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20102026
most citedAnalytical Validation Formulas for Best Estimate Calculation in Traditional Life Insurance

5 citations · 10 across the 4 of their papers we have counts for

collaborators

6 papers

math.ST2026

On the asymptotic shape of quantile surfaces

Florian Gach, Simon Hochgerner

This article is concerned with the asymptotic shape of quantile surfaces, defined as the set of quantiles at a given level generated by a controlled one-dimensional distributio…

q-fin.RM2023★ 1 cited

Mean-field Libor market model and valuation of long term guarantees

Florian Gach, Simon Hochgerner, Eva Kienbacher +1

Existence and uniqueness of solutions to the multi-dimensional mean-field Libor market model (introduced by [7]) is shown. This is used as the basis for a numerical asset-liability…

stat.ME2021★ 3 cited

Estimation of future discretionary benefits in traditional life insurance

Florian Gach, Simon Hochgerner

In the context of life insurance with profit participation, the future discretionary benefits (), which are a central item for Solvency~II reporting, are generally calculated…

q-fin.RM2018★ 5 cited

Analytical Validation Formulas for Best Estimate Calculation in Traditional Life Insurance

Simon Hochgerner, Florian Gach

Within the context of traditional life insurance, a model-independent relationship about how the market value of assets is attributed to the best estimate, the value of in-force bu…

math.ST2011

Spatially Adaptive Density Estimation by Localised Haar Projections

Florian Gach, Richard Nickl, Vladimir Spokoiny

Given a random sample from some unknown density we devise Haar wavelet estimators for with variable resolution levels constructed from locali…

math.ST2010★ 1 cited

Non-Parametric Maximum Likelihood Density Estimation and Simulation-Based Minimum Distance Estimators

Florian Gach, Benedikt M. Pötscher

Indirect inference estimators (i.e., simulation-based minimum distance estimators) in a parametric model that are based on auxiliary non-parametric maximum likelihood density estim…