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The choice of admissible trading strategies in mathematical modelling of financial markets is a delicate issue, going back to Harrison and Kreps (1979). In the context of optimal portfolio selection with expected utility preferences this…

Computational Finance · Quantitative Finance 2017-07-25 Sara Biagini , Aleš Černý

In this paper, we study properties of certain risk measures associated with acceptance sets. These sets describe regulatory preconditions that have to be fulfilled by financial institutions to pass a given acceptance test. If the financial…

Optimization and Control · Mathematics 2021-10-07 Marcel Marohn , Christiane Tammer

This paper proposes a novel approach for efficiently evaluating regular path queries over provenance graphs of workflows that may include recursion. The approach assumes that an execution g of a workflow G is labeled with query-agnostic…

Databases · Computer Science 2014-08-06 Xiaocheng Huang , Zhuowei Bao , Susan B. Davidson , Tova Milo , Xiaojie Yuan

The risk of financial positions is measured by the minimum amount of capital to raise and invest in eligible portfolios of traded assets in order to meet a prescribed acceptability constraint. We investigate nondegeneracy, finiteness and…

Risk Management · Quantitative Finance 2014-03-05 Walter Farkas , Pablo Koch-Medina , Cosimo Munari

The gain-loss ratio is known to enjoy very good properties from a normative point of view. As a confirmation, we show that the best market gain-loss ratio in the presence of a random endowment is an acceptability index and we provide its…

Portfolio Management · Quantitative Finance 2015-03-13 Sara Biagini , Mustafa Pinar

Deep learning has become the standard approach for most machine learning tasks. While its impact is undeniable, interpreting the predictions of deep learning models from a human perspective remains a challenge. In contrast to model…

Machine Learning · Computer Science 2023-11-13 Kyriakos Axiotis , Sami Abu-al-haija , Lin Chen , Matthew Fahrbach , Gang Fu

Adaptable computing is an increasingly important paradigm that specializes system resources to variable application requirements, environmental conditions, or user requirements. Adapting computing resources to variable application…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-11-03 Keeley Criswell , Tosiron Adegbija

We discuss importance sampling of exit problems that involve unbounded stopping times; examples are mean first passage times, transition rates or committor probabilities in molecular dynamics. The naive application of variance minimization…

Probability · Mathematics 2024-02-14 Carsten Hartmann , Annika Jöster

We derive an algorithm to compute satisfiability bounds for arbitrary {\omega}-regular properties in an Interval-valued Markov Chain (IMC) interpreted in the adversarial sense. IMCs generalize regular Markov Chains by assigning a range of…

Systems and Control · Computer Science 2018-09-18 Maxence Dutreix , Samuel Coogan

We define Conditional quasi concave Performance Measures (CPMs), on random variables bounded from below, to accommodate for additional information. Our notion encompasses a wide variety of cases, from conditional expected utility and…

Portfolio Management · Quantitative Finance 2012-12-18 Sara Biagini , Jocelyne Bion-Nadal

Business process models abstract complex business processes by representing them as graphical models. Their layout, solely determined by the modeler, affects their understandability. To support the construction of understandable models it…

Software Engineering · Computer Science 2017-01-18 Andrea Burattin , Vered Bernstein , Manuel Neurauter , Pnina Soffer , Barbara Weber

This paper considers possible price paths of a financial security in an idealized market. Its main result is that the variation index of typical price paths is at most 2, in this sense, typical price paths are not rougher than typical paths…

General Finance · Quantitative Finance 2016-11-29 Vladimir Vovk

Desirable system performance in the face of threats and disruptions has been characterized by various management concepts. Through semi-structured interviews with editors of journals in the fields of emergency response and systems…

Physics and Society · Physics 2020-08-25 Stephanie Galaitsi , Benjamin D. Trump , Jeffrey M. Keisler , Igor Linkov

Action-constrained reinforcement learning (ACRL) is a generic framework for learning control policies with zero action constraint violation, which is required by various safety-critical and resource-constrained applications. The existing…

Machine Learning · Computer Science 2025-03-18 Wei Hung , Shao-Hua Sun , Ping-Chun Hsieh

A key impediment to reinforcement learning (RL) in real applications with limited, batch data is defining a reward function that reflects what we implicitly know about reasonable behaviour for a task and allows for robust off-policy…

Machine Learning · Computer Science 2019-05-31 Niranjani Prasad , Barbara E Engelhardt , Finale Doshi-Velez

This paper is devoted to the estimation of the common marginal density function of weakly dependent processes. The accuracy of estimation is measured using pointwise risks. We propose a datadriven procedure using kernel rules. The bandwidth…

Statistics Theory · Mathematics 2016-04-04 Karine Bertin , Nicolas Klutchnikoff

We consider the problem of approximating the probability mass of the set of timed paths under a continuous-time Markov chain (CTMC) that are accepted by a deterministic timed automaton (DTA). As opposed to several existing works on this…

Systems and Control · Computer Science 2013-02-04 Hongfei Fu

In this paper we aim to find a measure for the diversity of cash flows between agents in an economy. We argue that cash flows can be linked to probabilities of finding a currency unit in a given cash flow. We then use the information…

General Finance · Quantitative Finance 2013-01-24 Ulrich Kirchner , Simon Moolman

The long-run average payoff per transition (mean payoff) is the main tool for specifying the performance and dependability properties of discrete systems. The problem of constructing a controller (strategy) simultaneously optimizing several…

Artificial Intelligence · Computer Science 2024-12-19 David Klaška , Antonín Kučera , Vojtěch Kůr , Vít Musil , Vojtěch Řehák

Systemic risk refers to the risk that the financial system is susceptible to failures due to the characteristics of the system itself. The tremendous cost of systemic risk requires the design and implementation of tools for the efficient…

Risk Management · Quantitative Finance 2021-04-06 Zachary Feinstein , Birgit Rudloff , Stefan Weber