The likelihood value of residual risk estimation in the management of enterprise risk

  • Received April 24, 2018;
    Accepted June 26, 2018;
    Published July 13, 2018
  • Author(s)
    Ronny Kountur
    ORCID
  • DOI
    http://dx.doi.org/10.21511/imfi.15(3).2018.04
  • Article Info
    Volume 15 2018, Issue #3, pp. 49-55
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This work is licensed under a Creative Commons Attribution 4.0 International License

A model for estimating the likelihood value of residual risk (Y) is introduced. The model consists of three independent variables: the likelihood value of risk before risk treatment (X1), the quality of risk treatment (X2), and the appropriateness of risk treatment (X3). An experimental research design with a multiple linear regression analysis was used in the estimation. All independent variables, the likelihood value of risk before treatment, the quality of risk treatment, and the appropriateness of risk treatment, can be significantly used to estimate the likelihood value of residual risk. Since no model of estimating residual risk of likelihood had been introduced yet, the findings of this study provide significant contribution to firms or organizations that need to assess the likelihood value of residual risks.

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    • Figure 1. Normal P-P plot: residual probability
    • Figure 2. Scatterplot dependent variable: residual probability
    • Table 1. The quality of risk treatment
    • Table 2. The appropriateness of risk treatment
    • Table 3. Collinearity statistics
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Investment Management and Financial Innovations
Investment Management and Financial Innovations