The Experts below are selected from a list of 25353 Experts worldwide ranked by ideXlab platform
Dilip B Madan - One of the best experts on this subject based on the ideXlab platform.
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Asset pricing theory for two price economies
Annals of Finance, 2015Co-Authors: Dilip B MadanAbstract:We show that nonlinearly discounted nonlinear martingales are related to no arbitrage in two price economies as linearly discounted martingales were related to no arbitrage in economies satisfying the law of one price. Furthermore, assuming Risk Acceptability requires a positive physical expectation, we demonstrate that expected rates of return on ask prices should be dominated by expected rates of return on bid prices. A preliminary investigation conducted here, supports this hypothesis. In general we observe that asset pricing theory in two price economies leads to asset pricing inequalities. A model incorporating both nonlinear discounting and nonlinear martingales is developed for the valuation of contingent claims in two price economies. Examples illustrate the interactions present between the severity of measure changes and their associated discount rates. As a consequence arbitrage free two price economies can involve unique discount curves and measure changes that are however specific to both the product being priced and the trade direction. Furthermore the developed valuation operators call into question the current practice of Debt Valuation Adjustments.
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modeling and monitoring Risk Acceptability in markets the case of the credit default swap market
Journal of Banking and Finance, 2014Co-Authors: Dilip B MadanAbstract:Minimal discounted distorted expectations across a range of stress levels are employed to model Risk Acceptability in markets. Interactions between discounting and stress levels used in measure changes are accommodated by lowering discount rates for the higher stress levels. Acceptability parameters represent a maximal and minimal discount rate, a maximal stress level and the speed of rate reduction in response to stress. An explicit model relating credit default swap (CDS) prices to default probabilities is formulated with a view to making the default Risk market acceptable. Data on CDS prices and default probabilities for the six major US banks obtained from the Risk Management Institute of the National University of Singapore is employed to estimate parameters defining Acceptability and the movements in market implied recovery rates. We observe that the financial crisis saw an increase in the maximal discount rate and its spread over the minimal rate along with an increase in the maximal stress level being demanded for Acceptability and a stable pattern for the speed of rate adjustment through the period. The maximal rate, rate spread and stress levels have come down but with periods in the interim where they have peaked as they did in the crisis. Recovery rates have oscillated and they did fall substantially but have recovered towards 40 percent near the end of the period.
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asset pricing theory for two price economies
Social Science Research Network, 2014Co-Authors: Dilip B MadanAbstract:We show that nonlinearly discounted nonlinear martingales are related to no arbitrage in two price economies as linearly discounted martingales were related to no arbitrage in economies satisfying the law of one price. Furthermore, assuming Risk Acceptability requires a positive physical expectation, we demonstrate that expected rates of return on ask prices should be dominated by expected rates of return on bid prices. A preliminary investigation conducted here, supports this hypothesis. In general we observe that asset pricing theory in two price economies leads to asset pricing inequalities. A model incorporating both nonlinear discounting and nonlinear martingales is developed for the valuation of contingent claims in two price economies. Examples illustrate the interactions present between the severity of measure changes and their associated discount rates. As a consequence arbitrage free two price economies can involve unique discount curves and measure changes that are however specific to both the product being priced and the trade direction.
Rudiger Rackwitz - One of the best experts on this subject based on the ideXlab platform.
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the effect of discounting different mortality reduction schemes and predictive cohort life tables on Risk Acceptability criteria
Reliability Engineering & System Safety, 2006Co-Authors: Rudiger RackwitzAbstract:Abstract Technical facilities should be optimal with respect to benefits and cost. Optimization of technical facilities involving Risks for human life and limb require an Acceptability criterion and suitable discount rates both for the public and the operator depending on for whom the optimization is carried out. The life quality index is presented and embedded into modem socio-economic concepts. A general Risk Acceptability criterion is derived. The societal life saving cost to be used in optimization as life saving or compensation cost and the societal willingness-to-pay based on the societal value of a statistical life or on the societal life quality index are developed. Different mortality reduction schemes are studied. Also, predictive cohort life tables are derived and applied. Discount rates γ must be long-term averages in view of the time horizon of some 20 to more than 100 years for the facilities of interest and net of inflation and taxes. While the operator may use long-term averages from the financial market for his cost–benefit analysis the assessment of interest rates for investments of the public into Risk reduction is more difficult. The classical Ramsey model decomposes the real interest rate (=output growth rate) into the rate of time preference of consumption and the rate of economical growth multiplied by the elasticity of marginal utility of consumption. It is proposed to use a relatively small interest rate of 3% implying a rate of time preference of consumption of about 1%. This appears intergenerationally acceptable from an ethical point of view. Risk–consequence curves are derived for an example.
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a rational Risk Acceptability criterion based on the life quality index
ASME 2002 21st International Conference on Offshore Mechanics and Arctic Engineering, 2002Co-Authors: Rudiger RackwitzAbstract:Optimization techniques are essential ingredients of reliability-oriented optimal designs of technical facilities. An example of a suitable objective functions in terms of generalized cost is presented. Within FORM/SORM structural reliability analysis can be reduced to an optimization task and some simple algebra. However, instead of a optimization of cost on top of a optimization for the reliability task, a one-level optimization is proposed by adding the Kuhn-Tucker conditions of the reliability problem to general cost-benefit optimization. A rational basis to account for the cost of saving lives based on the recently proposed Life Quality Index is presented. An example illustrates the methodology.Copyright © 2002 by ASME
D.n.d. Hartford - One of the best experts on this subject based on the ideXlab platform.
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Legal framework considerations in the development of Risk acceptance criteria
Structural Safety, 2009Co-Authors: D.n.d. HartfordAbstract:Abstract This paper presents the view that the form and nature of “criteria for Risk Acceptability” are primarily political constructs determined by the legal and political frameworks of the jurisdiction where the Risk is to be taken and the consequences of failure are absorbed. Accordingly, the paper presents the view of Risk acceptance criteria as a complex matter of socio-economics and politics, informed by the engineering and natural sciences and then “made to work in practice” by the professions (doctors, engineers, lawyers, etc.).
Tsunemi Watanabe - One of the best experts on this subject based on the ideXlab platform.
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The Roles of Three Types of Knowledge and Perceived Uncertainty in Explaining Risk Perception, Acceptability, and Self-Protective Response-A Case Study on Endocrine Disrupting Surfactants.
International journal of environmental research and public health, 2018Co-Authors: Tsunemi WatanabeAbstract:The ubiquitous surfactants nonylphenol (NP) and its ethoxylates (NPEOs), which are known as endocrine disrupters, have appeared in the lists of restricted chemical substances, monitoring programs, and environmental quality standards of many countries due to their adverse effects. Recent studies have reported alarming levels of NP, as the final metabolite of NPEOs, in Vietnamese urban waters, whilst response to this issue is negligible. With the aim of addressing how the public perceives and expects to avoid the Risk of endocrine disrupting surfactants (EDSs), the study tested the hypothesized roles of specific knowledge, general knowledge, and perceived uncertainty using structural equation modelling. The findings revealed that different types of knowledge played certain roles in explaining Risk perception, Risk Acceptability, and self-protective response, which are distinguished by experience amongst the public. Evidence of the mediating role that perceived uncertainty may play in the decrease of Risk perception and the increase of Risk unacceptance has been provided. The insights gained from the study may help answer why the public are in favor of taking non-diet-related self-protective measures rather than changing their dietary habits, which illustrates a comparison with the basis of health belief model. The needs for building cognitive capacity amongst the public, particularly pregnant women and young mothers, and Risk communication concerning endocrine disrupting contamination linked to reproductive health are highlighted.
Karimi Shadi - One of the best experts on this subject based on the ideXlab platform.
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Microfluidic platform for multiple parameters readouts in a point-of-care
Universitat Politècnica de Catalunya, 2020Co-Authors: Karimi ShadiAbstract:Tesi amb una secció retallada per drets de l'editorThe research is motivated by real applications, such as pasteurization plant, water networks and autonomous system, which each of them require a specific control system to provide proper management able to take into account their particular features and operating limits in presence of uncertainties related to their operation and failures from component breakdowns. According to that most of the real systems have nonlinear behaviors, it can be approximated them by polytopic linear uncertain models such as Linear Parameter Varying (LPV) and Takagi-Sugeno (TS) models. Therefore, a new economic Model Predictive Control (MPC) approach based on LPV/TS models is proposed and the stability of the proposed approach is certified by using a region constraint on the terminal state. Besides, the MPC-LPV strategy is extended based on the system with varying delays affecting states and inputs. The control approach allows the controller to accommodate the scheduling parameters and delay change. By computing the prediction of the state variables and delay along a prediction time horizon, the system model can be modified according to the evaluation of the estimated state and delay at each time instant. To increase the system reliability, anticipate the appearance of faults and reduce the operational costs, actuator health monitoring should be considered. Regarding several types of system failures, different strategies are studied for obtaining system failures. First, the damage is assessed with the rainflow-counting algorithm that allows estimating the component’s fatigue and control objective is modified by adding an extra criterion that takes into account the accumulated damage. Besides, two different health-aware economic predictive control strategies that aim to minimize the damage of components are presented. Then, economic health-aware MPC controller is developed to compute the components and system reliability in the MPC model using an LPV modeling approach and maximizes the availability of the system by estimating system reliability. Additionally, another improvement considers chance-constraint programming to compute an optimal list replenishment policy based on a desired Risk Acceptability level, managing to dynamically designate safety stocks in flow-based networks to satisfy non-stationary flow demands. Finally, an innovative health-aware control approach for autonomous racing vehicles to simultaneously control it to the driving limits and to follow the desired path based on maximization of the battery RUL. The proposed approach is formulated as an optimal on-line robust LMI based MPC driven from Lyapunov stability and controller gain synthesis solved by LPV-LQR problem in LMI formulation with integral action for tracking the trajectory.Postprint (published version
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Microfluidic platform for multiple parameters readouts in a point-of-care
Universitat Politècnica de Catalunya, 2020Co-Authors: Karimi ShadiAbstract:Tesi amb una secció retallada per drets de l'editorThe research is motivated by real applications, such as pasteurization plant, water networks and autonomous system, which each of them require a specific control system to provide proper management able to take into account their particular features and operating limits in presence of uncertainties related to their operation and failures from component breakdowns. According to that most of the real systems have nonlinear behaviors, it can be approximated them by polytopic linear uncertain models such as Linear Parameter Varying (LPV) and Takagi-Sugeno (TS) models. Therefore, a new economic Model Predictive Control (MPC) approach based on LPV/TS models is proposed and the stability of the proposed approach is certified by using a region constraint on the terminal state. Besides, the MPC-LPV strategy is extended based on the system with varying delays affecting states and inputs. The control approach allows the controller to accommodate the scheduling parameters and delay change. By computing the prediction of the state variables and delay along a prediction time horizon, the system model can be modified according to the evaluation of the estimated state and delay at each time instant. To increase the system reliability, anticipate the appearance of faults and reduce the operational costs, actuator health monitoring should be considered. Regarding several types of system failures, different strategies are studied for obtaining system failures. First, the damage is assessed with the rainflow-counting algorithm that allows estimating the component’s fatigue and control objective is modified by adding an extra criterion that takes into account the accumulated damage. Besides, two different health-aware economic predictive control strategies that aim to minimize the damage of components are presented. Then, economic health-aware MPC controller is developed to compute the components and system reliability in the MPC model using an LPV modeling approach and maximizes the availability of the system by estimating system reliability. Additionally, another improvement considers chance-constraint programming to compute an optimal list replenishment policy based on a desired Risk Acceptability level, managing to dynamically designate safety stocks in flow-based networks to satisfy non-stationary flow demands. Finally, an innovative health-aware control approach for autonomous racing vehicles to simultaneously control it to the driving limits and to follow the desired path based on maximization of the battery RUL. The proposed approach is formulated as an optimal on-line robust LMI based MPC driven from Lyapunov stability and controller gain synthesis solved by LPV-LQR problem in LMI formulation with integral action for tracking the trajectory
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Microfluidic platform for multiple parameters readouts in a point-of-care
Universitat Politècnica de Catalunya, 2020Co-Authors: Karimi ShadiAbstract:The research is motivated by real applications, such as pasteurization plant, water networks and autonomous system, which each of them require a specific control system to provide proper management able to take into account their particular features and operating limits in presence of uncertainties related to their operation and failures from component breakdowns. According to that most of the real systems have nonlinear behaviors, it can be approximated them by polytopic linear uncertain models such as Linear Parameter Varying (LPV) and Takagi-Sugeno (TS) models. Therefore, a new economic Model Predictive Control (MPC) approach based on LPV/TS models is proposed and the stability of the proposed approach is certified by using a region constraint on the terminal state. Besides, the MPC-LPV strategy is extended based on the system with varying delays affecting states and inputs. The control approach allows the controller to accommodate the scheduling parameters and delay change. By computing the prediction of the state variables and delay along a prediction time horizon, the system model can be modified according to the evaluation of the estimated state and delay at each time instant. To increase the system reliability, anticipate the appearance of faults and reduce the operational costs, actuator health monitoring should be considered. Regarding several types of system failures, different strategies are studied for obtaining system failures. First, the damage is assessed with the rainflow-counting algorithm that allows estimating the component’s fatigue and control objective is modified by adding an extra criterion that takes into account the accumulated damage. Besides, two different health-aware economic predictive control strategies that aim to minimize the damage of components are presented. Then, economic health-aware MPC controller is developed to compute the components and system reliability in the MPC model using an LPV modeling approach and maximizes the availability of the system by estimating system reliability. Additionally, another improvement considers chance-constraint programming to compute an optimal list replenishment policy based on a desired Risk Acceptability level, managing to dynamically designate safety stocks in flow-based networks to satisfy non-stationary flow demands. Finally, an innovative health-aware control approach for autonomous racing vehicles to simultaneously control it to the driving limits and to follow the desired path based on maximization of the battery RUL. The proposed approach is formulated as an optimal on-line robust LMI based MPC driven from Lyapunov stability and controller gain synthesis solved by LPV-LQR problem in LMI formulation with integral action for tracking the trajectory
