Angelos Dassios

Prof. Angelos Dassios

London School of Economics and Political Science

Research Focus & Metrics

Academic Career Length

32Years (1995-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 May 2014 in Bernoulli
Verified
Journal Article
Open access
PDF file
WBWicher Bergsma
Wicher Bergsma
Angelos DassiosAngelos Dassios
Angelos Dassios
Project Euclid - mathematics and statistics online

1 January 2003 in Finance and Stochastics
Verified
Journal Article
Closed access
PDF file
Angelos DassiosAngelos Dassios
Angelos Dassios
JJJiwook Jang
Jiwook Jang

1 January 2013 in Electronic Communications in Probability
Verified
Journal Article
Open access
PDF file
Angelos DassiosAngelos Dassios
Angelos Dassios
HZHongbiao Zhao
Hongbiao Zhao
Exact simulation of Hawkes process with exponentially decaying intensity

1 May 1995 in The Annals of Applied Probability
Verified
Journal Article
Open access
Angelos DassiosAngelos Dassios
Angelos Dassios
The study of the quantile of a Brownian motion with a drift is undertaken. An explicit formula for its density, as well as a representation of its distribution as the sum of the maximum and the minimum of two rescaled independent Brownian motions with drift, is given. The result is used in the pricing of a financial path-dependent option due to Miura.

11 November 2009 in Finance and Stochastics
Verified
Journal Article
Closed access
PDF file
Angelos DassiosAngelos Dassios
Angelos Dassios
SWShanle Wu
Shanle Wu

1 August 1996 in The Annals of Applied Probability
Verified
Journal Article
Open access
PDF file
Angelos DassiosAngelos Dassios
Angelos Dassios
The purpose of this note is to obtain a representation of the distribution of the $\alpha$-quantile of a process with stationary and independent increments as the sum of the supremum and the infimum of two rescaled independent copies of the process. This representation has already been proved for a Brownian motion. The proof is based on already known discrete time results.