Limited dependent variables (logit and probit models) and an application on BIST-100 logit and probit models
Regression models of a dependent variable that take on qualitative values 0 and 1 cannot be interpreted as conventional regression models. The fact that the dependent variable takes on two different values causes some problems in the model. These problems include the fact that the model’s errors do...
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| Veröffentlicht in: | Handbook of research on emerging theories, models, and applications of financial econometrics |
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| 1. Verfasser: | |
| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
2021
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Tag hinzufügen | Zusammenfassung: | Regression models of a dependent variable that take on qualitative values 0 and 1 cannot be interpreted as conventional regression models. The fact that the dependent variable takes on two different values causes some problems in the model. These problems include the fact that the model’s errors do not show normal distribution, that the model’s errors take on values less than 0 or greater than 1, and that the relationship between dependent and independent variables is not linear. Nonlinear models should be utilized to solve these problems. Nonlinear models include logit and probit models. Therefore, logit and probit models are discussed in detail in this chapter of the book. Macroeconomic factors affecting the return on the BIST-100 Index (Gold price per ounce, TL Deposit Interest, Euro-Dollar Currency Basket Return) have been investigated using logit and probit models. The findings of the study indicate that the return on the BIST-100 Index is affected by Euro-Dollar Currency Basket Return. |
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| ISBN: | 9783030541071 9783030541101 |