PurposeIn recent times, behavioural models for asset allocation have been getting more attention due to their probabilistic modelling for scenario consideration. Many investors are thinking about the trade-offs and benefits of using behavioural models over conventional mean-variance models. In this study, the authors compare asset allocations generated by the behavioural portfolio theory (BPT) developed by Shefrin and Statman (2000) against the Markowitz (1952) mean-variance theory (MVT).Design/methodology/approachThe data used have been culled from BRICS countries' major index constituents from 2009 to 2019. The authors consider a single period economy and generate future probable outcomes based on historical data in order to determine BPT optimal portfolios.FindingsThis study shows that a fair number of portfolios satisfy the first entry constraint of the BPT model. BPT optimal portfolio exhibits high risk and higher returns as compared to typical Markowitz optimal portfolio.Originality/valueThe BRICS countries' data were used because the dynamics of the emerging markets are significantly different from the developed markets, and many investors have been considering emerging markets as their new investment avenues.
In this paper, we try to integrate edge computing with the cloud computing paradigm. There are several issues and challenges in cloud computing paradigm which can be resolved by edge computing. So, in this paper we have discussed about those issues and given an idea that how edge computing is able to resolve that issues.In this paper, first we have discussed about edge computing with its definition and data flow diagram followed by its applications in various fields like smart city, smart home, cloud offloading and image and video analysis, then at last we have discussed about the issues and challenges of cloud computing followed by the idea of how edge computing can solve that issues.
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