Build a Robo Advisor with Python (From Scratch) (MEAP V06)

Description

In Build a Robo Advisor with Python (From Scratch), you’ll design and develop a working financial advisor that can manage a real investing strategy. You’ll add new features to your advisor chapter-by-chapter, including determining the optimal weight of cryptocurrency in your portfolio, rebalancing to keep your investments on target while minimizing taxes, and using reinforcement learning to find a “glide path” that can maximize how long your money will last in retirement. Best of all, the skills you learn in reinforcement learning, convex optimization, and Monte Carlo methods can be applied to numerous lucrative fields beyond the domain of finance. In Build a Robo Advisor with Python (From Scratch) you’ll learn how to: • Measure returns and estimate the benefits of robo advisors • Use Monte Carlo simulations to build and test financial planning tools • Construct diversified, efficient portfolios using optimization and other advanced methods • Implement and evaluate rebalancing methods to track a target portfolio over time • Decrease taxes through tax-loss harvesting and optimized withdrawal sequencing • Use reinforcement learning to find the optimal investment path up to, and after, retirement Copyright_2023_Manning_Publications welcome 1_The_Rise_of_Robo-Advisors 2_An_Introduction_to_Portfolio_Construction 3_Estimating_Expected_Returns_and_Covariances 4_ETFs:_The_Building_Blocks_of_Robo-Portfolios 5_Monte_Carlo_Simulations 6_Asset_Location 7_Measuring_and_Evaluating_Returns 8_Optimization_and_Portfolio_Construction:_A_first_look 9_Asset_Allocation_by_Risk:_Introduction_to_Risk_Parity 10_The_Black-Litterman_Model