• 제목/요약/키워드: Stochastic simulation

검색결과 787건 처리시간 0.026초

Performances of Simple Option Models When Volatility Changes

  • Jung, Do-Sub
    • 디지털융복합연구
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    • 제7권1호
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    • pp.73-80
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    • 2009
  • In this study, the pricing performances of alternative simple option models are examined by creating a simulated market environment in which asset prices evolve according to a stochastic volatility process. To do this, option prices fully consistent with Heston[9]'s model are generated. Assuming this prices as market prices, the trading positions utilizing the Black-Scholes[4] model, a semi-parametric Corrado-Su[7] model and an ad-hoc modified Black-Scholes model are evaluated with respect to the true option prices obtained from Heston's stochastic volatility model. The simulation results suggest that both the Corrado-Su model and the modified Black-Scholes model perform well in this simulated world substantially reducing the biases of the Black-Scholes model arising from stochastic volatility. Surprisingly, however, the improvements of the modified Black-Scholes model over the Black-Scholes model are much higher than those of the Corrado-Su model.

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Hybrid Distributed Stochastic Addressing Scheme for ZigBee/IEEE 802.15.4 Wireless Sensor Networks

  • Kim, Hyung-Seok;Yoon, Ji-Won
    • ETRI Journal
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    • 제33권5호
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    • pp.704-711
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    • 2011
  • This paper proposes hybrid distributed stochastic addressing (HDSA), which combines the advantages of distributed addressing and stochastic addressing, to solve the problems encountered when constructing a network in a ZigBee-based wireless sensor network. HDSA can assign all the addresses for ZigBee beyond the limit of addresses assigned by the existing distributed address assignment mechanism. Thus, it can make the network scalable and can also utilize the advantages of tree routing. The simulation results reveal that HDSA has better addressing performance than distributed addressing and better routing performance than other on-demand routing methods.

결정적/확률적 요소로의 음성 분해와 심리음향 모델 기반 잡음 제거 기법 (Speech Enhancement with Decomposition into Deterministic and Stochastic components and Psychoacoustic Model)

  • 조석환;유창동
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2007년도 하계종합학술대회 논문집
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    • pp.301-302
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    • 2007
  • A speech enhancement algorithm based on both a decomposition of speech into deterministic and stochastic components and a psychoacoustic model is proposed. Noisy speech is decomposed into deterministic and stochastic components, and then each component is enhanced preserving its individual characteristics. A psychoacoustic model is taken into account when enhancing the stochastic component. Simulation results show that the proposed algorithm performs better than some of the more popular algorithms.

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Stochastic interpolation of earthquake ground motions under spectral uncertainties

  • Morikawa, Hitoshi;Kameda, Hiroyuki
    • Structural Engineering and Mechanics
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    • 제5권6호
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    • pp.839-851
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    • 1997
  • Closed-form solutions are analytically derived for stochastic properties of earthquake ground motion fields, which are conditioned by an observed time series at certain observation sites and are characterized by spectra with uncertainties. The theoretical framework presented here can estimate not only the expectations of such simulated earthquake ground motions, but also the prediction errors which offer important information for the field of engineering. Before these derivations are made, the theory of conditional random fields is summarized for convenience in this study. Furthermore, a method for stochastic interpolation of power spectra is explained.

SCHEDULING REPETITIVE PROJECTS WITH STOCHASTIC RESOURCE CONSTRAINTS

  • I-Tung Yang
    • 국제학술발표논문집
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    • The 1th International Conference on Construction Engineering and Project Management
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    • pp.881-885
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    • 2005
  • Scheduling repetitive projects under limitations on the amounts of available resources (labor and equipment) has been an active subject because of its practical relevance. Traditionally, the limitation is specified as a deterministic (fixed) number, such as 1000 labor-hours. The limitation, however, is often exposed to uncertainty and variability, especially when the project is lengthy. This paper presents a stochastic optimization model to treat the situations where the limitations of resources are expressed as probability functions in lieu of deterministic numbers. The proposed model transfers each deterministic resource constraint into a corresponding stochastic one and then solves the problem by the use of a chance-constrained programming technique. The solution is validated by comparison with simulation results to show that it can satisfy the resource constraints with a probability beyond the desired confidence level.

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A Case Study on Function Point Method applying on Monte Carlo Simulation in Automotive Software Development

  • Do, Sung Ryong
    • 한국컴퓨터정보학회논문지
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    • 제25권6호
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    • pp.119-129
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    • 2020
  • 소프트웨어 개발은 다양한 프로세스 변동을 포함하기 때문에, 결정론적 이론 보다는 확률론적 이론에 더 영향을 많이 받는다. 확률론적 방식은 결정론적 방식보다 프로젝트 활동과 관련된 불확실을 고려하고, 예상되는 결과에 대해서 확률 분포로 접근하는 장점이 있다. 그러므로 소프트웨어 프로젝트를 성공하기 위해서는 확률 분포에 기반하여 범위, 규모, 비용, 공수, 일정 그리고 품질 목표를 체계적으로 관리해야 한다. 소프트웨어 규모 산정은 불확실성이 큰 개발 초기의 활동임에도 불구하고, LOC, COCOMO, FP, SLIM과 같은 결정론적 산정 방식으로 수행되고 있다. 본 연구에서는 확률적 분포 기반의 기능 점수 프로세스를 수립하고, 효과를 검증하기 위해 몬테카를로 시뮬레이션 기반의 자동차 전기전자 제어시스템 소프트웨어 개발에 적용한 사례를 제시한다. 본 연구 결과가 조직 내 기능 점수 프로세스를 수립하기 위한 가이드 및 관리자들의 정확한 의사결정 도구로 활용될 것으로 기대한다.

유전자 알고리즘과 군집 분석을 이용한 확률적 시뮬레이션 최적화 기법 (Genetic Algorithm and Clustering Technique for Optimization of Stochastic Simulation)

  • 이동훈;허성필
    • 한국군사과학기술학회지
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    • 제2권1호
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    • pp.90-100
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    • 1999
  • 유전자 알고리즘은 전통적인 등반 알고리즘을 이용하여 구하기 어려웠던 최적화 문제를 해결하기 위한 강인한(Robust) 탐색 기법이다. 특히 목적함수가 (1)여러 개의 국부 최대치를 가지는 경우, (2)수학적으로 표현이 불가능하거나 어려운 경우, (3)목적함수에 교란 항(disturbance term)이 섞여 있을 경우도 우수한 탐색 능력을 갖는 것으로 알려져 있다. 본 논문에서는 유전자 알고리즘을 이용하여 나타나는 다양한 해집합을 형성하는 개체군을 군집성 분석(cluster analysis)을 이용하여 군집화하고, 각 군집에 부여된 군집 적합도에 따라서 최적해를 구함으로써 단순 유전자 알고리즘에 의한 최적화보다 훨씬 향상된 탐색 알고리즘을 제안하였다. 반응표면의 형태가 정형화한 테스트 함수의 형태로 나타난다고 가정한 경우에 대하여 몬테 칼로 시뮬레이션을 통하여 본 알고리즘을 적용하여 평가하고 분석하였다.

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Stochastic Design Approach for the Guidance and Control System of an Automatic Landing Vehicle

  • Minami, Yoshinori;Miyazawa, Yoshikazu;Shimada, Yuzo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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    • pp.41-46
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    • 1998
  • In this paper, a stochastic approach based on a Monte Carlo simulation method for the design of a guidance and control (G & C) system of an automatic landing flight experiment (ALFLEX) vehicle is presented. The aim of this study is to design a G & C system robust against uncertainties in the vehicular dynamics. In this study, uncertain parameters and disturbances are treated as random variables in the Monte Carlo simulation. Then, some controller gains in the G & C system are tuned to satisfy conditions concerning the states at touchdown. The proposed method was applied to the ALFLEX vehicle. The simulation results shored the effectiveness of the present approach.

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DCBA-DEA: A Monte Carlo Simulation Optimization Approach for Predicting an Accurate Technical Efficiency in Stochastic Environment

  • Qiang, Deng;Peng, Wong Wai
    • Industrial Engineering and Management Systems
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    • 제13권2호
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    • pp.210-220
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    • 2014
  • This article describes a 2-in-1 methodology utilizing simulation optimization technique and Data Envelopment Analysis in measuring an accurate efficiency score. Given the high level of stochastic data in real environment, a novel methodology known as Data Collection Budget Allocation-Data Envelopment Analysis (DCBA-DEA) is developed. An example of the method application is shown in banking institutions. In addition to the novel approach presented, this article provides a new insight to the application domain of efficiency measurement as well as the way one conducts efficiency study.

앙상블 칼만필터를 연계한 추계학적 연속형 저류함수모형 (II) : - 적용 및 검증 - (Stochastic Continuous Storage Function Model with Ensemble Kalman Filtering (II) : Application and Verification)

  • 이병주;배덕효
    • 한국수자원학회논문집
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    • 제42권11호
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    • pp.963-972
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    • 2009
  • 본 연구의 목적은 앙상블 칼만필터 기법과 연속형 저류함수모형을 연계하여 개발한 추계학적 연속형 저류함수모형의 적용성을 평가하고자 하는데 있다. 대상유역은 안동댐과 임하댐을 포함하는 지보 수위관측소 상류유역을 선정하였으며 2006년과 2007년 홍수기에 대해 분석을 수행하였다. 확정론적 모형을 적용한 결과 장기간의 모의기간에 대해 유출해석이 가능한 것을 확인하였다. 앙상블 칼만필터 기법을 적용하기 위해 Monte Carlo 모의기법을 적용하여 모형입력자료와 매개변수들에 대해 앙상블 멤버를 생성하였다. 추계학적 모형과 확정론적 모형의 누적절대오차를 비교한 결과 안동댐과 임하댐의 2007년 사상에서 각각 17.5 %와 18.3 %의 정확도가 향상되고 지보수위관측소에서는 40 % 이상의 정확도가 향상되는 것으로 나타났다. 이상의 결과로부터 관측유량과의 오차가 큰 모의결과에 있어서는 추계학적 모형이 보다 향상된 결과를 도출하는 것을 확인하였다.