Investment Basics XLVI. On estimating the beta coefficient

Bradfield, D. J.

doi:10.1080/10293523.2003.11082448

Cited by 14 publications

(20 citation statements)

References 17 publications

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“…The average Beta estimate of the market should be 1 because market-related systematic risk of the market index is one: market returns move in line with market returns exactly (trivially). Bradfield (2003) var(M ) , the systematic risk is underestimated for thinly traded shares because the numerator is reduced. On the contrary, because the mean Beta for all shares on an index is 1, the Beta for frequently traded shares is thus upwardly biased.…”

Section: Literature Reviewmentioning

confidence: 99%

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Beta estimates of shares on the JSE Top 40 in the context of reference-day risk

2016

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A topic of interest in the finance world is measuring systematic risk.Accurately measuring the systematic risk component -or Beta -of an asset or portfolio is important in many financial applications. In this work, we consider the efficiency of a range of Beta estimation methods commonly used in practice from a reference-day risk perspective. We show that, when using the industry standard data sample of five years of monthly returns, the choice of referenceday used to calculate underlying returns has a significant impact on all of the Beta estimation methods considered. Driven by this finding, we propose and test an alternative non-parametric bootstrap approach for calculating Beta estimates which is unaffected by reference-day risk. Our primary goal is to determine a point-estimate of Beta, independent of reference-day.

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Section: Literature Reviewmentioning

confidence: 99%

“…Additionally, Bradfield (2003) discusses the regression bias property of Beta estimates, first documented by Blume (1971). The regression bias states that a Beta that is significantly higher than average (of all listed shares) is overestimated, and conversely, an estimate that is significantly lower than average is underestimated.…”

Section: Literature Reviewmentioning

confidence: 99%

Beta estimates of shares on the JSE Top 40 in the context of reference-day risk

2016

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“…The coefficient of determination (R 2 ), being a measure of the percentage of total risk accounted for by the non-diversifiable, systematic risk, ranged from 0.04 for Co. 1 to 0.43 for Co.8. The share of the systematic risk within the total risk is usually found to be lower than the share of the diversifiable unsystematic risk (Hotvedt and Tedder, 1978;Bradfield, 2003), as revealed in the case of the Macedonian agri-food companies. It is important to stress that in this type of analysis there is no direct relation between beta and R 2 ; hence, high beta does not necessarily produce a high coefficient of determination.…”

Section: Results and Discussion Macroeconomic Overview Of The Macedonmentioning

confidence: 99%

“…In 2005, the index MBI10 was introduced, which is a price index weighted with market capitalization and refers to companies quoted on the official market. As such, it is suitable for assessment of systematic risk (Bradfield, 2003). In 2007, MSE started to calculate a new index of publicly held companies -MBID, i.e., for companies quoted on the regular market.…”

Section: Results and Discussion Macroeconomic Overview Of The Macedonmentioning

confidence: 99%

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Sensitivity of Agri-Food Sector to the Financial Crisis: Empirical Evidence From a Balkan Country

Simonovska¹,

Gjosevski²,

Elenova³

et al. 2017

AgricultForest

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SUMMARYIn post-communist economies, agri-food sector can suffer financial instability in periods of external shocks, such as the global financial crisis of [2008][2009][2010]. By applying two different approaches, authors examine the financial response of the listed and unlisted Macedonian agri-food companies to the crisis. The results show that the crisis had no great effects over the Macedonian agrifood companies, except for the reduction of the production volume of the unlisted companies and the decreased investment activities of the listed companies. Finally, this paper suggests an understanding of the financial behaviour of the agri-food companies when faced with systematic risk factors, and sets grounds for further researches in the context of other post-communist economies.

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A nonparametric approach to measuring the sensitivity of an asset’s return to the market

Severini

2016

Ann Finance

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In the market model the return on an asset is modeled as a linear function of the return on a market index with slope parameter beta. The coefficient beta is often used as a measure of the sensitivity of the asset's return to the market and to measure the component of the variance of the return that is explained by the market. However, both of these interpretations require the additional assumption that the error term in the market model has mean 0 conditional on the return on the market index, an assumption that is often difficult to verify in practice. In this paper, a nonparametric version of the market model is proposed that does not require such an assumption. This nonparametric model replaces the beta coefficient of the market model with a "beta curve" describing the relationship between the asset's return and that of the market locally near a given value of the market return. The proposed model is applied to stock returns, as well as to returns on mutual funds. Corresponding tests of the market model are given and it is shown that the nonparametric model often provides an improvement over the standard parametric market model.

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Investment Basics XLVI. On estimating the beta coefficient

Cited by 14 publications

References 17 publications

Beta estimates of shares on the JSE Top 40 in the context of reference-day risk

Beta estimates of shares on the JSE Top 40 in the context of reference-day risk

Sensitivity of Agri-Food Sector to the Financial Crisis: Empirical Evidence From a Balkan Country

A nonparametric approach to measuring the sensitivity of an asset’s return to the market

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