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It is often the case that risk assessment and prognostics are viewed as related but separate tasks. This chapter describes a risk-based approach to prognostics that seeks to provide a tighter coupling between risk assessment and fault…

Systems and Control · Electrical Eng. & Systems 2025-08-18 John W. Sheppard

Information exchange systems differ in many ways, but all share a common vulnerability to selfish behavior and free-riding. In this paper, we build incentives schemes based on social norms. Social norms prescribe a social strategy for the…

Computer Science and Game Theory · Computer Science 2012-11-13 Jie Xu , Mihaela van der Schaar

Biondi et al. (2012) develop an analytical model to examine the emergent dynamic properties of share market price formation over time, capable to capture important stylized facts. These latter properties prove to be sensitive to regulatory…

General Finance · Quantitative Finance 2021-09-27 Yuri Biondi , Simone Righi

We explore a stochastic model that enables capturing external influences in two specific ways. The model allows for the expression of uncertainty in the parametrisation of the stochastic dynamics and incorporates patterns to account for…

Pricing of Securities · Quantitative Finance 2024-04-11 Felix L. Wolf , Griselda Deelstra , Lech A. Grzelak

Many forecasts consist not of point predictions but concern the evolution of quantities. For example, a central bank might predict the interest rates during the next quarter, an epidemiologist might predict trajectories of infection rates,…

Methodology · Statistics 2021-11-12 Patric Bonnier , Harald Oberhauser

This paper develops a dynamic insurance market model comprising two competing insurance companies and a continuum of insureds, and examines the interaction between strategic underreporting by the insureds and competitive pricing between the…

Mathematical Finance · Quantitative Finance 2026-01-21 Zongxia Liang , Jiayu Zhang , Zhou Zhou , Bin Zou

This Element offers a practical guide to estimating conditional marginal effects-how treatment effects vary with a moderating variable-using modern statistical methods. Commonly used approaches, such as linear interaction models, often…

Methodology · Statistics 2026-05-21 Jiehan Liu , Ziyi Liu , Yiqing Xu

Biases with respect to socially-salient attributes of individuals have been well documented in evaluation processes used in settings such as admissions and hiring. We view such an evaluation process as a transformation of a distribution of…

Computers and Society · Computer Science 2023-10-27 L. Elisa Celis , Amit Kumar , Anay Mehrotra , Nisheeth K. Vishnoi

During recent years the counterparty risk subject has received a growing attention because of the so called Basel Accord. In particular the Basel III Accord asks the banks to fulfill finer conditions concerning counterparty credit exposures…

Pricing of Securities · Quantitative Finance 2015-03-06 M. Bonollo , L. Di Persio , I. Oliva , A. Semmoloni

The non-identifiability of the competing risks model requires researchers to work with restrictions on the model to obtain informative results. We present a new identifiability solution based on an exclusion restriction. Many areas of…

Methodology · Statistics 2023-09-06 Munir Hiabu , Simon M. S. LU , Ralf A. Wilke

The measurable properties of the artifacts or objects in the computer, management, or finance disciplines are extrinsic, not inherent -- dependent on their problem definitions and solution instantiations. Only after the instantiation can…

Emerging Technologies · Computer Science 2022-05-17 Jianfeng Zhan

New, emerging domains such as the engineering of wireless Internet services are characterized by a lack of experience based on quantitative data. Systematic tracking and observation of representative pilot projects can be seen as one means…

Software Engineering · Computer Science 2014-03-12 Fabio Bella , Jürgen Münch , Alexis Ocampo

Industrial monitoring systems, especially when deployed in Industry 4.0 environments, are experiencing a shift in paradigm from traditional rule-based architectures to data-driven approaches leveraging machine learning and artificial…

Artificial Intelligence · Computer Science 2026-05-28 Giovanni De Gasperis , Sante Dino Facchini

Unambiguous identification of the rewards driving behaviours of entities operating in complex open-ended real-world environments is difficult, partly because goals and associated behaviours emerge endogenously and are dynamically updated as…

Machine Learning · Computer Science 2024-05-03 Richard M. Bailey

Access to capital is a major constraint for economic growth in the developing world. Yet those attempting to lend in this space face high defaults due to their inability to distinguish creditworthy borrowers from the rest. In this paper, we…

Computer Science and Game Theory · Computer Science 2021-08-23 Mark York , Munther Dahleh , David Parkes

Large Language Models (LLMs) demonstrate significant potential in multi-agent negotiation tasks, yet evaluation in this domain remains challenging due to a lack of robust and generalizable benchmarks. Abdelnabi et al. (2024) introduce a…

Machine Learning · Computer Science 2026-02-24 Jorge Carrasco Pollo , Ioannis Kapetangeorgis , Joshua Rosenthal , John Hua Yao

In this paper we propose and develop a relatively simple and efficient approach for estimating unknown elements of a user-rating matrix in the context of a recommender system (RS). The critical theoretical property of the method is its…

Social and Information Networks · Computer Science 2019-06-04 Jeffrey Uhlmann

Identifying systemic risk patterns in geopolitical, economic, financial, environmental, transportation, epidemiological systems and their impacts is the key to risk management. This paper proposes a new nonlinear time series model:…

Applications · Statistics 2021-09-03 Jingyu Ji , Deyuan Li , Zhengjun Zhang

Commonly, AI or machine learning (ML) models are evaluated on benchmark datasets. This practice supports innovative methodological research, but benchmark performance can be poorly correlated with performance in real-world applications -- a…

Machine Learning · Computer Science 2024-06-18 Olivier Binette , Jerome P. Reiter

Machine learning is about forecasting. When the forecasts come with an evaluation metric the forecasts become useful. What are reasonable evaluation metrics? How do existing evaluation metrics relate? In this work, we provide a general…

Machine Learning · Computer Science 2025-07-08 Rabanus Derr , Robert C. Williamson
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