An Investor Sentiment Barometer - Greek Implied Volatility Index

2008 ◽  
Author(s):  
Costas Siriopoulos ◽  
Athanasios Fassas
2012 ◽  
Vol 23 (2) ◽  
pp. 77-93 ◽  
Author(s):  
Costas Siriopoulos ◽  
Athanasios Fassas

2020 ◽  
Vol 21 (5) ◽  
pp. 1350-1374
Author(s):  
Imlak Shaikh

Economic policy drives investment, production, employment, and other macroeconomic indicators of the economy. The study examines the equity, commodity, interest rates, and currency markets, taking into consideration the US economic policy uncertainty (EPU) index. The present work determines the association among policy uncertainty and volatility index, expressed in terms of generalized autoregressive conditional heteroscedasticity and period of empirical work spanning from 2000 to 2018. The results suggest that equity markets’ volatility tends to be very high based on a high degree of policy uncertainty. The findings on the commodity market indicate that crude oil and gold prices remain more volatile during the presidential election and financial crisis. One of the essential results shows that the 2000s boom, early credit crunch, Lehman’s collapse and recession, and fiscal policy battles have significantly affected the equity, currency, and commodity markets. The interest rates and currency markets have responded considerably to Feds’ and EPU index. The empirical outcome provides evidence that implied volatility index is a forward looking expectation of future stock market volatility, and it uncovers that policy uncertainty affects investor sentiment. The present work holds some practical implications for the government to formulate policies to regulate the US market.


Author(s):  
Prasenjit Chakrabarti

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.


2021 ◽  
Vol 73 ◽  
pp. 101612
Author(s):  
Wen Long ◽  
Manyi Zhao ◽  
Yeran Tang

2014 ◽  
Vol 09 (03) ◽  
pp. 1450006 ◽  
Author(s):  
CHUONG LUONG ◽  
NIKOLAI DOKUCHAEV

The paper studies methods of dynamic estimation of volatility for financial time series. We suggest to estimate the volatility as the implied volatility inferred from some artificial "dynamically purified" price process that in theory allows to eliminate the impact of the stock price movements. The complete elimination would be possible if the option prices were available for continuous sets of strike prices and expiration times. In practice, we have to use only finite sets of available prices. We discuss the construction of this process from the available option prices using different methods. In order to overcome the incompleteness of the available option prices, we suggests several interpolation approaches, including the first order Taylor series extrapolation and quadratic interpolation. We examine the potential of the implied volatility derived from this proposed process for forecasting of the future volatility, in comparison with the traditional implied volatility process such as the volatility index VIX.


2012 ◽  
pp. 479-492
Author(s):  
David E. Allen ◽  
Abhay K. Singh ◽  
Robert J. Powell ◽  
Akhmad Kramadibrata

2008 ◽  
Vol 42 (1) ◽  
pp. 103-125 ◽  
Author(s):  
Bart Frijns ◽  
Alireza Tourani‐Rad ◽  
Yajie Zhang

2011 ◽  
Vol 14 (04) ◽  
pp. 433-463 ◽  
Author(s):  
M. FUKASAWA ◽  
I. ISHIDA ◽  
N. MAGHREBI ◽  
K. OYA ◽  
M. UBUKATA ◽  
...  

We propose a new method for approximating the expected quadratic variation of an asset based on its option prices. The quadratic variation of an asset price is often regarded as a measure of its volatility, and its expected value under pricing measure can be understood as the market's expectation of future volatility. We utilize the relation between the asset variance and the Black-Scholes implied volatility surface, and discuss the merits of this new model-free approach compared to the CBOE procedure underlying the VIX index. The interpolation scheme for the volatility surface we introduce is designed to be consistent with arbitrage bounds. We show numerically under the Heston stochastic volatility model that this approach significantly reduces the approximation errors, and we further provide empirical evidence from the Nikkei 225 options that the new implied volatility index is more accurate in predicting future volatility.


Author(s):  
Klaus Grobys ◽  
James W. Kolari ◽  
Jere Rutanen

AbstractFactor momentum produces robust average returns that exhibit a similar economic magnitude as stock price momentum. To the extent that the post-earnings announcement drift (PEAD) factor captures mispricing, winner factors earn profits from being long on underpriced stocks and short on overpriced stocks. Conversely, loser-factors’ negative exposure to the PEAD factor suggests that loser factors capture mispricing by being long on overpriced stocks and short on underpriced stocks. Option-implied volatility scaling increases both the economic magnitude and statistical significance of factor momentum. Factor momentum is not exposed to the same crashes as stock price momentum and therefore could provide a hedge for stock price momentum crash risks. Also, factor momentum mispricing is more pronounced when investor sentiment is high.


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