• Title/Summary/Keyword: Variance constraints

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The Admissible Multiperiod Mean Variance Portfolio Selection Problem with Cardinality Constraints

  • Zhang, Peng;Li, Bing
    • Industrial Engineering and Management Systems
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    • v.16 no.1
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    • pp.118-128
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    • 2017
  • Uncertain factors in finical markets make the prediction of future returns and risk of asset much difficult. In this paper, a model,assuming the admissible errors on expected returns and risks of assets, assisted in the multiperiod mean variance portfolio selection problem is built. The model considers transaction costs, upper bound on borrowing risk-free asset constraints, cardinality constraints and threshold constraints. Cardinality constraints limit the number of assets to be held in an efficient portfolio. At the same time, threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Because of these limitations, the proposed model is a mix integer dynamic optimization problem with path dependence. The forward dynamic programming method is designed to obtain the optimal portfolio strategy. Finally, to evaluate the model, our result of a meaning example is compared to the terminal wealth under different constraints.

Weight Vector Analysis to Portfolio Performance with Diversification Constraints (비중 상한 제약조건에 따른 포트폴리오 성과에 대한 투자 비중 분석)

  • Park, Kyungchan;Kim, Hongseon;Kim, Seongmoon
    • Korean Management Science Review
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    • v.33 no.4
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    • pp.51-64
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    • 2016
  • The maximum weight of single stock in mutual fund is limited by regulations to enforce diversification. Under incomplete information with added constraints on portfolio weights, enhanced performance had been reported in previous researches. We analyze a weight vector to examine the effects of additional constraints on the portfolio's performance by computing the Euclidean distance from the in-sample tangency portfolio, as opposed to previous researches which analyzed ex-post return only. Empirical experiment was performed on Mean-variance and Minimum-variance model with Fama French's 30 industry portfolio and 10 industry portfolio for the last 1,000 months from August 1932 to November 2015. We find that diversification-constrained portfolios have 7% to 26% smaller Euclidean distances with the benchmark portfolio compared to those of unconstrained portfolios and 3% to 11% greater Sharpe Ratio.

An IMM Approach for Tracking a Maneuvering Target with Kinematic Constraints Based on the Square Root Information Filter

  • Kim, Kyung-Youn;Kim, Joong-Soo
    • Journal of Electrical Engineering and information Science
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    • v.1 no.2
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    • pp.39-44
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    • 1996
  • An efficient interacting multiple mode(IMM) approach for tracking a maneuvering target with kinematic constraints is described based on the square root information filter(SRIF). The SRIF is employed instead of the conventional Kalman filter since it exhibits more efficient features in handling the kinematic constraints and improved numerical characteristics. The kinematic constraints are considered in the filtering process as pseudomeasurements where the degree of uncertainty is represented by the magnitude of the pseudomeasurement noise variance. The Monte Carlo simulations for the constant speed, maneuvering target are provided to demonstrate the improved tracking performance of the proposed algorithm.

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A Signal Detection of Minimum Variance Algorithm on Linear Constraints

  • Kwan Hyeong Lee
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.3
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    • pp.8-13
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    • 2023
  • We propose a method for removing interference and noise to estimate target information. In wireless channels, information signals are subject to interference and noise, making it is difficult to accurately estimate the desired signal. To estimate the desired information signal, it is essential to remove the noise and interference from the received signal, extracting only the desired signal. If the received signal noise and interference are not removed, the estimated information signal will have a large error in distance and direction, and the exact location of the target cannot be estimated. This study aims to accurately estimate the desired target in space. The objective is to achieve more presice target estimation than existing methods and enhance target resolution.An estimation method is proposed to improve the accuracy of target estimation. The proposed target estimation method obtains optimal weights using linear constraints and the minimum variance method. Through simulation, the performance of the proposed method and the existing method is analyzed. The proposed method successfully estimated all four targets, while the existing method only estimated two targets. The results show that the proposed method has better resolutiopn and superior estimation capability than the existing method.

Optimal actuator selection for output variance constrained control

  • 김재훈
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.565-569
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    • 1993
  • In this paper, a specified number of actuators are selected from a given set of admissible actuators. The selected set of actuators is likely to use minimum control energy while required output variance constraints are guaranteed to be satisfied. The actuator selection procedure is an iterative algorithm composed of two parts; an output variance constrained control and an input variance constrained control algorithm. The idea behind this algorithm is that the solution to the first control problem provides the necessary weighting matrix in the objective function of the second optimization problem, and the sensitivity information from the second problem is utilized to delete one actuator. For variance constrained control problems, by considering a dual version of each control problem an efficient algorithm is provided, whose convergence properties turn out to be better than an existing algorithm. Numerical examples with a simple beam are given for both the input/output variance constrained control problem and the actuator selection problem.

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Minimum Variance FIR Smoother for Model-based Signals

  • Kwon, Bo-Kyu;Kwon, Wook-Hyun;Han, Soo-Hee
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2516-2520
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    • 2005
  • In this paper, finite impulse response (FIR) smoothers are proposed for discrete-time systems. The proposed FIR smoother is designed under the constraints of linearity, unbiasedness, FIR structure, and independence of the initial state information. It is also obtained by directly minimizing the performance criterion with unbiased constraints. The approach to the MVF smoother proposed in this paper is logical and systematic, while existing results have heuristic assumption, such as infinite covariance of the initial state. Additionally, the proposed MVF smoother is based on the general system model that may have the singular system matrix and has both system and measurement noises. Thorough simulation studies, it is shown that the proposed MVF smoother is more robust against modeling uncertainties numerical errors than fixed-lag Kalman smoother which is infinite impulse response (IIR) type estimator.

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Variance Analysis for State Estimation In Communication Channel with Finite Bandwidth (유한한 대역폭을 가지는 통신 채널에서의 상태 추정값에 대한 분산 해석)

  • Fang, Tae-Hyun;Choi, Jae-Weon
    • Proceedings of the KSME Conference
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    • 2000.11a
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    • pp.693-698
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    • 2000
  • Aspects of classical information theory, such as rate distortion theory, investigate how to encode and decode information from an independently identically distributed source so that the asymptotic distortion rate between the source and its quantized representation is minimized. However, in most natural dynamics, the source state is highly corrupted by disturbances, and the measurement contains the noise. In recent coder-estimator sequence is developed for state estimation problem based on observations transmitted with finite communication capacity constraints. Unlike classical estimation problems where the observation is a continuous process corrupted by additive noises, the condition is that the observations must be coded and transmitted over a digital communication channel with finite capacity. However, coder-estimator sequence does not provide such a quantitative analysis as a variance for estimation error. In this paper, under the assumption that the estimation error is Gaussian distribution, a variance for coder-estimation sequence is proposed and its fitness is evaluated through simulations with a simple example.

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Optimal Fuzzy Filter for Nonlinear Systems with Variance Constraints (분산 제약을 갖는 비선형 시스템의 최적 퍼지 필터)

  • Noh, Sun-Young;Park, Jin-Bae;Joo, Young-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.5
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    • pp.549-554
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    • 2012
  • In this paper, we consider the optimal fuzzy filter of nonlinear discrete-time with estimation error variance constraint. First, the Takagi and Sugeno(T-S) fuzzy model is employed to approximate the nonlinear system. Next, the error state is mean square bounded, and the steady state variance of the estimation error of each state is not more than the individual predefined value. It is shown that, the addressed problem can be carried out by solving linear matrix inequality(LMI) and some algebraic quadratic matrix inequalities. Finally, some examples are provided to illustrate the design procedure and expected performance through simulations.

An Analysis of the Constraints of Residential Mobility (주거이동 제약 요인 분석)

  • Yang, Se-Hwa;Kim, Myo-Jung
    • Journal of Families and Better Life
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    • v.28 no.2
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    • pp.27-37
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    • 2010
  • The purpose of the study was to analyze the constraints that are normally experienced before moving in the context of the household characteristics of households that had recently moved to newly-built apartments. The data for the analysis was collected through a self-administered questionnaire from July 1, 2008 to August 10, 2008. The sample consisted of 251 households in Ulsan living in an apartment complex who had moved within a year. The data from the sample was analyzed by descriptive statistics, factor analysis, and analysis of variance with Duncan's multiple range tests. The results are as follows. The constraints were categorized into information gathering, attractive housing characteristics, expectations of residential mobility, housing development and policies, and resources. Overall, the constraints did not have a huge impact on the performance of the residential mobility of the sample households. Resources, however, were the most influential factors among the five constraints followed by attractive housing characteristics, information gathering, etc. The constraints varied based on the demographic characteristics, such as the household size, duration of marriage, age of the household head, and the socio-economic characteristics, such as the education level of the household head, household income, and the number of mobility. As the number of family members increased, the age of the household head went up, or the level of education went down, the constraints on information gathering were affected in terms of performing residential mobility. Households with a middle aged head with a professional occupation were more constrained by the attractive characteristics of the housing. The impact of the resources related constraints was significantly different based on the number of family members, marriage duration, and the household head's age and occupation, and the number of mobility.