Nonlinear Valuation and Non-Gaussian Risks in Finance
eBook - PDF

Nonlinear Valuation and Non-Gaussian Risks in Finance

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Nonlinear Valuation and Non-Gaussian Risks in Finance

About this book

What happens to risk as the economic horizon goes to zero and risk is seen as an exposure to a change in state that may occur instantaneously at any time? All activities that have been undertaken statically at a fixed finite horizon can now be reconsidered dynamically at a zero time horizon, with arrival rates at the core of the modeling. This book, aimed at practitioners and researchers in financial risk, delivers the theoretical framework and various applications of the newly established dynamic conic finance theory. The result is a nonlinear non-Gaussian valuation framework for risk management in finance. Risk-free assets disappear and low risk portfolios must pay for their risk reduction with negative expected returns. Hedges may be constructed to enhance value by exploiting risk interactions. Dynamic trading mechanisms are synthesized by machine learning algorithms. Optimal exposures are designed for option positioning simultaneously across all strikes and maturities.

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Yes, you can access Nonlinear Valuation and Non-Gaussian Risks in Finance by Dilip B. Madan,Wim Schoutens in PDF and/or ePUB format, as well as other popular books in Matemáticas & Matemática aplicada. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half-title Page
  3. Title Page
  4. Copyright Page
  5. Dedication
  6. Contents
  7. Preface
  8. Acknowledgments
  9. 1 Introduction
  10. 2 Univariate Risk Representation Using Arrival Rates
  11. 3 Estimation of Univariate Arrival Rates from Time Series Data
  12. 4 Estimation of Univariate Arrival Rates from Option Surface Data
  13. 5 Multivariate Arrival Rates Associated with Prespecified Univariate Arrival Rates
  14. 6 The Measure-Distorted Valuation As a Financial Objective
  15. 7 Representing Market Realities
  16. 8 Measure-Distorted Value-Maximizing Hedges in Practice
  17. 9 Conic Hedging Contributions and Comparisons
  18. 10 Designing Optimal Univariate Exposures
  19. 11 Multivariate Static Hedge Designs Using Measure-Distorted Valuations
  20. 12 Static Portfolio Allocation Theory for Measure-Distorted Valuations
  21. 13 Dynamic Valuation via Nonlinear Martingales and Associated Backward Stochastic Partial Integro-Differential Equations
  22. 14 Dynamic Portfolio Theory
  23. 15 Enterprise Valuation Using Infinite and Finite Horizon Valuation of Terminal Liquidation
  24. 16 Economic Acceptability
  25. 17 Trading Markovian Models
  26. 18 Market-Implied Measure-Distortion Parameters
  27. References
  28. Index