Investment horizon and beta coefficients

Lin, Winston T.; Chen, Yueh H.

doi:10.1016/0148-2963(90)90003-v

Cited by 8 publications

(3 citation statements)

References 19 publications

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“…in which m is the module, and m is 4.25; z 1 is the tooth number of the pinion, and z 1 is 13; z 2 is the tooth number of the rack, and z 2 is 245. Substitute equations (10) and (11) into equation 8, we can obtain the normal load P based on the Hertz contact theory…”

Section: Construct the Wear Model Of The High-lift Device Mechanismmentioning

confidence: 99%

“…An et al 10 assumed that the correlated random variables follow the multidimensional normal and lognormal distributions, and use Bayesian statistics method to estimate the wear coefficient and predict the wear volume in the revolute joint. For the sake of convenience, Lin and Chen 11 adopt the assumption of independence in their research. However, in the above approximate methods, there exist obvious disadvantages: the assumption of independence may lead to large errors in some cases; different types of multidimensional joint distribution assumptions can cause different Bayesian updating results.…”

Section: Introductionmentioning

confidence: 99%

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Reliability analysis for high-lift device based on Copula function and Bayesian updating

Feng

Zhang

Qiu

2018

Advances in Mechanical Engineering

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In order to improve the reliability analysis accuracy of the aircraft high-lift, an approach based on the Copula function theory and Bayesian updating is proposed. Considering the influence of the random variables' correlation in the process of updating, choosing the reasonable prior joint distribution and likelihood function is crucial. Under the condition of the incomplete probability information, the analytic expressions of the prior joint distribution and likelihood function of the correlated random variables are derived through the Copula function. Then, the posterior joint distribution is obtained by Bayesian updating. The reliability of the lifting device is calculated based on the posterior distribution. The case analysis shows that the reliability results based on the proposed approach are more accurate and more coincident with the factual situation than the reliability analysis results based on the independence assumption of random variables.

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Section: Construct the Wear Model Of The High-lift Device Mechanismmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reliability analysis for high-lift device based on Copula function and Bayesian updating

Feng

Zhang

Qiu

2018

Advances in Mechanical Engineering

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show abstract

“…The results of other authors in this field either confirmed the conclusion drawn from Levy's research or contradicted it. It is difficult to mention here the works of all the authors, but as an example the following works can be indicated: Eubank and Zumwalt (1979); Chen (1982); Alexander and Benson (1982); Fisher and Kamin (1985); Brennan and Copeland (1988); Lin and Chen (1990); Clarkson and Thompson (1990); Sercu et al (2008); Berger (2013). In these works, beta parameter was also under consideration in the context of issues such as: length of the estimation sample, portfolio size, company size, liquidity of trading shares of the company on the stock exchange, frequency of measurement of the rate of return, etc.…”

Section: Introductionmentioning

confidence: 99%

Beta Stability Over Bull and Bear Market on the Warsaw Stock Exchange

Dębski

Feder‐Sempach

Świderski³

2016

Folia Oeconomica Stetinensia

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Beta parameter is one of the commonly used measures of the investment risk of individual stock or portfolio. It plays a crucial role in modern portfolio theory particularly in management of financial investment portfolios. In the field of beta parameter, numerous studies have been conducted, especially beta properties stability in the context of the stock market cycle phases, measuring frequency of rate of return, and the length of a sample period. There are much fewer studies concerned beta parameter in the countries of Central and Eastern Europe which have undergone systemic transformation at the end of the previous century. From a scientific point of view, it is interesting to know how the beta parameter behaves in these countries. The main goal of this article is to examine the beta parameter stability over bull and bear market conditions on the Warsaw Stock Exchange. The paper presents an analysis of beta stability for 134 stocks of the largest companies listed at the WSE during years 2005–2013. To verify statistically the hypothesis of beta parameter stability, we used monthly returns in the Sharpe’s single-index model. In the first part of the article, we present a brief review of the literature and methodology of the study, while in the second part, the obtained results and conclusions are shown.

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The dynamic and stochastic instability of betas: Implications for forecasting stock returns

Lin

Chen

Boot

1992

Journal of Forecasting

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The purpose of this paper is to simultaneously investigate several important issues that feature the dynamic and stochastic behavior of beta coefficients for individual stocks and affect the forecasting of stock returns. The issues include randomness, nonstantionarity, and shifts in the mean and variance parameters of the beta coefficient, and are addressed within the framework of variable-mean-response (VMR) random coefficients models in which the problem of heteroscedasticity is present.Estimation is done using a four-step generalized least squares method. The hypotheses concerning randomness and nonstationarity of betas are tested. The time paths, sizes, and marginal rates of mean shifts are determined. The issue of variance shift is examined on the basis of five special tests, called T*, B, S ' , G , and W . Then the impacts of the dynamic and stochastic instability on the estimation of betas is tested by a nonparametric procedure. Finally, the VMR models' ability of forecasting stock returns is evaluated against the standard capital asset pricing model. The empirical findings shed new light on the continuing debate as to whether the beta coefficient is random and nonstationary and have important implications for modeling and forecasting the measurement of performance and the determination of stock returns.

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Investment horizon and beta coefficients

Cited by 8 publications

References 19 publications

Reliability analysis for high-lift device based on Copula function and Bayesian updating

Reliability analysis for high-lift device based on Copula function and Bayesian updating

Beta Stability Over Bull and Bear Market on the Warsaw Stock Exchange

The dynamic and stochastic instability of betas: Implications for forecasting stock returns

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