Stochastic Simulation and Applications in Finance with MATLAB® Programs

Huynh, Huu Tuê; Lai, Van Son; Soumaré, Issouf

doi:10.1002/9781118467374

Cited by 36 publications

(24 citation statements)

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“…To confirm the validity of the model, we generate some scenarios with Monte Carlo simulations (see [14] and [17]). We assume that the risky asset price process follows a geometric Brownian motion (GBM).…”

Section: Multi-stage Portfolio Selection Problemmentioning

confidence: 99%

Multi-stage distributionally robust optimization with risk aversion

Huang¹,

Qu²,

Yang³

et al. 2021

Journal of Industrial &Amp; Management Optimization

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Two-stage risk-neutral stochastic optimization problem has been widely studied recently. The goals of our research are to construct a two-stage distributionally robust optimization model with risk aversion and to extend it to multi-stage case. We use a coherent risk measure, Conditional Value-at-Risk, to describe risk. Due to the computational complexity of the nonlinear objective function of the proposed model, two decomposition methods based on cutting planes algorithm are proposed to solve the two-stage and multi-stage distributional robust optimization problems, respectively. To verify the validity of the two models, we give two applications on multi-product assembly problem and portfolio selection problem, respectively. Compared with the risk-neutral stochastic optimization models, the proposed models are more robust.

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Section: Multi-stage Portfolio Selection Problemmentioning

confidence: 99%

Multi-stage distributionally robust optimization with risk aversion

Huang¹,

Qu²,

Yang³

et al. 2021

Journal of Industrial &Amp; Management Optimization

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“…In our study we demonstrate the working practice of SCN using stochastic simulation (Huynh & Soumare, 2011). Simulation can be used in a range of applications, from operations research to project management, reliability engineering to economics.…”

Section: Context and Characterizationmentioning

confidence: 99%

Towards a Social Internet of Things Enabled Framework for Supply Community Networks

Omar¹,

Mason²

2019

IBR

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Social Internet of Things (SIoT) is one of several emerging internet paradigms, signaling the inevitable fusion of Internet of Things with Social Networks. This paper demonstrates the feasibility of applying an existing SIoT framework to Supply Community Networks (SCN). a term we use to describe the changing pattern of supply chains whose morphology continues to evolve from traditional linear continuums, into ostensibly mesh-like structures. Specifically, we identify an appropriate SIoT architecture from current literature which was used as a basis for realizing the notion of SCN, where in this case the "members" are autonomous objects (Supply Community Agents, or SCA) working on behalf of member organizations (suppliers, manufacturers, retailers, etc.) and whose generic object architecture we extended by specifying interfaces to various member functions that all such agents must possess to engage in the exchange of goods/services information and remittance one would expect whether part of a chain or as here, a network (or networks). We substantiate our claims of feasibility using stochastic MATLAB simulation of a baked-goods SCN scenario. Results showed that the modified SIoT framework exhibited the flexibility required by SCAs when operating as part of a Supply Community Network so that they can effectively discharge their responsibilities in delivering the services needed by other member agents of a SCN.

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“…Software should be developed for windows environment; 2. To simplify the task of software development, it is desirable to use the MATLAB opportunities [10,11];…”

Section: Software Structurementioning

confidence: 99%

Power plants feasibility studies supported by stochastic programming software

Sauhats

Pashnin

Kucajevs

et al. 2014

2014 55th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)

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The paper is dedicated to the power plants feasibility study, which can be considered as a first step of a long way design, construction and commissioning of power plant. This task is hundred years old, but with the market tools implementation on power systems operation and planning the feasibility study conditions change substantially. The criteria for maximizing the profit of stakeholders of power plant should be reformulated. The criteria may contain the uncertain and random variables. The task assumes stochastic programming form. The needs for additional large amount of information appear. As a result, the task becomes much more complicated which necessitates the creation of new algorithms and software tools for its solution. The paper is devoted to a description and justification of the developed software product and its application to real plant feasibility study.

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Stochastic Simulation and Applications in Finance with MATLAB® Programs

Cited by 36 publications

References 0 publications

Multi-stage distributionally robust optimization with risk aversion

Multi-stage distributionally robust optimization with risk aversion

Towards a Social Internet of Things Enabled Framework for Supply Community Networks

Power plants feasibility studies supported by stochastic programming software

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