The Intra Day Volatility Using extreme-value estimators and financial Models - PowerPoint PPT Presentation

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The Intra Day Volatility Using extreme-value estimators and financial Models

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  1. Dr Kriti Arekar Dr Rinku Jain Keshav Trehan The Intra Day Volatility Using extreme-value estimators and financial Models

  2. Introduction Volatility is the key word in stock markets. What is volatility? It is a measure of how far the current price of an assets deviates from its average past prices. Greater this deviation, greater is the volatility. At a more primary level, instability can indicate strength or certainty behind a price move. So is Volatility bad? An efficient market is one which responds to news rapidly

  3. Reasons of Volatility • More the Competition more the volatility • More the Leverage more the volatility • More the MNCs more the volatility • Macroeconomic indicators • Currency Crisis and Political Crisis

  4. Objectives of the Study • Risk calculation based on Indian Stock markets. • A need for a comprehensive study on the intra-day volatility of Indian Stock markets. • Frequent and wide stock market variation cause uncertainty about the value of an asset and affect the confidence of the investors

  5. Methodology • Our research helps understand higher order moments in the volatility in these markets. • The normal distribution is a symmetric distribution with well-behaved tails. This is indicated by the skewness of 0.03. The kurtosis of 2.96 is near the expected value of 3. Which is not the case in the data hence Log normal approach is used. • We have compared:- Average Annual squared lognormal returns Vs. the square root of average of squared lognormal returns of top 5% returns in the year.


  6. Methodology There are two financial models are used to make a comparative study 1) Parkinson’s Model. (Realized volatility) 2) German and Klass Model. (Implied Volatility)

  7. Comparison between BSE and S&P CNX Nifty

  8. Conclusion and recommendation-1 The emerging market returns in the past have demonstrated certain distinguish features: • average return were higher • investors looked at emerging markets for risk diversification • returns were more predictable and volatility was higher. • Negative news has severe effect than good news on both the stock markets

  9. Conclusion and recommendation-2 • High – Low volatility conveys extreme moments and dispersions during the trade time. Very high High-low volatility is likely to scare investors and lead some times to panic conditions in the market place • Open to open volatility is very important for several of the participants. High open to open volatility reveals information is symmetric and also overflow of information • Between BSE Sensex and S & P CNX, NIFTY appears to be more volatile both in terms of open to close and high low dispersions

  10. Thank You…. • Q & A