We may earn an affiliate commission when you visit our partners.

Finding Alphas

Igor Tulchinsky

Discover the ins and outs of designing predictive trading models

Drawing on the expertise of WorldQuant's global network, this new edition of Finding Alphas: A Quantitative Approach to Building Trading Strategies contains significant changes and updates to the original material, with new and updated data and examples.

Nine chapters have been added about alphas - models used to make predictions regarding the prices of financial instruments. The new chapters cover topics including alpha correlation, controlling biases, exchange-traded funds, event-driven investing, index alphas, intraday data in alpha research, intraday trading, machine learning, and the triple axis plan for identifying alphas.

- Provides more references to the academic literature

- Includes new, high-quality material

- Organizes content in a practical and easy-to-follow manner

- Adds new alpha examples with formulas and explanations

If you're looking for the latest information on building trading strategies from a quantitative approach, this book has you covered.

Read on Amazon
Read this for free with Kindle Unlimited

Save this book

Create your own learning path. Save this book to your list so you can find it easily later.
Save

Share

Help others find this book page by sharing it with your friends and followers:
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