Applied probabilistic calculus for financial engineering : an introduction using R

Applied probabilistic calculus for financial engineering an introduction using R

Illustrates how R may be used successfully to solve problems in quantitative finance Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R provides R recipes for asset allocation and portfolio optimization problems. It begins by introducing all the necessary probabilistic...

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Detalles Bibliográficos
Otros Autores: Chan, B. K. C. author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Hoboken, New Jersey : Wiley 2017.
Edición:1st edition
Materias:
Financial engineering > Mathematical models.
Probabilities.
Calculus.
R (Computer program language)
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009631277206719
Tabla de Contenidos:
  • Intro
  • Title Page
  • Copyright
  • Dedication
  • Preface
  • About the Companion Website
  • Chapter 1: Introduction to Financial Engineering
  • 1.1 What Is Financial Engineering?
  • 1.2 The Meaning of the Title of This Book
  • 1.3 The Continuing Challenge in Financial Engineering
  • 1.4 "Financial Engineering 101": Modern Portfolio Theory
  • 1.5 Asset Class Assumptions Modeling
  • 1.6 Some Typical Examples of Proprietary Investment Funds
  • 1.7 The Dow Jones Industrial Average (DJIA) and Inflation
  • 1.8 Some Less Commendable Stock Investment Approaches
  • 1.9 Developing Tools for Financial Engineering Analysis
  • Review Questions
  • Chapter 2: Probabilistic Calculus for Modeling Financial Engineering
  • 2.1 Introduction to Financial Engineering
  • 2.2 Mathematical Modeling in Financial Engineering
  • 2.3 Building an Effective Financial Model from GBM via Probabilistic Calculus
  • 2.4 A Continuous Financial Model Using Probabilistic Calculus: Stochastic Calculus, Ito Calculus
  • 2.5 A Numerical Study of the Geometric Brownian Motion (GBM) Model and the Random Walk Model Using R
  • Review Questions and Exercises
  • Chapter 3: Classical Mathematical Models in Financial Engineering and Modern Portfolio Theory
  • 3.1 An Introduction to the Cost of Money in the Financial Market
  • 3.2 Modern Theories of Portfolio Optimization
  • 3.3 The Black-Litterman Model
  • 3.4 The Black-Scholes Option Pricing Model
  • 3.5 The Black-Litterman Model
  • 3.6 The Black-Litterman Model
  • 3.7 The Black-Scholes Option Pricing Model
  • 3.8 Some Worked Examples
  • Review Questions and Exercises
  • Solutions to Exercise 3: The Black-Scholes Equation
  • Chapter 4: Data Analysis Using R Programming
  • 4.1 Data and Data Processing
  • Review Questions for Section 4.1
  • 4.2 Beginning R
  • Review Questions for Section 4.2
  • 4.3 R as a Calculator.
  • Review Questions for Section 4.3
  • Exercises for Section 4.3
  • 4.4 Using R in Data Analysis in Financial Engineering
  • Review Questions for Section 4.4
  • 4.5 Univariate, Bivariate, and Multivariate Data Analysis
  • Review Questions for Section 4.5
  • Exercise for Section 4.5
  • Chapter 5: Assets Allocation Using R
  • 5.1 Risk Aversion and the Assets Allocation Process
  • 5.2 Classical Assets Allocation Approaches
  • 5.3 Allocation with Time Varying Risk Aversion
  • 5.4 Variable Risk Preference Bias
  • 5.5 A Unified Approach for Time Varying Risk Aversion
  • 5.6 Assets Allocation Worked Examples
  • Review Questions and Exercises
  • Chapter 6: Financial Risk Modeling and Portfolio Optimization Using R
  • 6.1 Introduction to the Optimization Process
  • 6.2 Optimization Methodologies in Probabilistic Calculus for Financial Engineering
  • 6.3 Financial Risk Modeling and Portfolio Optimization
  • 6.4 Portfolio Optimization Using R1
  • Review Questions and Exercises
  • References
  • Index
  • End User License Agreement.

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