The optimal allocation of current assets using mean-variance analysis
The optimal allocation of current assets using mean-variance analysis

Summary/Abstract: Research Question: The investigation of the optimal allocation of current assets. Motivation: Current assets investment is a decision process which affects firm value. In this paper, we develop a framework that encompasses these decisions by taking into consideration the trade-off between risk and return. Idea: We build up a model implemented in two stages. In the first stage, using random coefficient modeling on panel data, we obtain the estimates of the expected returns and standard deviations for cash holdings, inventories and receivables along with the correlations between them. Having these estimates on hand we move on to the second stage to determine the optimal allocation of current assets portfolio and construct the efficient frontier of the possible combinations of the current assets’ elements. Data: For the purposes of our study we use financial data from Greek manufacturing firms, drawn from their annual income statements and balance sheets. Firms are classified into the manufacturing industry for the years 2003 to 2014. Tools: In the first stage we use random coefficient modeling on panel data while in the second stage mean-variance analysis is employed. Findings: By applying the model in the Greek manufacturing sector we find that the minimum-variance portfolio of the average firm of our data set has an expected return of 10.00% with a 6.14% standard deviation (risk) and consists of 13% cash and cash equivalents, 29% inventories and 58% receivables. Contribution: Our model would be useful to assess and monitor firms’ current assets investments and may be used in the formulation of sound current assets policies and procedures.

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