Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/20423
Title: Construction of volatility index for NSE
Authors: Goyal, Piyush
Keywords: Volatility index for NSE;NIFTY;Construct Volatility Index (VIX)
Issue Date: 2005
Publisher: Indian Institute of Management Ahmedabad
Series/Report no.: SP;001128
Abstract: Abstract: 1) Introduction and context description: This IP seeks to construct Volatility Index (VIX) for Indian Stock markets which will help investors in taking bearish/ bullish position, enable traders to take positions on future volatility levels (through derivatives), achieve diversification (since volatility is negatively correlated with other asset classes like equities) and hedge portfolios exposed to volatility risk. 2) Research questions: > Relationship between VIX and market movement: This involves data analysis to gather empirical evidence for the relationship between market-bottoms and that indicated by VIX. The analysis will also establish the time lag between VIX prediction and market movement / rading strategies based on VIX ♦ Can I take a bearish perspective when VIX is high? Whai is the range? ♦ How much option premium for a particular level of VIX? Should one remain out of the options markei when VIX is in a certain range? > Application to Indian Stock markets ♦ VIX construction for NSE and BSE. ♦ Establishing relationship between VIX and NSE, BSE market movement. ♦ Trading strategies for NSE and BSE. 3) Methodology: the VIX construction is similar to that followed by CBOE. Data is sourced from noting it manually from ICICI Direct online trading website as well as purchasing it from the NSE. 4) Findings: > VIX and NIFTY are inversely related and hence trading strategies can be based on VIX. > VIX can be used by portfolio managers to hedge their portfolios against volatility. 5) Limitations of the study: In this project I try to establish that NVX has an inverse relationship with NIFTY. Owing to data constraints I have been able to only do illustrative calculations of NVX for August and September 2004. Observations for these months do indicate that there is an inverse relationship between the two; but this needs further probing with data for larger period. Preferably, data spanning across the last three years, since the options were introduced on NSE in 2001 should be used. 6) Scope for further work: My greatest regret about not being able to do for this project has been calculation of actual values of VIX and finding exact relationship with NIFTY. This is what I propose can be done further - V Calculate exact values of VIX > Run a regression to test a linear relationship between VIX and NIFTY. Here different combinations can be tried. o Linear relationship between VIX and NIFTY? o Linear relationship between change in VIX and change in NIFTY? o Linear relationship between VIX and returns on NIFTY? o Linear relationship between change in VIX and returns on NIFTY? o Linear relationship between log of VIX and log of NIFTY? 7) Key words (up to five): Volatility, VIX, NSE, CBOE Learning from the IP process: > Data gathering is time consuming I started the data gathering part even before starting the project. I used to note the data from online trading site of ICICI Direct manually. This data was not sufficient. I decided to buy the data from NSE. The buying process took about 1.5 months and hence the project spilled into the 6th term. > Relationship with guide is important - Prof. S.K. Barua were extremely supportive. He did not put undue pressure on me. Whenever I met him we could discuss stuff other than project only and this helped me in ways more than just for this project. His resourcefulness also helped me buy data from NSE easily. If it were not him, I would not have been able to buy the data and the project would not have reached as far.
URI: http://hdl.handle.net/11718/20423
Appears in Collections:Student Projects

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