High-Frequency Return-Implied Volatility Relationship: Empirical Evidence from Nifty and India VIX

2020 ◽  
Vol 54 (3) ◽  
Author(s):  
Prasenjit Chakrabarti ◽  
K Kiran Kumar
Keyword(s):  
Empirical Evidence ◽  
High Frequency ◽  
Implied Volatility ◽  
India Vix

Examining Contemporaneous Relationship between Return of Nifty Index and India VIX

2015 ◽  
Vol 5 (2) ◽  
Author(s):  
Prasenjit Chakrabarti
Keyword(s):  
Implied Volatility ◽  
Stock Index ◽  
Quadratic Effect ◽  
Asymmetric Building ◽  
Volatility Index ◽  
India Vix ◽  
The Relationship

The study examines the contemporaneous relationship between Nifty returns and India VIX returns. Literature documents that the relationship between them is negative and asymmetric. Building on this, the study considers the linear and quadratic effect of stock index return (CNX Nifty) and examines the changes in implied volatility index (India VIX). The study finds both linear and quadratic CNX Nifty index returns are significant for changes in the level of India VIX. Findings suggest that India VIX provides insurance both for downside market movement and size of the downside movement.

Implied volatility smirk and future stock returns: evidence from the German market

2015 ◽  
Vol 41 (12) ◽  
pp. 1357-1379
Author(s):  
Di Mo ◽  
Neda Todorova ◽  
Rakesh Gupta
Keyword(s):  
High Frequency ◽  
Implied Volatility ◽  
Stock Index ◽  
High Frequency Data ◽  
Frequency Data ◽  
European Options ◽  
German Market ◽  
Content Type ◽  
The Relationship ◽  
Option Market

Purpose – The purpose of this paper is to investigate the relationship between option’s implied volatility smirk (IVS) and excess returns in the Germany’s leading stock index Deutscher-Aktien Index (DAX) 30. Design/methodology/approach – The study defines the IVS as the difference in implied volatility derived from out-of-the-money put options and at-the-money call options. This study employs the ordinary least square regression with Newey-West correction to analyse the relationship between IVS and excess DAX 30 index returns in Germany. Findings – The authors find that the German market adjusts information in an efficient way. Consequently, there is no information linkage between option volatility smirk and market index returns over the nine years sample period after considering the control variables, global financial crisis dummies, and the subsample test. Research limitations/implications – This study finds that the option market and the DAX 30 index are informationally efficient. Implications of the findings are that the investors cannot profit from the information contained in the IVS since the information is simultaneously incorporated into option prices and the stock index prices. The findings of this study are applicable to other markets with European options and for market participants who seek to exploit short-term market divergence from efficiency. Originality/value – The relationship between IVS and stock price changes has not been investigated sufficiently in academic literature. This study looks at this relationship in the context of European options using high-frequency transactions data. Prior studies look at this relationship for only American options using daily data. Pricing efficiency of the European option market using high-frequency data have not been studied in the prior literature. The authors find different results for the German market based on this high-frequency data set.

Unifying cell assembly theory with observations of brain dynamics

1999 ◽  
Vol 22 (2) ◽  
pp. 297-298
Author(s):  
R. Miller
Keyword(s):  
Empirical Evidence ◽  
High Frequency ◽  
Theoretical Work ◽  
Brain Dynamics ◽  
Cell Assembly ◽  
Neural Basis ◽  
Cell Assemblies ◽  
Active Representation ◽  
Sentence Planning

Empirical evidence suggests that high frequency electrographic activity is involved in active representation of meaningful entities in the cortex. Theoretical work suggests that distributed cell assemblies also represent meaningful entities. However, we are still some way from understanding how these two are related. This commentary also makes suggestions for further investigation of the neural basis of language at the level of both words and sentence planning.

scholarly journals The Behavior of Option’s Implied Volatility Index: a Case of India VIX

2015 ◽  
Vol 16 (2) ◽  
pp. 149-158 ◽  
Author(s):  
Imlak Shaikh ◽  
Puja Padhi
Keyword(s):  
Implied Volatility ◽  
Negative Impact ◽  
Practical Implication ◽  
Stock Market Volatility ◽  
Put Options ◽  
Monday Effect ◽  
Volatility Index ◽  
Significant Negative Impact ◽  
Day Of The Week ◽  
India Vix

The aim of this paper is to investigate the behavior of implied volatility in the form of day-of-the-week, year-of-the-month and surround the expiration of options. The persistence of volatility is modeled in ARCH/GARCH type framework. The empirical results have shown significant effects of the day-of-the-week, month-of-the-year and day of options expiration. The positive significant Monday effect explains that India VIX rises significantly on the initial days of the market opening, and the significant negative Wednesday effect shows that expected stock market volatility fall through Wednesday-Friday. Moreover, the study reveals the fact on options expiration, the evidence shows that India VIX fall significantly on the day of expiration of European call and put options. The March and December months have reported significant negative impact on the volatility index. Certainly, this kind of results holds practical implication for volatility traders, and helps to the market participant in hedging and pricing of options.

scholarly journals Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility

2019 ◽  
Vol 12 (1) ◽  
pp. 79-88
Author(s):  
T. Bazhenov ◽  
D. Fantazzini
Keyword(s):  
At Risk ◽  
Empirical Evidence ◽  
Value At Risk ◽  
Implied Volatility ◽  
Realized Volatility ◽  
Google Trends ◽  
Probability Level ◽  
Sample Analysis ◽  
Search Activity ◽  
Additional Information

This work proposes to forecast the Realized Volatility (RV) and the Value-at-Risk (VaR) of the most liquid Russian stocks using GARCH, ARFIMA and HAR models, including both the implied volatility computed from options prices and Google Trends data. The in-sample analysis showed that only the implied volatility had a significant effect on the realized volatility across most stocks and estimated models, whereas Google Trends did not have any significant effect. The outof-sample analysis highlighted that models including the implied volatility improved their forecasting performances, whereas models including internet search activity worsened their performances in several cases. Moreover, simple HAR and ARFIMA models without additional regressors often reported the best forecasts for the daily realized volatility and for the daily Value-at-Risk at the 1 % probability level, thus showing that efficiency gains more than compensate any possible model misspecifications and parameters biases. Our empirical evidence shows that, in the case of Russian stocks, Google Trends does not capture any additional information already included in the implied volatility.

Coherent Model-Free Implied Volatility: A Corridor Fix for High-Frequency VIX

2011 ◽  
Author(s):  
Torben G. Andersen ◽  
Oleg Bondarenko ◽  
Maria T. Gonzalez-Perez
Keyword(s):  
High Frequency ◽  
Implied Volatility ◽  
Model Free
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