Cyber Capital at Risk

Author(s):  
Claudio Scardovi
Keyword(s):  
At Risk ◽  
2016 ◽  
Vol 03 (04) ◽  
pp. 1650031 ◽  
Author(s):  
Tarek Ibrahim Eldomiaty ◽  
Mohamed Hashem Rashwan ◽  
Mohamed Bahaa El Din ◽  
Waleed Tayel

Purpose: The objective of this study is to examine the relative contribution of firm-level, industry-level and country level variables to working capital at risk. Working capital at risk is treated as the value at risk for a portfolio of firm’s current assets. As far as short-term liquidity is concerned, working capital at risk, being the maximum amount that a firm may lose at a certain confidence interval, must be the most important part that a firm’s management must focus on. Design/methodology/approach: This study empirically examines the possible associations between wide range of variables and working capital at risk. The sample firms include 143 non-financial firms listed in Egypt stock exchange. The data cover the years 2000–2014. The statistical tests include the fixed and random effects, testing for linearity versus nonlinearity. The least squares dummy variables and discriminant analysis are utilized. The working capital at risk is classified into three levels: low, medium and high. Findings: The general findings of the study show that cash conversion cycle and the leverage are the most significant determinants of working capital at risk. Both determinants have significant influence on the level of volatility of working capital throughout the three categories of working capital at risk. Originality/value: This study offers a new approach that deals with working capital as a portfolio, rather than single ratios, that firm’s management must decrease its volatility (value at risk), therefore, short-term liquidity can be improved significantly. This approach can be considered a financial engineering in terms of monitoring and managing short-term liquidity exposure.


2010 ◽  
Vol 2010 ◽  
pp. 1-26 ◽  
Author(s):  
Gordana Dmitrasinovic-Vidovic ◽  
Ali Lari-Lavassani ◽  
Xun Li ◽  
Antony Ware

Portfolio optimization with respect to different risk measures is of interest to both practitioners and academics. For there to be a well-defined optimal portfolio, it is important that the risk measure be coherent and quasiconvex with respect to the proportion invested in risky assets. In this paper we investigate one such measure—conditional capital at risk—and find the optimal strategies under this measure, in the Black-Scholes continuous time setting, with time dependent coefficients.


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