Book contents
- Frontmatter
- Contents
- 1 Introduction
- Part One Consistencies
- Part Two Structures
- 6 Strong Markov Family Structures
- 7 Markov Chain Structures
- 8 Conditional Markov Chain Structures
- 9 Special Semimartingale Structures
- Part Three Further Developments
- Part Four Applications of Stochastic Structures
- Appendices
- References
- Notation Index
- Subject Index
9 - Special Semimartingale Structures
from Part Two - Structures
Published online by Cambridge University Press: 18 September 2020
- Frontmatter
- Contents
- 1 Introduction
- Part One Consistencies
- Part Two Structures
- 6 Strong Markov Family Structures
- 7 Markov Chain Structures
- 8 Conditional Markov Chain Structures
- 9 Special Semimartingale Structures
- Part Three Further Developments
- Part Four Applications of Stochastic Structures
- Appendices
- References
- Notation Index
- Subject Index
Summary
In this brief chapter we discuss the concept of semimartingale structure for a collection of special semimartingales. As in Chapter 5, we confine ourselves to the bivariate case only, and we consider semimartingale characteristics with respect to the standard truncation function. We start with definition of the semimartingale structure, and then we follow with examples.
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- Structured Dependence between Stochastic Processes , pp. 117 - 120Publisher: Cambridge University PressPrint publication year: 2020