Forecasting Business Efficiency by Using Classification Techniques: A Comparative Analysis Based on a Spanish Case

Andrés, Javier De; Álvarez, Manuel Landajo; Fernández, Pedro Lorca

doi:10.2139/ssrn.413700

Cited by 4 publications

(3 citation statements)

References 39 publications

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“…The statistical models used for the prediction are multivariate discriminant analysis, logistic regression, and neural networks. Research shows that "Artificial Neural Network (ANN)", "logit and probit" models have more accuracy to predict the financial distress (Andres, et al, 2005). Due to inadequacy of the logistic regression model, many non-parametric models have been proposed to train themselves based on the data fed into the model and provided acceptable results (Andres, et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…The reduced activities led to the reduction of the profits for the firms that has the core competencies in drilling services for the oil rig. There was a constant increase in oil and gas drilling from 2005to 2006(Petroleum Resources Branch, 2011. The rise in drilling activities is evident from the predicted distress probabilities shown in the second period of Figure 7: Predicted and forecasts of probabilities of financial distress in Canadian energy sector, as there was an enormous dip from 49% to 41%.…”

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confidence: 99%

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Likelihood of financial distress in Canadian oil and gas market: An optimized hybrid forecasting approach

Mahbobi¹,

Sukhmani²

2017

JEFS

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Forecasting models are built on either multivariate parametric or nonparametric methodologies. We attempt to optimize the accuracy of the forecasts combining these approaches to make a robust hybrid forecasting model in predicting the likelihood of financial distress for companies in the Canadian oil and gas market. The proposed approach combined the forecasts out of a multivariate logit model based on the conventional Altman's Z-score with a nonparametric Artificial Neural Network (ANN) technique. The sample firms are publicly traded and listed on the Toronto Stock Exchange (TSX) and span over a period from first quarter of 1999 to the last quarter of 2014. The results of a proposed three-stage estimation process for the period of 2015-2020 indicated that besides the fact that Canadian energy sector will go through ups and downs regarding the likelihood of financial distress, this industry would face a hard time by late 2020. Results show that the forecasting accuracy out of the proposed three-stage forecasting technique is significantly superior to the outcomes of any individual forecasting techniques, i.e. ANN and logit models.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Likelihood of financial distress in Canadian oil and gas market: An optimized hybrid forecasting approach

Mahbobi¹,

Sukhmani²

2017

JEFS

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“…Previous researchers all emphasized that financial ratios have significant effect on bankruptcy risk, return, credit risk, commercial risk, market and economic conditions [27] . While attempts have been made to solve problems of using accounting-based financial ratios, none has been entirely successfully developed in quantitative and objective systems for bankruptcy prediction [2] . Some attempts included trimming the sample ratios, eliminating negative observations and use of various transformations such as logarithms and square roots to achieve more normal distributions [8] .…”

Section: Introductionmentioning

confidence: 99%

Robust Logistic Regression to Static Geometric Representation of Ratios

Bahiraie¹,

Ibrahim²,

Azhar³

et al. 2009

J. of Mathematics and Statistics

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Problem statement: Some methodological problems concerning financial ratios such as nonproportionality, non-asymetricity, non-salacity were solved in this study and we presented a complementary technique for empirical analysis of financial ratios and bankruptcy risk. This new method would be a general methodological guideline associated with financial data and bankruptcy risk. Approach: We proposed the use of a new measure of risk, the Share Risk (SR) measure. We provided evidence of the extent to which changes in values of this index are associated with changes in each axis values and how this may alter our economic interpretation of changes in the patterns and directions. Our simple methodology provided a geometric illustration of the new proposed risk measure and transformation behavior. This study also employed Robust logit method, which extends the logit model by considering outlier. Results: Results showed new SR method obtained better numerical results in compare to common ratios approach. With respect to accuracy results, Logistic and Robust Logistic Regression Analysis illustrated that this new transformation (SR) produced more accurate prediction statistically and can be used as an alternative for common ratios. Additionally, robust logit model outperforms logit model in both approaches and was substantially superior to the logit method in predictions to assess sample forecast performances and regressions. Conclusion/Recommendations: This study presented a new perspective on the study of firm financial statement and bankruptcy. In this study, a new dimension to risk measurement and data representation with the advent of the Share Risk method (SR) was proposed. With respect to forecast results, robust loigt method was substantially superior to the logit method. It was strongly suggested the use of SR methodology for ratio analysis, which provided a conceptual and complimentary methodological solution to many problems associated with the use of ratios. Respectively, robust logit regression can be employed as a tool of regression in providing regression for studies associated with financial data.

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Forecasting business profitability by using classification techniques: A comparative analysis based on a Spanish case

Andrés

Landajo

Lorca

2005

European Journal of Operational Research

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Forecasting Business Efficiency by Using Classification Techniques: A Comparative Analysis Based on a Spanish Case

Cited by 4 publications

References 39 publications

Likelihood of financial distress in Canadian oil and gas market: An optimized hybrid forecasting approach

Likelihood of financial distress in Canadian oil and gas market: An optimized hybrid forecasting approach

Robust Logistic Regression to Static Geometric Representation of Ratios

Forecasting business profitability by using classification techniques: A comparative analysis based on a Spanish case

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