Hidden semi-Markov models for rainfall-related insurance claims

Autor: Shi, Yue, Punzo, Antonio, Otneim, Håkon, Maruotti, Antonello

Publikováno v: In Insurance Mathematics and Economics January 2025 120:91-106

Portfolio Allocation under Asymmetric Dependence in Asset Returns using Local Gaussian Correlations

Autor: Sleire, Anders D., Støve, Bård, Otneim, Håkon, Berentsen, Geir Drage, Tjøstheim, Dag, Haugen, Sverre Hauso

It is well known that there are asymmetric dependence structures between financial returns. In this paper we use a new nonparametric measure of local dependence, the local Gaussian correlation, to improve portfolio allocation. We extend the classical

Externí odkaz: http://arxiv.org/abs/2106.12425

Statistical dependence: Beyond Pearson's $\rho$

Autor: Tjøstheim, Dag, Otneim, Håkon, Støve, Bård

Pearson's $\rho$ is the most used measure of statistical dependence. It gives a complete characterization of dependence in the Gaussian case, and it also works well in some non-Gaussian situations. It is well known, however, that it has a number of s

Externí odkaz: http://arxiv.org/abs/1809.10455

Non-parametric estimation of conditional densities: A new method

Autor: Otneim, Håkon, Tjøstheim, Dag

Publikováno v: Otneim, H{\aa}kon, and Dag Tj{\o}stheim. "Conditional density estimation using the local Gaussian correlation." Statistics and Computing 28.2 (2018): 303-321

Let $\textbf{X} = (X_1,\ldots, X_p)$ be a stochastic vector having joint density function $f_{\textbf{X}}(x)$ with partitions $\textbf{X}_1 = (X_1,\ldots, X_k)$ and $\textbf{X}_2 = (X_{k+1},\ldots, X_p)$. A new method for estimating the conditional d

Externí odkaz: http://arxiv.org/abs/1610.05035

Pairwise local Fisher and naive Bayes: Improving two standard discriminants

Autor: Otneim, Håkon, Jullum, Martin, Tjøstheim, Dag

Publikováno v: In Journal of Econometrics May 2020 216(1):284-304