Results 61 to 70 of about 521,883 (320)

Tail Value-at-Risk-Based Expectiles for Extreme Risks and Their Application in Distributionally Robust Portfolio Selections

Mathematics, 2022
Empirical evidence suggests that financial risk has a heavy-tailed profile. Motivated by recent advances in the generalized quantile risk measure, we propose the tail value-at-risk (TVaR)-based expectile, which can capture the tail risk compared with the
Haoyu Chen, Kun Fan
doaj   +1 more source

A comparison of extreme value theory approaches for determining value at risk [PDF]

, 2005
This paper compares a number of different extreme value models for determining the value at risk (VaR) of three LIFFE futures contracts. A semi-nonparametric approach is also proposed, where the tail events are modeled using the generalised Pareto ...
Brooks, Chris, Clare, A. D., Dalle Molle, J. W., Persand, Gitanjali   +3 more
core   +2 more sources

Financial Fraud Detection Using Value-at-Risk With Machine Learning in Skewed Data

IEEE Access
The significant losses that banks and other financial organizations suffered due to new bank account (NBA) fraud are alarming as the number of online banking service users increases.
Abdullahi Ubale Usman, Sunusi Bala Abdullahi, Liping Yu, Bayan I. Alghofaily, Ahmed S. Almasoud, A. Rehman   +5 more
semanticscholar   +1 more source

Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer

Molecular Oncology, EarlyView.
Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson, Lyanne Delgado‐Coka, Natalia Marchenko, Luisa F. Escobar‐Hoyos, Kenneth R. Shroyer, Alisa Yurovsky, Trey Ideker, Gábor Balázsi, Thomas MacCarthy, Scott Powers   +9 more
wiley   +1 more source

A consistent estimator to the orthant-based tail value-at-risk [PDF]

ESAIM: Probability and Statistics, 2018
In this paper, we address the estimation of multivariate value-at-risk (VaR) and tail value-at-risk (TVaR). We recall definitions for the bivariate lower and upper orthant VaR and bivariate lower and upper orthant TVaR, presented in Cossetteet al.[Eur. Actuar. J.3(2013) 321–357 orMethodol. Comput. Appl. Probab.(2014) 1–22].
Beck, Nicholas, Mailhot, Mélina
openaire   +1 more source

Engineered extracellular vesicles enriched with the miR‐214/199a cluster enhance the efficacy of chemotherapy in ovarian cancer

Molecular Oncology, EarlyView.
Loss of the miR‐214/199a cluster is associated with recurrence in ovarian cancer. Engineered small extracellular vesicles (m214‐sEVs) elevate miR‐214‐3p/miR‐199a‐5p in tumor cells, suppress β‐catenin, TLR4, and YKT6 signaling, reprogram tumor‐derived sEV cargo, reduce chemoresistance and migration, and enhance carboplatin efficacy and survival in ...
Weida Wang, Ayesha Alvero, Yi Qin, Mingjin Wang, Alexandra Fox, Yanfeng Li, Michael Millman, Amy Kemper, Gil Mor, Xian Shuang Liu, Michael Chopp, Zheng Gang Zhang, Yi Zhang   +12 more
wiley   +1 more source

A New Reciprocal Weibull Extension for Modeling Extreme Values with Risk Analysis under Insurance Data

Mathematics, 2023
Probability-based distributions might be able to explain risk exposure well. Usually, one number, or at the very least, a limited number of numbers called the key risk indicators (KRIs), are used to describe the level of risk exposure.
Haitham M. Yousof, Yusra Tashkandy, Walid Emam, M. Masoom Ali, Mohamed Ibrahim   +4 more
doaj   +1 more source

Establishment of a humanized patient‐derived xenograft mouse model of high‐grade serous ovarian cancer for preclinical evaluation of combination immunotherapy

Molecular Oncology, EarlyView.
We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric, Line Bjørge, Martine Rott Lode, Cecilie Fredvik Torkildsen, Pia Aehnlich, Rammah Elnour, Daniela Elena Costea, Lars Andreas Akslen, Liv Cecilie Vestrheim Thomsen, Emmet McCormack, Katrin Kleinmanns   +10 more
wiley   +1 more source

Deciphering transcriptional plasticity in pancreatic ductal adenocarcinoma reveals alterations in sensory neuron innervation

Molecular Oncology, EarlyView.
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova, Michele Montrone, Uday Rangaswamy, Francesco Diversi, Irene Schiavo, Denise Ferrarini, Roberta Di Florio, Irene Longo, Michele Coscia, Nicola Zamboni, Giorgia Demontis, Lisa Veghini, Vincenzo Corbo, Remo Sanges, Paul Heppenstall   +14 more
wiley   +1 more source

Improved estimators of extreme Wang distortion risk measures for very heavy-tailed distributions [PDF]

, 2017
A general way to study the extremes of a random variable is to consider the family of its Wang distortion risk measures. This class of risk measures encompasses several indicators such as the classical quantile/Value-at-Risk, the Tail-Value-at-Risk and ...
Alvarado, Beirlant, Beirlant, Belles-Sampera, Caeiro, Cherny, Csörgő, Csörgő, Davison, de Haan, Deme, Deme, Diebolt, Dowd, Drees, Drees, Drees, El Methni, El Methni, Etemadi, Gardes, Ghosh, Goegebeur, Gomes, Gomes, Gomes, Hill, Hosking, Jones, Koutsoyiannis, Necir, Necir, Peng, Pickands, Rootzén, Smith, Stigler, Stupfler, Stupfler, Vandewalle, Wang, Wang, Wang, Wang, Weissman, Yang   +45 more
core   +2 more sources