Demo Data from VLDB 2026 / reviewers in the wild / expert
A. Fauth
dblp:145/0831
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational finance and economics · 100% | |
| Theoretical computer science
1 paper |
Information theory · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational finance and economics
financial modeling |
0.2 | 1 | 2014 | Multifractal Random Walks With Fractional Brownian Motion via Malliavin Calculus · IEEE Trans. Inf. Theory 2014 |
Information theory › probability theory › stochastic processes › self-similar processes
fractional brownian motion |
0.1 | 1 | 2014 | Multifractal Random Walks With Fractional Brownian Motion via Malliavin Calculus · IEEE Trans. Inf. Theory 2014 |
Information theory › probability theory
stochastic processes |
0.1 | 1 | 2014 | Multifractal Random Walks With Fractional Brownian Motion via Malliavin Calculus · IEEE Trans. Inf. Theory 2014 |
Methods — techniques the papers use, named apart from their topics
stochastic integration · 0.4malliavin calculus · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Multifractal Random Walks With Fractional Brownian Motion via Malliavin CalculusabstractWe introduce a Multifractal Random Walk (MRW) defined as a stochastic integral of an infinitely divisible noise with respect to a dependent fractional Brownian motion. Using the techniques of the Malliavin calculus, we study the existence of this object and its properties. We then propose a continuous time model for financial modeling that captures the main properties observed in the empirical data, including the leverage effect. We illustrate our result by numerical simulations. A. Fauth, C. A. Tudor |
IEEE Trans. Inf. Theory | 1 |