Name: Advances in Superprocesses and Nonlinear PDEs
ISBN: 9781461462392

Book information

Authors: Janos Englander verified identity
First published: 2013
Editions known: 3
Publishers: Brand: Springer
Languages: eng
ISBN-13: 9781461462392, 9781461462408, 9781489973337
Main topics: Mathematical Finance
Also covers: Numerical Methods, Time Series Analysis, Stochastic Calculus
Related site topics: Stochastic Control & Optimal Stopping

Overview

Advances in Superprocesses and Nonlinear PDEs is a book by Janos Englander, first published in 2013. In this catalogue it is classified mainly under Mathematical Finance, with secondary coverage of Numerical Methods, Time Series Analysis and Stochastic Calculus.

Audience and depth. The rule-based model places its mathematical difficulty at advanced level (7/10); readers are typically expected to know calculus, differential equations, linear algebra, numerical analysis, probability theory, statistics and stochastic processes.

Orientation. The theory-versus-practice balance could not be determined from metadata. The archive holds 6 papers whose topics and vocabulary overlap with this book; those links are inferred (see the research connections below).

How to read this page. Topics, difficulty, prerequisites and orientation are model-derived (rule-based, rule_based_v1) from bibliographic metadata such as title, subject headings and edition data. They were not produced by reading the book and are not a review. Relevance confidence is 86% and difficulty confidence is 95%; the catalogue lists no ratings or awards.

Research assessment

Rule-based and model-derived from metadata (title, subject headings, edition data). These are not reviews or ratings; see the evidence below.

Quant-finance relevance	62/100 confidence 86% Score 61.8/100. Strongest: quant_relevance 0.84, technical_depth 0.71; weakest: practical_applicability 0.00. Evidence: subjects:'mathematical finance'.
Mathematical difficulty	Advanced (7/10) confidence 95%
Prerequisites	calculus, differential equations, linear algebra, numerical analysis, probability theory, statistics, stochastic processes
Metadata quality	95%

Difficulty evidence (8 signals)

econometrics matched in ol_description: “time series”
intro_statistics matched in subjects: “statistics for”
mathematical_finance_core matched in subjects: “mathematical finance”
probability_basics matched in ol_description: “probability”
probability_basics matched in subjects: “probability”
sde_pde matched in ol_description: “partial differential equations”
sde_pde matched in subjects: “partial differential equations”
sde_pde matched in title: “pdes”

Research connections

Related papers on this site

Similarity of research area (shared vocabulary, topics and methods). Not citations: the paper does not necessarily cite this book.

Error Analysis of Option Pricing via Deep PDE Solvers: Empirical Study Topic similarity inferred similarity 0.35
Quantum-inspired nonlinear Galerkin ansatz for high-dimensional HJB equations Topic similarity inferred similarity 0.35
Deep multi-step mixed algorithm for high dimensional non-linear PDEs and associated BSDEs Topic similarity inferred similarity 0.34
Simultaneously Solving FBSDEs and their Associated Semilinear Elliptic PDEs with Small Neural Operators Topic similarity inferred similarity 0.33
Deep Runge-Kutta schemes for BSDEs Topic similarity inferred similarity 0.33
A forward differential deep learning-based algorithm for solving high-dimensional nonlinear backward stochastic differential equations Topic similarity inferred similarity 0.33

Similar books

From elementary probability to stochastic differential equations with Maple inferred similarity 0.64
Numerical Solution of Stochastic Differential Equations inferred similarity 0.61
Option Theory with Stochastic Analysis inferred similarity 0.58
Mathematical Statistics inferred similarity 0.58
Robustness In Statistical Forecasting inferred similarity 0.57

Author profiles

Janos Englander verified identity

External resources

Open Library
Search on Amazon (ISBN-13 9781489973337) (search link; may be an affiliate link)

Relationship graph

Solid lines are verified facts (authorship from persistent identifiers, editions); dashed lines are inferred by rules or similarity. Open in the full explorer.

Interactive relationship graph (requires JavaScript). The relationships are also listed as text below it once loaded.