Results 161 to 170 of about 237,695 (301)

Value-at-Risk versus Non-Value-at-Risk Traders

open access: yes
In the paper, I simulate the games with a joint presence of 95% VaR-rule and return-rule groups of agents in the game. Simulations highlighted the level of omniscience, next being the rule, which agents follow at the decision-making, and the third the ...
Steinbacher, Matjaz
core  

Conditional and Dynamic Convex Risk Measures [PDF]

open access: yes
We extend the definition of a convex risk measure to a conditional framework where additional information is available. We characterize these risk measures through the associated acceptance sets and prove a representation result in terms of conditional ...
Kai Detlefsen, Giacomo Scandolo
core  

Mechanical Activation of Piezo1 Drives Osteoarthritis Through Kdm5c‐Mediated Epigenetic Silencing

open access: yesAdvanced Science, EarlyView.
Excessive mechanical stress activates Piezo1, triggering Ca2+‐dependent cytoskeletal forces that deform the nucleus and reduce H3K4me3. Kdm5c demethylates H3K4me3 at Col2a1 and Runx3 promoters. Kdm5c knockout rescues degradation. Repurposed telmisartan directly inhibits Kdm5c, blocking this axis and showing disease‐modifying efficacy in mouse OA models
Tianyou Kan   +13 more
wiley   +1 more source

Exchange Rate, Interest Rate and Stock Market Price Volatility for Value-at-Risk Analysis [PDF]

open access: yes
The study derives a theoretically and empirically founded procedure for volatility estimation and forecasting of daily financial return series for use in value-at-risk model frameworks.
Ahlstedt, Monica
core  

HLA‐DR+ Schwann Cells Generate the Protumor Cancer‐Neuron‐Immune Niche in Head and Neck Squamous Cell Carcinoma

open access: yesAdvanced Science, EarlyView.
Hijacked and educated by HNSCC cells, HLA‐DR+ Schwann cells lost their normal neural‐related functions but acquired immunoregulatory phenotypes to promote CD4+ T cells transform into Tregs. HLA‐DR+ Schwann cells induced a macrophage subpopulation, Il1β.
Xiaoyan Meng   +7 more
wiley   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

open access: yesAdvanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

Bridging Performance and Fate: A Framework for Sustainable, Composite‐Based Flexible Electronic Systems

open access: yesAdvanced Electronic Materials, EarlyView.
Composite‐based flexible electronics integrate biodegradable polymers, conductive networks, and multilayer device architectures to balance electrical performance, mechanical durability, and controlled degradation. Interfacial engineering and encapsulation regulate transport stability and operational lifetime, while programmed disassembly enables ...
Sayam, Sangho Cho
wiley   +1 more source

A Decision Rule to Minimize Daily Capital Charges in Forecasting Value-at-Risk [PDF]

open access: yes
Under the Basel II Accord, banks and other Authorized Deposit-taking Institutions (ADIs) have to communicate their daily risk estimates to the monetary authorities at the beginning of the trading day, using a variety of Value-at-Risk (VaR) models to ...
Michael McAleer   +2 more
core  

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

open access: yesAdvanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu   +6 more
wiley   +1 more source

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