CLASSICAL AND BAYESIAN APPROACH TO UNIVARIATE VOLATILITY MODELS
Abstract
There are two different approaches to the development of statistics. These are the "Classical" and the "Bayesian" approaches. We encounter the concept of "objectivity", which in the classical approach refers to ignoring prior information about the process being measured. However, in the presence of prior information about the process under consideration, there is a loss of information because the existing information is ignored. Since the parameters are not random, probability statements about the parameters cannot be made. The Bayesian approach takes into account prior information about the process and takes a more disciplined approach to uncertainty. It is therefore an approach derived from Bayes' theorem. The Bayesian approach treats parameters as probabilistic and random variables. There are no assumptions to be made as in the classical approach. Given this information, the aim is to evaluate the univariate volatility models under the Classical and Bayesian approaches. Volatility, which corresponds to uncertainty in the financial markets, also represents the risk of the financial asset. Therefore, it is expected that it will be beneficial to evaluate the effect of both approaches on the analysis of volatility models.
Keywords
Financial Markets , Volatility Models , Classical Approach , Bayesian Approach.
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