Which is the latest and best statistical method to check the Stock Price Variations/Volatility??
For Ph.D. Thesis
Time series analysis and panel data analysis using E-view software, but it all depends on your model.
The link below gives a good concise intro:
https://www.investopedia.com/ask/answers/021015/what-best-measure-given-stocks-volatility.asp
Dear Professor Petersen,
Good simple statistical methods for estimating the variation of stock prices are the weighted arithmetic mean and the coefficient of variation.
I suppose that you are looking for tools allowing conditional volatility estimation. Nowadays the most common tools are based on the use of realized (intra-daily) measures (e.g. see the HAR model of Corsi, 2009). Standard, but still actual, approaches are based on GARCH modelling and its variants. Another interesting approach to analyze volatility is represented by the component models, involving the use of low-frequency variables (e.g. macroeconomic factors), as the GARCH-MIDAS and its extensions. If interested, you can use the "rumidas" package in R to implement such models. Clearly there is also an R package implementing the HAR model.
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