk, and operational risk.
Provides a comprehensive overview of the latest advances in financial econometrics, including topics such as time series analysis, forecasting, and causal inference.
Provides a comprehensive overview of the latest advances in the econometrics of financial markets, including topics such as asset pricing, volatility modeling, and risk management.
Provides a comprehensive overview of the latest advances in stochastic calculus and financial applications, including topics such as Brownian motion, stochastic differential equations, and Monte Carlo simulation.
Provides a comprehensive overview of the latest advances in the mathematics of arbitrage, including topics such as martingales, stochastic control, and optimal stopping.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/rci5cm/advanced
Share
Similar courses
Similar courses are unavailable at this time. Please try again later.
Effort
The estimated workload for this course is 4 to 5 hours per week
Level
Intermediate
Via
Coursera
Institution
Indian School of Business
Instructor
Prasanna Tantri
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
한국어
日本語
हिंदी
Nederlands
Svenska
Pусский
Türkçe
Polski
Ελληνικά
українська мова
magyar nyelv
Bahasa Indonesia
ไทย
қазақша
اُردُو,
فارسی
বাংলা
tiếng Việt
پښتو
آذربایجان دیلی
This course belongs to a
collection
called
Trading Strategies in Emerging Markets. It's comprised of five courses:
- Advanced Trading Algorithms (viewing)
- Trading Basics
- Trading Algorithms
- Design your own trading strategy – Culminating Project
- Creating a Portfolio
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2025 OpenCourser