Abstract
In this work, we focus on volatility estimation which plays a crucial role in risk analysis and management. In order to improve value at risk (VaR) forecasts, we discuss the concept of low price effect and introduce the low price correction which does not require any additional parameters and instead of returns it takes into account the prices of the asset. Judgement on the forecasting quality of the proposed methodology is based on both the relative number of violations and VaR volatility. For illustrative purposes, a real example from the Athens Stock Exchange is fully explored.
Highlights
In finance, one of the main goals is the estimation of volatility, since it is crucial in risk analysis and management
In order to answer all the questions raised above, we discuss the concept of low price effect and recommend a low price correction for improved value at risk (VaR) forecasts which does not require any additional parameters and takes into account the prices of the asset
It is clear that Generalized ARCH (GARCH)(1,1), which is one of the models that captures satisfactorily the behavior of the stock, has slightly improved forecasts when the correction has been applied
Summary
One of the main goals is the estimation of volatility, since it is crucial in risk analysis and management. The need that has driven researchers to introduce and explore such models is the fact that after extensive investigation on the statistical properties of financial returns, three properties have shown to be present in most, if not all, financial returns Their existence has been the source of most problems associated with the estimation of the underlying risk of assets. These are often called the three stylized facts of financial returns and are Volatility clusters, Fat tails and Nonlinear dependence (Demirgüç-Kunt and Levine (1996); Cont (2001)). For judging the forecasting quality of the proposed methodology, we rely on two measures, namely the relative number of violations, known as the violation ratio, and the VaR volatility For comparative purposes, both measures are evaluated with and without the low price correction. Bank of Greece stock (of Athens Stock Exchange) which exhibits violent changes in its price, together with volatility structural changes due to the abnormal economic environment under which it operates
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