# An Empirical Analysis for the Prediction of a Financial Crisis in Turkey through the Use of Forecast Error Measures

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## Abstract

**:**

## 1. Introduction

## 2. Forecast Error Measures

^{2}), adopted the number of observations (n). These scale-dependent measures include Mean Square Error (MSE), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Median Absolute Error (MEDAE). Some methods are better when, for example, Mean Absolute Percentage Errors (MAPEs) are used, while others are better when rankings are utilized. Forecast accuracy measures were suggested in the past by many researchers and several researchers made advices about what should be used when comparing the accuracy of forecast methods applied to multivariate time series data. Our focus here is on measures of forecast accuracy which indicates that percentage errors are not scale-independent.

_{t}is the actual value and F

_{t}is the forecast value [33,42,43]. The mean absolute percentage error (MAPE), also known as mean absolute percentage deviation (MAPD), is a measure of accuracy of a method for constructing fitted time series values in statistics, specifically in trend estimation. It usually expresses accuracy as a percentage, and is defined by the following formula;

## 3. Research Methodology

**Figure 1.**The depiction of the proposed methodology for the first ANN constituted with seven inputs and one output.

- Identifying related factors among macro-economic and financial variables through the variables adopted in financial literature.
- Constituting the financial crisis variable through the ANN.
- Modeling and estimating the financial crisis through 7 and 6 variables by using multilayered neural network.
- Evaluating the asymmetric information of the obtained forecasting results through symmetry measurements such as MAPE, sMAPE, and SE.

## 4. Design of Neural Network Ensemble and the Empirical Findings

**Figure 2.**The depiction of the second ANN model constituted with six input layers and three output layers.

**Figure 3.**The Comparison between the actual values (USD) and the predicted values (P USD) obtained by the second ANN model.

**Figure 4.**The comparison between the actual values (BIST) and the predicted values (PBIST) obtained by the second ANN model.

**Figure 5.**The comparison between the actual values (GP) and the predicted values (P GP) obtained by the second ANN model.

Variables | MAPE | sMAPE | SE |
---|---|---|---|

P-USD | 0,233795 | 0,259054 | 0,490194 |

P-BIST | 0,2979441 | 0,409444817 | 0,520474501 |

P-GP | 0,28199499 | 0,35654177 | 0,51499577 |

**Table 2.**Some symmetry measures prior to the financial crisis with the result of the second ANN output variables.

Variables | MAPE | sMAPE | SE |
---|---|---|---|

P-USD | 0,693821 | 0,780014 | 0,365896 |

P-BIST | 0,699714818 | 1,145152353 | 0,360465821 |

P-GP | 0,75348091 | 0,99799538 | 0,30768931 |

**Table 3.**Some symmetry measures after the financial crisis with the results of the second ANN output variables.

Variables | MAPE | sMAPE | SE |
---|---|---|---|

P-USD | 0,078712 | 0,077303 | 0,288659 |

P-BIST | 0,186697824 | 0,20131717 | 0,452037062 |

P-GP | 0,1121769 | 0,12041367 | 0,35404741 |

**Table 4.**Some symmetry measures during the financial crisis with the results of the second ANN output variables.

Variables | MAPE | sMAPE | SE |
---|---|---|---|

P-USD | 0,299768 | 0,362415 | 0,521021 |

P-BIST | 0,261079863 | 0,242397891 | 0,505825762 |

P-GP | 0,46626279 | 0,62913661 | 0,51325499 |

## 5. Discussion and Conclusion

## Acknowledgments

## Author Contributions

## Conflicts of Interest

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**MDPI and ACS Style**

Cavdar, S.C.; Aydin, A.D.
An Empirical Analysis for the Prediction of a Financial Crisis in Turkey through the Use of Forecast Error Measures. *J. Risk Financial Manag.* **2015**, *8*, 337-354.
https://doi.org/10.3390/jrfm8030337

**AMA Style**

Cavdar SC, Aydin AD.
An Empirical Analysis for the Prediction of a Financial Crisis in Turkey through the Use of Forecast Error Measures. *Journal of Risk and Financial Management*. 2015; 8(3):337-354.
https://doi.org/10.3390/jrfm8030337

**Chicago/Turabian Style**

Cavdar, Seyma Caliskan, and Alev Dilek Aydin.
2015. "An Empirical Analysis for the Prediction of a Financial Crisis in Turkey through the Use of Forecast Error Measures" *Journal of Risk and Financial Management* 8, no. 3: 337-354.
https://doi.org/10.3390/jrfm8030337