Description

Book Synopsis

Chapter 1 Introduction.- Chapter 2 Why use Python?.- Part I Parameter Estimation.- Chapter 3 Sample Based Methods.- Chapter 4  Risk Factors Models.- Chapter 5 Black Litterman Models.- Chapter 7 Convex Risk Measures.- Chapter 8 Return-Risk Trade-Off Optimization.- Chapter 9 Real Features Constraints.- Chapter 10 Risk Parity Optimization.- Chapter 11 Robust Optimization.- Part III Machine Learning Portfolio Optimization.- Chapter 12 Hierarchical Clustering Portfolios.- Chapter 13 Graph Theory Based Portfolios.- Part IV Backtesting.- Chapter 14 Generation of Synthetic Data.- Chapter 15 Backtesting Process.- Part V Appendix.- Chapter A Linear Algebra.- Chapter B Convex Optimization.- Chapter C Mixed Integer Programming.

Advanced Portfolio Optimization

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    A Hardback by Dany Cajas

    3 in stock


      View other formats and editions of Advanced Portfolio Optimization by Dany Cajas

      Publisher: Springer
      Publication Date: 09/04/2025
      ISBN13: 9783031843037, 978-3031843037
      ISBN10:
      Also in:
      Probability and statistics

      Description

      Book Synopsis

      Chapter 1 Introduction.- Chapter 2 Why use Python?.- Part I Parameter Estimation.- Chapter 3 Sample Based Methods.- Chapter 4  Risk Factors Models.- Chapter 5 Black Litterman Models.- Chapter 7 Convex Risk Measures.- Chapter 8 Return-Risk Trade-Off Optimization.- Chapter 9 Real Features Constraints.- Chapter 10 Risk Parity Optimization.- Chapter 11 Robust Optimization.- Part III Machine Learning Portfolio Optimization.- Chapter 12 Hierarchical Clustering Portfolios.- Chapter 13 Graph Theory Based Portfolios.- Part IV Backtesting.- Chapter 14 Generation of Synthetic Data.- Chapter 15 Backtesting Process.- Part V Appendix.- Chapter A Linear Algebra.- Chapter B Convex Optimization.- Chapter C Mixed Integer Programming.

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