the intra day volatility using extreme-value estimators and financial models

10
The Intra Day Volatility Using extreme-value estimators and financial Models Dr Kriti Arekar Dr Rinku Jain Keshav Trehan

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Dr Kriti Arekar Dr Rinku Jain Keshav Trehan. The Intra Day Volatility Using extreme-value estimators and financial Models. Introduction. Volatility is the key word in stock markets. - PowerPoint PPT Presentation

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Page 1: The Intra Day Volatility  Using extreme-value estimators and financial Models

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

Dr Kriti Arekar Dr Rinku Jain Keshav Trehan

Page 2: The Intra Day Volatility  Using extreme-value estimators and financial Models

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

Page 3: The Intra Day Volatility  Using extreme-value estimators and financial Models

Reasons of Volatility

More the Competition more the volatility

More the Leverage more the volatility

More the MNCs more the volatilityMacroeconomic indicatorsCurrency Crisis and Political Crisis

Page 4: The Intra Day Volatility  Using extreme-value estimators and financial Models

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

Page 5: The Intra Day Volatility  Using extreme-value estimators and financial Models

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.

Page 6: The Intra Day Volatility  Using extreme-value estimators and financial Models

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)

22 log12log2log5.1tttt OCLHn

2)log(1 tt LHn

k

Page 7: The Intra Day Volatility  Using extreme-value estimators and financial Models

Comparison between BSE and S&P CNX Nifty

Page 8: The Intra Day Volatility  Using extreme-value estimators and financial Models

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

Page 9: The Intra Day Volatility  Using extreme-value estimators and financial Models

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

Page 10: The Intra Day Volatility  Using extreme-value estimators and financial Models

Thank You….

Q & A