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ISSN: 2950-6298

What are risk sciences?

This article articulates a conceptual framework for risk sciences—an emerging interdisciplinary field dedicated to the study of risk and uncertainty across natural, social, economic, management, technological...

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Interpretability in deep learning for finance: A case study for the Heston model

Deep learning is a powerful tool whose applications in quantitative finance are growing every day. Yet, artificial neural networks behave as black boxes, and this introduces risks, hindering validation...

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Data-enriched Prediction of Insurance Risk

In this study, we examine the impact of big data and corresponding prediction techniques on insurance risk assessment. We demonstrate that both big data and the Least Absolute Shrinkage and Selection...

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Axiomatic characterizations of certain simple risk-sharing rules

In this paper, we present axiomatic characterizations of certain simple risk-sharing (RS) rules, such as uniform, mean-proportional and covariance-based linear RS rules. These characterizations facilitate...

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Fundamentals of non-parametric statistical inference for integrated quantiles

We present a general non-parametric statistical inference theory for integrals of quantiles without assuming any specific sampling design or dependence structure. Technical considerations are accompanied...

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