Appendices
Modern Financial Modeling
Preface
Introduction
1
Why Program?
2
Why use Julia?
Foundations: Effective Financial Modeling
3
Elements of Financial Modeling
4
The Practice of Financial Modeling
Foundations: Programming and Abstractions
5
Elements of Programming
6
Functional Abstractions
7
Data and Types
8
Higher Levels of Abstraction
Foundations: Building Performant Models
9
Hardware and Its Implications
10
Writing Performant Single-Threaded Code
11
Parallelization
Interdisciplinary Concepts and Applications
12
Applying Software Engineering Practices
13
Elements of Computer Science
14
Statistical Inference and Information Theory
15
Stochastic Modeling
16
Automatic Differentiation
17
Optimization
18
Visualizations
19
Matrices and Their Uses
20
Learning from Data
Developing In Julia
21
Writing Julia Code
22
Troubleshooting Julia Code
23
Distributing and Sharing Julia Code
24
Optimizing Julia Code
Applied Financial Modeling Techniques
25
Stochastic Mortality Projections
26
Scenario Generation
27
Similarity Analysis
28
Sensitivity Analysis
29
Portfolio Optimization
30
Bayesian Mortality Modeling
31
Auto-differentiation and Asset Liability Management (AAD & ALM)
32
Other Useful Techniques
Appendices
33
The Julia Ecosystem Today
References
Appendices
32
Other Useful Techniques
33
The Julia Ecosystem Today