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size
15.24 x 2.29 x 22.86 cm
Product Information
Ideal For
General Readers, Fiction Lovers, Mythology & Historical Fiction Readers, Indian Mythology Enthusiasts, Young Adults (YA) & Adults, College Students, Competitive Exam Aspirants (General Reading / Culture), Gift Purpose (Books Gift Set), Spiritual & Philosophy Interest Readers, Library / Book Collection Buyers
Country Of Origin
India
About Author
Ernie Chan Is A Quantitative Trader, Researcher, And Author Known For Making Algorithmic Trading Accessible To Individual Investors.Chan Has Worked At Several Prominent Financial Firms, Including Ibm, Morgan Stanley, And Credit Suisse, Applying Quantitative Methods To Trading Strategies.
Author Name
Ernie Chan
Genre
Business & Finance
No Of Pages
224
Publisher
Books Kingdom
Product Description
- Premium Quality: Algorithmic Trading: Winning Strategies and Their Rationale is praised as an insightful book on quantitative trading written by a seasoned practitioner, with an emphasis on real examples as opposed to just theory.
- Product Design: Concepts are not only described, they are brought to life with actual trading strategies, which give the reader insight into how and why each strategy was developed, how it was implemented, and even how it was coded.
- User Experience: This book is a valuable resource for anyone looking to create their own systematic trading strategies and those involved in manager selection, where the knowledge contained in this book will lead to a more informed and nuanced conversation with managers.
- Versatile Occasion: Suited to individual investors, quantitative researchers, finance students, and professional fund managers seeking a rigorous yet accessible guide to building and evaluating algorithmic trading systems.
- Quality Assurance: The endorsement from Daren Smith, CFA, CAIA, FSA, President and Chief Investment Officer, affirms the book's standing as a credible and practically oriented resource within the quantitative finance community.
- Ideal For: This hardcover edition is ideal for finance professionals, data-driven traders, college students in quantitative disciplines, and anyone seeking to develop a deeper understanding of systematic investment strategies.