Finite Mixture Models for an underlying Beta distribution with an application to COVID-19 data

Scientific Conference (2023, July 04)

A new R package for Finite Mixture Models with an application to clustering countries with respect to COVID data

Scientific Conference (2023, June 02)

Modèles de mélanges finis pour une distribution de loi BETA sous-jacente avec une application à des données sur la COVID-19

Scientific Conference (2022, September 14)

A new R package for Finite Mixture Models with an application to pension systems

Scientific Conference (2022, April 20)

trajeR, une nouvelle librairie R pour les modèles de mélange pour données longitundinales

Scientific Conference (2022, April 04)

Multiple Trajectory Analysis in Finite Mixture Modeling

Scientific Conference (2021, June 02)

Luxembourg Fund Data Repository

in Data (2020), 5(3), 1-15

In this paper, we introduce the Luxembourg Fund Data Repository, a novel database of investment funds available for academic research that was created at the Department of Finance of the University of ... [more ▼]

In this paper, we introduce the Luxembourg Fund Data Repository, a novel database of investment funds available for academic research that was created at the Department of Finance of the University of Luxembourg. The database contains the population of Undertakings for Collective Investment in Transferable Securities funds domiciled in Luxembourg from the starting month of their existence (March 1988) to October 2016. The fund characteristics are organized in a comprehensive database architecture encompassing static and dynamic data over the entire life of the funds. The characteristics include fund identifiers, official name, status information, management company and other service providers, daily and monthly performance time-series, portfolio holdings, classification of investment objective, fees, dividends, and cash flows. The database was constructed after collecting and assembling complementary historical information from three data providers. Importantly, funds no longer in existence due to liquidation or mergers are included in the database, preventing survivorship bias. The database has been constructed to serve as a research dataset of high accuracy due to the maximization of population coverage, the maximization of historical coverage, and validation by using information acquired from the supervisory authority of the financial sector of Luxembourg. License currently available to researchers of the Department of Finance of the University of Luxembourg. Future plans for extending accessibility to the global academic community. [less ▲]

Identifiability of Finite Mixture Models

Scientific Conference (2020, June 04)

A performance evaluation of weight-constrained conditioned portfolio optimization

Scientific Conference (2019, December 20)

Financial markets dependence modeling using vine copulae - Vine copulae estimation of asset decomposition

Scientific Conference (2019, July 12)