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Operational Risk Analysis Of Industrial Small And Medium Enterprises

Author

Listed:
  • Jorge A. Restrepo
  • Jairo Angel Díaz
  • Juan Esteban Ocampo

Abstract

This paper develops a quantitative analysis of operative risk. We model the volatilities of major financial indices Chemicals Industry for the period 2000-2009. The model uses an Analytical Hierarchy Process (AHP), a multicriterio technique, to identifying the weight of major financial indices: profitability, indebtedness, liquidity, efficiency and viability. Next, we set up an operative risk measure capturing the whole Industry indices. It becomes the risk measurement benchmark to settle level business risk by a membership function which qualitatively sorts as severe, moderate or low. The model uses time series analysis to predict industry ratios. We use a linear programming model and choose the method that produces the minimum forecast error. Last, we project ratios and their volatility. We use business information issued by the Annual Manufacturing Survey 2010, and information of the 5000 Money Magazine companies.

Suggested Citation

  • Jorge A. Restrepo & Jairo Angel Díaz & Juan Esteban Ocampo, 2014. "Operational Risk Analysis Of Industrial Small And Medium Enterprises," Global Journal of Business Research, The Institute for Business and Finance Research, vol. 8(2), pages 65-80.
    • Handle: RePEc:ibf:gjbres:v:8:y:2014:i:2:p:65-80
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    References listed on IDEAS

    as
    1. Thomas, Lyn C., 2000. "A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers," International Journal of Forecasting, Elsevier, vol. 16(2), pages 149-172.
    2. Bouchaud,Jean-Philippe & Potters,Marc, 2003. "Theory of Financial Risk and Derivative Pricing," Cambridge Books, Cambridge University Press, number 9780521819169, September.
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    More about this item

    Keywords

    Operational Risk; Modeling; AHP; Time Series;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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