Abstract
Value of a project of an organization is primarily determined by two major factors – risk and return. The most important aspect of a business analysis, therefore, lies with the analysis of the risks and their associated returns. The basic objective of an organization is to increase the productivity to grab more market share. But the problem is that market risk is inherent in all projects and, by nature, it is stochastic. It can hardly be avoided but can be mitigated at most through diversification. Through Capital Asset Pricing Model (CAPM), the systematic or un-diversifiable risks can be described and measured by beta, β. In order to mitigate the risk, investments are to be made on a combination of different projects or portfolio of projects rather than a single project. Through β-hedging, a proper hedging strategy can be developed to reduce the systematic risk. But it has also been observed that the concept of CAPM has been plagued by the stochastic nature of the economy. Therefore, in the first part of this work, the systematic risk has been evaluated through time-varying β analysis. According to the results of the hedge performance of individual projects of the portfolio, it will be possible to select/rank the projects according to their risk-return trade-off capacity and in the second part, the Technique for Order Preference using Similarity to Ideal Solution (TOPSIS), one of the most important MCDM techniques, has been merged with CAPM in order to provide a more justified selection procedure of projects considering four more attributes, other than risk, which may confirm a more realistic basis of creating the portfolio for increasing organizational effectiveness.
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Chakraborty, B., Das, S. (2019). Evaluation Criteria of Project Risk and Decision Making Through Beta Analysis and TOPSIS Towards Achieving Organizational Effectiveness. In: Mandal, J., Mukhopadhyay, S., Dutta, P., Dasgupta, K. (eds) Computational Intelligence, Communications, and Business Analytics. CICBA 2018. Communications in Computer and Information Science, vol 1031. Springer, Singapore. https://doi.org/10.1007/978-981-13-8581-0_13
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