Stock Market Volatility Measure Using Non-Traditional Tool Case of Germany
DOI:
https://doi.org/10.2478/eb-2018-0010Keywords:
Extreme-day return, non-normality, standard deviation, volatility, volatility rankingAbstract
Abstract. This study examines the stock market volatility of German bench-mark stock index DAX 30 using logarithmic extreme day return. German stock markets have been analyzed extensively in literature. We look into volatility issue from the standpoint of extreme-day changes. Our analysis indicates the non-normality of German stock market and higher probability of negative trading days. We measure the occurrences of extreme-day returns and their significance in measuring annual volatility. Our time series analysis indicates that the occurrences of extreme-days show a cyclical trend over the sample time period. Our comparison of negative and positive extreme-days indicates that negative extreme-days overweigh the positive extreme days. Standard deviation, as measure of volatility used traditionally, gives altered ranks of annual volatility to a considerable extent as compared to extreme-day returns. Lastly, existence of extreme day returns can be explained by past period occurrences, which show predictability.References
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Copyright (c) 2018 Naeem Ahmed, Mudassira Sarfraz (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
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