Robust estimation in Capital Asset Pricing Model

Wong, Wing Keung; Bian, Guorui

doi:10.1155/s1173912600000043

Cited by 45 publications

(29 citation statements)

References 43 publications

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“…In addition, the theory developed in this paper could be applied to many different areas in business, economics, and finance. For example, one could easily incorporate our approach to explain well-known financial anomalies (see, e.g., McNamara [23], Wong and Bian [42], Post [28], Post and Levy [30], Kuosmanen [15], and Fong et al [9]) and to model investment risk (see, e.g., Matsumura et al [22], Doumpos et al [6], Wong and Chan [43], Fong and Wong [8], and Broll et al [3]).…”

Section: Proposition 25 For Any Location-scale Familymentioning

confidence: 99%

Stochastic dominance theory for location-scale family

Wong

2006

Journal of Applied Mathematics and Decision Sciences

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Meyer (1987) extended the theory of mean-variance criterion to include the comparison among distributions that differ only by location and scale parameters and to include general utility functions with only convexity or concavity restrictions. In this paper, we make some comments on Meyer's paper and extend the results from Tobin (1958) that the indifference curve is convex upwards for risk averters, concave downwards for risk lovers, and horizontal for risk neutral investors to include the general conditions stated by Meyer (1987). We also provide an alternative proof for the theorem. Levy (1989) extended Meyer's results by introducing some inequality relationships between the stochastic-dominance and the mean-variance efficient sets. In this paper, we comment on Levy's findings and show that these relationships do not hold in certain situations. We further develop some properties among the first- and second-degree stochastic dominance efficient sets and the mean-variance efficient set.

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Section: Proposition 25 For Any Location-scale Familymentioning

confidence: 99%

Stochastic dominance theory for location-scale family

Wong

2006

Journal of Applied Mathematics and Decision Sciences

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“…Bian and Wong (1997) develop an alternative approach to estimate the regression coefficients. Wong and Bian (2000) introduce the robust Bayesian estimator developed by Bian and Dickey (1996) to the estimation of the Capital Asset Pricing Model (CAPM), in which the distribution of the error component is widely known to be flat-tailed.…”

Section: Robust Estimationmentioning

confidence: 99%

“…This estimator is an adaptive weighted average of the least squares estimator (LSE) and the prior location, and is robust to fat-tailed sample distributions. Wong and Bian (2000) introduce the robust Bayesian estimator to the estimation of the Capital Asset Pricing Model (CAPM) in which the distribution of the error component is well known to be fat-tailed.…”

Section: Other Econometrics Models and Testsmentioning

confidence: 99%

Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections

Chang

McAleer

Wong

2018

JRFM

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Abstract:The paper provides a review of the literature that connects Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology, and discusses research issues that are related to the various disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models, as well as conduct simulation to examine whether the estimators in their theories on estimation and hypothesis testing have good size and high power. Thereafter, academics and practitioners could apply theory to analyse some interesting issues in the seven disciplines and cognate areas.

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“…Wong and Bian (1997) develop an alternative approach to estimate the regression coefficients. Wong and Bian (2000) introduce the robust Bayesian estimator developed by Bian and Dickey (1996) to the estimation of the Capital Asset Pricing Model (CAPM), in which the distribution of the error component is widely known to be flat-tailed.…”

Section: Technical Analysismentioning

confidence: 99%