menu
{ "item_title" : "Portfolio Optimization", "item_author" : [" Daniel P. Palomar "], "item_description" : "This comprehensive guide to the world of financial data modeling and portfolio design is a must-read for anyone looking to understand and apply portfolio optimization in a practical context. It bridges the gap between mathematical formulations and the design of practical numerical algorithms. It explores a range of methods, from basic time series models to cutting-edge financial graph estimation approaches. The portfolio formulations span from Markowitz's original 1952 mean-variance portfolio to more advanced formulations, including downside risk portfolios, drawdown portfolios, risk parity portfolios, robust portfolios, bootstrapped portfolios, index tracking, pairs trading, and deep-learning portfolios. Enriched with a remarkable collection of numerical experiments and more than 200 figures, this is a valuable resource for researchers and finance industry practitioners. With slides, R and Python code examples, and exercise solutions available online, it serves as a textbook for portfolio optimization and financial data modeling courses, at advanced undergraduate and graduate level.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/1/00/942/808/100942808X_b.jpg", "price_data" : { "retail_price" : "99.99", "online_price" : "99.99", "our_price" : "99.99", "club_price" : "99.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Portfolio Optimization|Daniel P. Palomar

Portfolio Optimization

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

This comprehensive guide to the world of financial data modeling and portfolio design is a must-read for anyone looking to understand and apply portfolio optimization in a practical context. It bridges the gap between mathematical formulations and the design of practical numerical algorithms. It explores a range of methods, from basic time series models to cutting-edge financial graph estimation approaches. The portfolio formulations span from Markowitz's original 1952 mean-variance portfolio to more advanced formulations, including downside risk portfolios, drawdown portfolios, risk parity portfolios, robust portfolios, bootstrapped portfolios, index tracking, pairs trading, and deep-learning portfolios. Enriched with a remarkable collection of numerical experiments and more than 200 figures, this is a valuable resource for researchers and finance industry practitioners. With slides, R and Python code examples, and exercise solutions available online, it serves as a textbook for portfolio optimization and financial data modeling courses, at advanced undergraduate and graduate level.

This item is Non-Returnable

Details

  • ISBN-13: 9781009428088
  • ISBN-10: 100942808X
  • Publisher: Cambridge University Press
  • Publish Date: June 2025
  • Dimensions: 10 x 7 x 1.31 inches
  • Shipping Weight: 2.79 pounds
  • Page Count: 608

Related Categories

You May Also Like...

    1

BAM Customer Reviews