| Autor: |
Liapis, Angelos, Artsidakis, Stylianos, Galanos, Christos |
| Předmět: |
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| Zdroj: |
Journal of Risk & Financial Management; Mar2023, Vol. 16 Issue 3, p140, 17p |
| Abstrakt: |
This paper aims to develop a comprehensive procedure for calculating the fair value of a company by predicting its future values using historical data of key ratios and applying dynamic algorithms to improve the selection of forecasting methods. The most important business valuation methodologies are based on discounting a firm's future variables, and there are many ways to predict them through financial and quantitative methodologies. This paper provides the most important and commonly used time series forecasting methodologies that can be used for variables, such as financial ratios, and proposes three different algorithms to help and improve the selection of the best-fit method for each of the model's variables. Another, more indirect way of predicting values is using operational research methodologies, such as Monte Carlo simulation, where the output of the sensitivity analysis gives the most likely firm value, taking into account the distribution of each variable. This paper includes a complete example of using the above procedures in a real Greek company to calculate its fair value. It offers alternative approaches to the problem that exists around the process of predicting variables, with the help of technology. We hope this will be a useful tool for future use. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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