Results 51 to 60 of about 2,923 (211)

Clarifying space use concepts in ecology: Range vs. occurrence distributions

Ecology, Volume 107, Issue 3, March 2026.
Abstract Quantifying animal movements is necessary for answering a wide array of research questions in ecology and conservation biology. Consequently, ecologists have made considerable efforts to identify the best way to estimate an animal's home range, and many methods of estimating home ranges have arisen over the past half a century.
Jesse M. Alston, Christen H. Fleming, Michael J. Noonan, Marlee A. Tucker, Inês Silva, Cody Folta, Thomas S. B. Akre, Abdullahi H. Ali, Jerrold L. Belant, Dean Beyer, Niels Blaum, Katrin Böhning‐Gaese, Rogério Cunha de Paula, Jasja Dekker, Jonathan Drescher‐Lehman, Nina Farwig, Claudia Fichtel, Christina Fischer, Adam T. Ford, René Janssen, Florian Jeltsch, Peter M. Kappeler, Scott D. LaPoint, A. Catherine Markham, E. Patricia Medici, Ronaldo Gonçalves Morato, Ran Nathan, Kirk A. Olson, Bruce D. Patterson, Tyler R. Petroelje, Emiliano Esterci Ramalho, Sascha Rösner, Luiz Gustavo Rodrigues Oliveira‐Santos, Dana G. Schabo, Nuria Selva, Agnieszka Sergiel, Orr Spiegel, Wiebke Ullmann, Filip Zięba, Tomasz Zwijacz‐Kozica, George Wittemyer, William F. Fagan, Thomas Müller, Justin M. Calabrese   +43 more
wiley   +1 more source

Shock‐Triggered Asymmetric Response Stochastic Volatility

Journal of Forecasting, Volume 45, Issue 1, Page 217-240, January 2026.
ABSTRACT We propose a novel asymmetric stochastic volatility model (STAR‐SV) in which the leverage parameter adjusts to the magnitude of past shocks. This flexible specification captures both the leverage effects and their propagation more effectively than standard asymmetric volatility models.
J. Miguel Marin, Helena Veiga
wiley   +1 more source

Predicting Arbitrage Occurrences With Machine Learning and Improved Decision Threshold Level in Live‐Trading Crypto Environments

International Journal of Network Management, Volume 36, Issue 1, January/February 2026.
The results of this paper show that incorporating ML predictions with a confidence ratio significantly improves profitability, achieving a 258.5% profit and ~60% increase in total balance compared with traditional non‐ML strategies. By leveraging ML algorithms like multilayer perceptron, this approach enhances decision‐making and outperforms competing ...
Kristína Okasová, Michal Géci, Kristián Košťál   +2 more
wiley   +1 more source

Measuring financial risk : comparison of alternative procedures to estimate VaR and ES [PDF]

, 2008
We review several procedures for estimating and backtesting two of the most important measures of risk, the Value at Risk (VaR) and the Expected Shortfall (ES). The alternative estimators differ in the way the specify and estimate the conditional mean
Ruiz Ortega, Esther, Nieto, María Rosa, Ruiz, Esther   +2 more
core  

Risk Model Backtesting [PDF]

Ekonomika, 2016
Within this paper we shall research the validation methods of the risk model and we shall provide an overview of the existing literature which deals with validation and performance assessment of the VaR (Value at Risk) model. The importance of backtesting of the risk model stems from the fact that credit institutions have been allowed by regulatory ...
Terzic, Ivica, Milojevic, Marko, Terzic, Ivica, Milojevic, Marko   +3 more
openaire   +2 more sources

Escaping the Backtesting Illusion [PDF]

The Journal of Portfolio Management, 2019
Two tests can help asset managers to develop more robust investment strategies: an impact test and a survival test. Both tests complement the backtest, in which one checks how a proposed investment strategy would have performed in the past. The impact test considers the performance of the strategy when assets under management grow (crowdedness), and it
Hens, Thorsten, Schenk-Hoppé, Klaus Reiner, Woesthoff, Mathis-Hendrik   +2 more
openaire   +2 more sources

Partial Observability of Implied Volatility Matrices: Identification and Covolatilities Filtering

Mathematical Finance, Volume 36, Issue 1, Page 48-66, January 2026.
ABSTRACT Whereas data on implied volatilities are available for a large number of assets, this is less frequently the case of implied covolatilities. We introduce a new approach based on static and dynamic Wishart models to solve this problem of missing data.
Christian Gouriéroux, Yang Lu
wiley   +1 more source

Analyzing the use of generalized hyperbolic distributions to value at risk calculations

Economia Aplicada, 2005
The goal of this paper is to analyze the use of the Generalized Hyperbolic (GH) Distributions to model the US Dollar/Brazilian Real exchange rate in a way to produce more accurate VaR (Value at Risk) measurements.
José Santiago Fajardo Barbadian, Aquiles Rocha de Farias, José Renato Haas Ornelas   +2 more
doaj  

Nonlinear Dependence Structure Between BRICS Stock Markets, Gold, and Cryptocurrencies

The Manchester School, Volume 94, Issue 1, Page 75-89, January 2026.
ABSTRACT This study aims to conduct an in‐depth analysis of the complex nonlinear dependence relationships between cryptocurrencies and gold within the stocks of BRICS countries. The study employs a GARCH‐EVT‐Vine‐Copula and wavelet coherence models to evaluate the interconnectedness, tail risk and Co‐movement pattern of these assets before and after ...
Jiale Yan
wiley   +1 more source

A review of backtesting for value at risk [PDF]

, 2017
There have been many backtesting methods proposed for value at risk. Yet they have rarely been applied in practice. Here, we provide a comprehensive review of all of the recent backtesting methods for VaR.
Y. Zhang, S. Nadarajah, Zhang, Y., Nadarajah, S.; id_orcid   +3 more
core   +1 more source