Modern Computational Finance - Scripting for Derivatives and Xva

An incisive and essential guide to building a complete system for derivative scripting
 
In Volume 2 of Modern Computational Finance Scripting for Derivatives and xVA, quantitative finance experts and practitioners Drs. Antoine Savine and Jesper Andreasen deliver an indispensable and insightful roadmap to the interrogation, aggregation, and manipulation of cash-flows in a variety of ways. The book demonstrates how to facilitate portfolio-wide risk assessment and regulatory calculations (like xVA).
 
Complete with a professional scripting library written in modern C++, this stand-alone volume walks readers through the construction of a comprehensive risk and valuation tool. This essential book also offers:
* Effective strategies for improving scripting libraries, from basic examples--like support for dates and vectors--to advanced improvements, including American Monte Carlo techniques
* Exploration of the concepts of fuzzy logic and risk sensitivities, including support for smoothing and condition domains
* Discussion of the application of scripting to xVA, complete with a full treatment of branching
 
Perfect for quantitative analysts, risk professionals, system developers, derivatives traders, and financial analysts, Modern Computational Finance Scripting for Derivatives and xVA: Volume 2 is also a must-read resource for students and teachers in master's and PhD finance programs.

List of contents

My Life in Script by Jesper Andreasen xi
 
Part I A Scripting Library in C++
 
Introduction 3
 
Chapter 1 Opening Remarks 7
 
Introduction 7
 
1.1 Scripting is not only for exotics 12
 
1.2 Scripting is for cash-flows not payoffs 13
 
1.3 Simulation models 15
 
1.4 Pre-processing 17
 
1.5 Visitors 19
 
1.6 Modern implementation in C++ 21
 
1.7 Script templates 22
 
Chapter 2 Expression Trees 25
 
2.1 In theory 25
 
2.2 In code 35
 
Chapter 3 Visitors 41
 
3.1 The visitor pattern 41
 
3.2 The debugger visitor 47
 
3.3 The variable indexer 50
 
3.4 Pre-processors 54
 
3.5 Const visitors 55
 
3.6 The evaluator 57
 
3.7 Communicating with models 65
 
Chapter 4 Putting Scripting Together with a Model 71
 
4.1 A simplistic Black-Scholes Monte-Carlo simulator 71
 
4.1.1 Random number generators 71
 
4.1.2 Simulation models 73
 
4.1.3 Simulation engines 76
 
4.2 Connecting the model to the scripting framework 76
 
Chapter 5 Core Extensions and the "Pays" Keyword 81
 
5.1 In theory 81
 
5.2 In code 83
 
Part II Basic Improvements
 
Introduction 93
 
Chapter 6 Past Evaluator 95
 
Chapter 7 Macros 97
 
Chapter 8 Schedules of Cash-Flows 99
 
Chapter 9 Support for Dates 105
 
Chapter 10 Predefined Schedules and Functions 109
 
Chapter 11 Support for Vectors 113
 
11.1 Basic functionality 113
 
11.2 Advanced functionality 115
 
11.2.1 New node types 116
 
11.2.2 Support in the parser 116
 
11.2.3 Processing 117
 
11.2.4 Evaluation 117
 
Part III Advanced Improvements Introduction 121
 
Chapter 12 Linear Products 123
 
12.1 Interest rates and swaps 123
 
12.2 Equities, foreign exchange, and commodities 125
 
12.3 Linear model implementation 126
 
Chapter 13 Fixed Income Instruments 127
 
13.1 Delayed payments 127
 
13.2 Discount factors 128
 
13.3 The simulated data processor 129
 
13.4 Indexing 129
 
13.5 Upgrading "pays" to support delayed payments 131
 
13.6 Annuities 132
 
13.7 Forward discount factors 132
 
13.8 Back to equities 132
 
13.9 Libor and rate fixings 133
 
13.10 Scripts for swaps and options 134
 
Chapter 14 Multiple Underlying Assets 137
 
14.1 Multiple assets 137
 
14.2 Multiple currencies 139
 
Chapter 15 American Monte-Carlo 143
 
15.1 Least Squares Method 143
 
15.2 One proxy 147
 
15.3 Additional regression variables 149
 
15.4 Feedback and exercise 149
 
15.5 Multiple exercise and recursion 152
 
Part IV Fuzzy Logic and Risk Sensitivities Introduction 157
 
Chapter 16 Risk Sensitivities with Monte-Carlo 161
 
16.1 Risk instabilities 161
 
16.2 Two approaches toward a solution 165
 
16.3 Smoothing for digitals and barriers 166
 
16.4 Smoothing for scripted transactions 168
 
Chapter 17 Support for Smoothing 169
 
Chapter 18 An Automated Smoothing Algorithm 175
 
18.1 Basic algorithm 176
 
18.2 Nested and combined conditions 179
 
18.3 Affected variables 179
 
18.4 Further optimization 180
 
Chapter 19 Fuzzy Logic 183
 
Chapter 20 Condition Domains 189
 
20.1 Fuzzy evaluation of discrete conditions 189
 
20.1.1 Condition domains 189
 
20.1.2 Constant conditions 190
 
20.

About the author

ANTOINE SAVINE is a mathematician and derivatives practitioner with 25 years of leadership experience with global investment banks. He wrote the book on automatic adjoint differentiation (AAD) and co-developed Differential Machine Learning. He was also influential in volatility modeling and many areas of numerical and computational finance. Antoine works with Superfly Analytics at Danske Bank, winner of the 2019 Excellence in Risk Management and Modelling RiskMinds award. He holds a PhD in Mathematical Finance from Copenhagen University, where he teaches quantitative and computational finance.
Jesper Andreasen heads the Quantitative Research department at Saxo Bank. Over a 25 year long career he has held senior roles in quant departments of Bank of America, Nordea and General Re Financial Products, and he founded and headed the Superfly Analytics department at Danske Bank. Jesper co-received Risk magazine's 2001 and 2012 Quant of the year awards and their In-House Risk System of the year award in 2015. He is an honorary professor of Mathematical Finance at Copenhagen University and completed his PhD in the same subject at Aarhus University in 1997.

Summary

An incisive and essential guide to building a complete system for derivative scripting

In Volume 2 of Modern Computational Finance Scripting for Derivatives and xVA, quantitative finance experts and practitioners Drs. Antoine Savine and Jesper Andreasen deliver an indispensable and insightful roadmap to the interrogation, aggregation, and manipulation of cash-flows in a variety of ways. The book demonstrates how to facilitate portfolio-wide risk assessment and regulatory calculations (like xVA).

Complete with a professional scripting library written in modern C++, this stand-alone volume walks readers through the construction of a comprehensive risk and valuation tool. This essential book also offers:
* Effective strategies for improving scripting libraries, from basic examples--like support for dates and vectors--to advanced improvements, including American Monte Carlo techniques
* Exploration of the concepts of fuzzy logic and risk sensitivities, including support for smoothing and condition domains
* Discussion of the application of scripting to xVA, complete with a full treatment of branching

Perfect for quantitative analysts, risk professionals, system developers, derivatives traders, and financial analysts, Modern Computational Finance Scripting for Derivatives and xVA: Volume 2 is also a must-read resource for students and teachers in master's and PhD finance programs.

Report

"The Global Financial Crisis resulted in profound changes in quants' Modus Operandi. This timely three-volume set describes some of the tools necessary to deal with these changes. Individual volumes cover in detail several important topics of interest to anyone who wants to stay au courant with modern developments in financial engineering. While the books are predominantly practically oriented, they strike a fine balance between theoretical and applied considerations. The authors are prominent practitioners and indisputable thought-leaders in the field. I recommend this set enthusiastically to anyone who wishes to understand the current and emerging trends in financial engineering."
 
- Prof. Alexander Lipton, Founder and CEO, Stronghold Labs; Fellow, Connection Science and Engineering, Massachusetts Institute of Technology

Product details

• Authors: Jesper Andreasen, a Savine, Antoin Savine, Antoine Savine, Antoine Andreasen Savine
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Hardback
• Released: 28.02.2019
• EAN: 9781119540786
• ISBN: 978-1-119-54078-6
• No. of pages: 288
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Miscellaneous; Social sciences, law, business > Business > Business administration; Mathematik, Angewandte Mathematik, Mathematics, Applied mathematics, Computational Finance