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

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 5 years of monthly returns, the choice of reference-day 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 nonparametric 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.     

A study of total beta specification through symmetric regression: the case of the Johannesburg Stock Exchange

A topic of recent interest is risk management in equity investments from emerging markets. One traditional measure for systematic risk of an asset is beta, which is constructed through ordinary least squares (OLS) regression between historical returns on an individual asset and an index representing the overall market. OLS regression assumes all the error lies within the asset returns. Tofallis (Eur J Oper Res 187(3):1358–1367, 2008) made the case for constructing a systematic risk measure through symmetric regression, where error is assumed to be present in the returns of both the asset and the index. In this paper, we construct a systematic risk measure using symmetric regression for the case of the Johannesburg Stock Exchange (JSE). This paper makes the case that the so-called ‘total beta’ parameter provides a more realistic and stable estimator for market-related risk and return. The total beta estimate, explicitly allowing for error in both variables, is less likely to underestimate the magnitude of the beta parameter.     

Identifying conservation priorities for threatened Eastern Himalayan mammals

To augment mammal conservation in the Eastern Himalayan region, we assessed the resident 255 terrestrial mammal species and identified the 50 most threatened species based on conservation status, endemism, range size, and evolutionary distinctiveness. By using the spatial analysis package letsR and the complementarity core‐area method in the conservation planning software Zonation, we assessed the current efficacy of their protection and identified priority conservation areas by comparing protected areas (PAs), land cover, and global ecoregion 2017 maps at a 100 × 100 m spatial scale. The 50 species that were most threatened, geographically restricted, and evolutionarily distinct faced a greater extinction risk than globally nonthreatened and wide‐ranging species and species with several close relatives. Small, medium‐sized, and data‐deficient species faced extinction from inadequate protection in PAs relative to wide‐ranging charismatic species. There was a mismatch between current PA distribution and priority areas for conservation of the 50 most endangered species. To protect these species, the skewed regional PA distribution would require expansion. Where possible, new PAs and transboundary reserves in the 35 priority areas we identified should be established. There are adequate remaining natural areas in which to expand current Eastern Himalayan PAs. Consolidation and expansion of PAs in the EH requires strengthening national and regional transboundary collaboration, formulating comprehensive regional land‐use plans, diversifying conservation funding, and enhancing information sharing through a consolidated regional database.