Build a Robo-Advisor with Python (from Scratch): Automate Your Financial and Investment Decisions

Build a Robo-Advisor with Python (from Scratch): Automate Your Financial and Investment Decisions
- Use Monte Carlo simulations to build and test financial planning tools
- Construct diversified, efficient portfolios using optimization and other 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 Automated "robo-advisors" are commonplace in financial services, thanks to their ability to give high-quality investment advice at a fraction of the cost of human advisors. Build a Robo-Advisor with Python (From Scratch) teaches you to develop one of these powerful, flexible tools using popular and free Python libraries. You'll master practical Python skills in demand in financial services, and financial planning skills that will help you take the best care of your money. All examples are accompanied by working Python code, and are easy to adjust for investors anywhere in the world. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology Millions of investors use robo-advisors as an alternative to human financial advisors. In this one-of-a-kind guide, you'll learn how to build one of your own. Your robo-advisor will assist you with all aspects of financial planning, including saving for retirement, creating a diversified portfolio, and decreasing your tax bill. And along the way, you'll learn a lot about Python and finance! About the book Build a Robo-Advisor with Python (From Scratch) guides you step-by-step, feature-by-feature as you create a robo-advisor from the ground up. As you go, you'll dive into techniques like reinforcement learning, convex optimization, and Monte Carlo methods that you can apply even outside the field of FinTech. When you finish, your powerful assistant will be able to create optimal asset allocations, rebalance investments while minimizing t
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- Use Monte Carlo simulations to build and test financial planning tools
- Construct diversified, efficient portfolios using optimization and other 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 Automated "robo-advisors" are commonplace in financial services, thanks to their ability to give high-quality investment advice at a fraction of the cost of human advisors. Build a Robo-Advisor with Python (From Scratch) teaches you to develop one of these powerful, flexible tools using popular and free Python libraries. You'll master practical Python skills in demand in financial services, and financial planning skills that will help you take the best care of your money. All examples are accompanied by working Python code, and are easy to adjust for investors anywhere in the world. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology Millions of investors use robo-advisors as an alternative to human financial advisors. In this one-of-a-kind guide, you'll learn how to build one of your own. Your robo-advisor will assist you with all aspects of financial planning, including saving for retirement, creating a diversified portfolio, and decreasing your tax bill. And along the way, you'll learn a lot about Python and finance! About the book Build a Robo-Advisor with Python (From Scratch) guides you step-by-step, feature-by-feature as you create a robo-advisor from the ground up. As you go, you'll dive into techniques like reinforcement learning, convex optimization, and Monte Carlo methods that you can apply even outside the field of FinTech. When you finish, your powerful assistant will be able to create optimal asset allocations, rebalance investments while minimizing t
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