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Journal articles on the topic 'Implied volatility (VIX、VXN)'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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1

Psaradellis, Ioannis, and Georgios Sermpinis. "Modelling and trading the U.S. implied volatility indices. Evidence from the VIX, VXN and VXD indices." International Journal of Forecasting 32, no. 4 (2016): 1268–83. http://dx.doi.org/10.1016/j.ijforecast.2016.05.004.

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2

Moghaddam, M. Dashti, Zhiyuan Liu, and R. A. Serota. "Distribution of Historic Market Data – Implied and Realized Volatility." Applied Economics and Finance 6, no. 5 (2019): 104. http://dx.doi.org/10.11114/aef.v6i5.4416.

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We undertake a systematic comparison between implied volatility, as represented by VIX (new methodology) and VXO (old methodology) and realized volatility. We do not find substantial difference in accuracy between VIX and VXO. We compare visually and statistically the distributions of realized and implied variance (volatility squared) and study the distribution of their ratio. The ratio distributions are studied both for the known realized variance (for the current month) and for the predicted realized variance (for the following month). We show that the ratio of the two is best fitted by a Be

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3

Magner, Nicolás, Jaime F. Lavin, Mauricio Valle, and Nicolás Hardy. "The predictive power of stock market’s expectations volatility: A financial synchronization phenomenon." PLOS ONE 16, no. 5 (2021): e0250846. http://dx.doi.org/10.1371/journal.pone.0250846.

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We explore the use of implied volatility indices as a tool for estimate changes in the synchronization of stock markets. Specifically, we assess the implied stock market’s volatility indices’ predictive power on synchronizing global equity indices returns. We built the correlation network of 26 stock indices and implemented in-sample and out-of-sample tests to evaluate the predictive power of VIX, VSTOXX, and VXJ implied volatility indices. To measure markets’ synchronization, we use the Minimum Spanning Tree length and the length of the Planar Maximally Filtered Graph. Our results indicate a

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4

Shaikh, Imlak. "The Brexit and investors' fear." Ekonomski pregled 69, no. 4 (2018): 396–442. http://dx.doi.org/10.32910/ep.69.4.3.

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This paper investigates most important implied volatility indices of Eurozone, Asia-Pacifi c, Africa, Canada and USA on the event of Brexit election of UK. Since the international economic events signal new information to market participants, the Brexit event has gauged in the 12 global markets’ volatility indices such as VFTSE, VIX, VDAX, VSMI, VSTOXX, VXJ, VHSI, VKOSPI, NVIX, VASX, VXIC and SAVI. A high fear of index about 20-36% has been noticed on the day of Brexit decision. Abnormal returns and cumulative abnormal returns on volatility index are found to be positive, while majority of glo

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5

SALVI, GIOVANNI, and ANATOLIY V. SWISHCHUK. "COVARIANCE AND CORRELATION SWAPS FOR FINANCIAL MARKETS WITH MARKOV-MODULATED VOLATILITIES." International Journal of Theoretical and Applied Finance 17, no. 01 (2014): 1450006. http://dx.doi.org/10.1142/s021902491450006x.

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In this paper, we price covariance and correlation swaps for financial markets with Markov-modulated volatilities. As an example, we consider stochastic volatility driven by a two-state continuous Markov chain. In this case, numerical examples are presented for VIX and VXN volatility indices (S&P 500 and NASDAQ-100, from January 2004 to June 2012). We also use VIX (January 2004 to June 2012) to price variance and volatility swaps for the two-state Markov-modulated volatility, and we present a numerical result in this case.

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Arak, Marcelle, and Naranchimeg Mijid. "The VIX and VXN volatility measures: Fear gauges or forecasts?" Derivatives Use, Trading & Regulation 12, no. 1 (2006): 14–27. http://dx.doi.org/10.1057/palgrave.dutr.1840040.

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7

Guo, Zi-Yi. "A Model of Plausible, Severe and Useful Stress Scenarios for VIX Shocks." Applied Economics and Finance 4, no. 3 (2017): 155. http://dx.doi.org/10.11114/aef.v4i3.2309.

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The implied volatility is a key component in determining option prices, and consequently a model of VIX shocks in stress testing plays a crucial role in quantifying market risk of derivative portfolios. Based on hypothetical moves of SPX spot price, we first apply the “sticky strike” rule to the existing SPX volatility surface and shock the implied volatility level by an additional relative amount, which would be determined by the analysis of historical VIX fluctuations. Then, we calculate the after-shock VIX index level according to the CBOE VIX White paper, and finally determine the daily VI

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8

Shaikh, Imlak, and Puja Padhi. "On the relationship between implied volatility index and equity index returns." Journal of Economic Studies 43, no. 1 (2016): 27–47. http://dx.doi.org/10.1108/jes-12-2013-0198.

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Purpose – The purpose of this paper is to analyze the asymmetric contemporaneous relationship between implied volatility index (India VIX) and Equity Index (S & P CNX Nifty Index). In addition, the study also analyzes the seasonality of implied volatility index in the form of day-of-the-week effects and option expiration cycle. Design/methodology/approach – This study employs simple OLS estimation to analyze the contemporaneous relationship among the volatility index and stock index. In order to obtain robust results, the analysis has been presented for the calendar years and sub-periods.

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9

G. Russon, Manuel, and Ahmad F. Vakil. "On the non-linear relationship between VIX and realized SP500 volatility." Investment Management and Financial Innovations 14, no. 2 (2017): 200–206. http://dx.doi.org/10.21511/imfi.14(2-1).2017.05.

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VIX, a ticker symbol for Volatility Index, measures the implied annual volatility of at-the-money SP500 Index Options. Conventional wisdom presumes VIX to measure the magnitude (positive or negative) of possible movements in future equity prices, with movements being a positive function of VIX. This research investigates the nature of the relationship between VIX and SP500 volatility, and answers the question as to whether that relationship is linear or nonlinear. Based on this research paper, the authors conclude that the realized SP500 volatility is nonlinear, and grows with the level of VIX

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10

Chittineni, Jyothi. "Indian Implied Volatility Index: A Macroeconomic Study." Applied Economics and Finance 5, no. 5 (2018): 75. http://dx.doi.org/10.11114/aef.v5i5.3585.

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The study investigates the dynamic behavior of Indian implied volatility index and its time dependent conditional correlations with selected macroeconomic variables. The volatility of macroeconomic variables is likely to put burden on inflation and also influence the economic decisions as investment vehicles. Thus, the volatility of these variables has become central issue for fund managers and investors. The study uses three macroeconomic variables, oil price, gold price and federal fund rate over the period 2nd March 2009 to 30th June 2018. The Dynamic Regime-Switching model reveals that the

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11

Sharma, Gagan, Parthajit Kayal, and Piyush Pandey. "Information Linkages Among BRICS Countries: Empirical Evidence from Implied Volatility Indices." Journal of Emerging Market Finance 18, no. 3 (2019): 263–89. http://dx.doi.org/10.1177/0972652719846315.

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In this article, we examine the information linkages of the forward-looking measure of volatility, the volatility index (VIX), for underlying equity market indices of BRICS countries—Brazil, Russia, India, China and South Africa. A study of the information transmission process confirmed a long-run equilibrium relationship between pairs of BRICS countries. The multivariate generalised autoregressive conditional heteroscedasticity (MGARCH) model revealed strong intertemporal linkages between sample VIX. Return and volatility spill-over matrix show the varying degree of connectedness of BRICS VIX

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12

Duan, Jin-Chuan, and Chung-Ying Yeh. "Jump and volatility risk premiums implied by VIX." Journal of Economic Dynamics and Control 34, no. 11 (2010): 2232–44. http://dx.doi.org/10.1016/j.jedc.2010.05.006.

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13

MUNIER, Bertrand, Eric BARTHALON, and Séverine MENGUY. "The magic of an Allaisian appraisal: implied and historical volatility revisited the VIX: once bitten, twice shy?" Finance Bulletin 1, no. 1 (2017): 63–74. http://dx.doi.org/10.20870/fb.2017.1.1.1873.

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Many contributions have dealt with the relation between implied and historical volatility in reference to the S&P100 index and on mostly limited samples of data. A large part of this literature finds that implied volatility defined directly from option prices is a biased estimator of future realized volatility, although some dissent has been expressed Christensen and Prabhala (1998). We investigate the issue on the larger market of the S&P500, using the VIX index as the measure of implied volatility and on a much larger sample (314 months), extending from January 1990 to December 2016.

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14

Pereira Azevedo, Luis Fernando, and Pedro L. Valls Pereira. "Testando o poder preditivo do VIX: uma aplicação do modelo de erro multiplicativo." Brazilian Review of Finance 13, no. 4 (2015): 571. http://dx.doi.org/10.12660/rbfin.v13n4.2015.57783.

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VIX - Volatility Index - emerged as an alternative calculation of implied volatility in order to mitigate some problems encountered in models of the Black-Scholes. This kind of volatility is seen as the best predictor of future volatility, given that option traders' expectations are embedded in their values. In this paper we test whether the VIX has more predictive power for future volatility and contains relevant information not found in time series models time for non-negative variables, treated by multiplicative error model. The results indicate that the VIX has greater predictive power in

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15

Lin, Jeng-Bau, Chin-Chia Liang, and Wei Tsai. "Nonlinear Relationships between Oil Prices and Implied Volatilities: Providing More Valuable Information." Sustainability 11, no. 14 (2019): 3906. http://dx.doi.org/10.3390/su11143906.

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This paper investigates the linear/nonlinear long-run and short-run dynamic relationships between oil prices and two implied volatilities, oil price volatility index (OVX) and stock index options volatility index (VIX), representing panic gauges. The results show that there is a long-run equilibrium relationship between oil prices and OVX (VIX) using the linear autoregressive distributed lag (ARDL)-bounds test. Likewise, while using the nonlinear autoregressive distributed lag (NARDL)-bounds test, not only does a long-run equilibrium relationship exist, but also the rising OVX (VIX) has a grea

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16

Lacombe, Chloe, Aitor Muguruza, and Henry Stone. "Asymptotics for volatility derivatives in multi-factor rough volatility models." Mathematics and Financial Economics 15, no. 3 (2021): 545–77. http://dx.doi.org/10.1007/s11579-020-00288-5.

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AbstractWe study the small-time implied volatility smile for Realised Variance options, and investigate the effect of correlation in multi-factor models on the linearity of the smile. We also develop an approximation scheme for the Realised Variance density, allowing fast and accurate pricing of Volatility Swaps. Additionally, we establish small-noise asymptotic behaviour of a general class of VIX options in the large strike regime.

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17

Chang, Kai‐Jiun, Mao‐Wei Hung, Yaw‐Huei Wang, and Kuang‐Chieh Yen. "Volatility information implied in the term structure of VIX." Journal of Futures Markets 39, no. 1 (2018): 56–71. http://dx.doi.org/10.1002/fut.21964.

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18

Lin, Yueh-Neng, and Anchor Y. Lin. "Using VIX futures to hedge forward implied volatility risk." International Review of Economics & Finance 43 (May 2016): 88–106. http://dx.doi.org/10.1016/j.iref.2015.10.033.

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19

Shaikh, Imlak, and Puja Padhi. "The information content of implied volatility index (India VIX)." Global Business Perspectives 1, no. 4 (2013): 359–78. http://dx.doi.org/10.1007/s40196-013-0025-4.

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20

Wang, Jying-Nan, Hung-Chun Liu, and Lu-Jui Chen. "On Forecasting Taiwanese Stock Index Option Prices: The Role of Implied Volatility Index." International Journal of Economics and Finance 9, no. 9 (2017): 133. http://dx.doi.org/10.5539/ijef.v9n9p133.

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This paper aims to propose four volatility measures: The first is the GARCH model advocated by Bollerslev (1986); the second is the GARCHVIX model which extends the GARCH model by including the volatility index (VIX) as explanatory variable for volatility; the last two are HS20D and HS252D, which represent the historical volatilities generated by traditional rolling window technique with 20- and 252-day historical index returns data, respectively. We examine the price information on VIX to improve the predictive performance of GARCH model for valuing TAIEX stock index call options (TXO) over t

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21

Osterrieder, Joerg, Daniel Kucharczyk, Silas Rudolf, and Daniel Wittwer. "Neural networks and arbitrage in the VIX." Digital Finance 2, no. 1-2 (2020): 97–115. http://dx.doi.org/10.1007/s42521-020-00026-y.

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Abstract The Chicago Board Options Exchange Volatility Index (VIX) is considered by many market participants as a common measure of market risk and investors’ sentiment, representing the market’s expectation of the 30-day-ahead looking implied volatility obtained from real-time prices of options on the S&P 500 index. While smaller deviations between implied and realized volatility are a well-known stylized fact of financial markets, large, time-varying differences are also frequently observed throughout the day. Furthermore, substantial deviations between the VIX and its futures might lead

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22

Ma, Changfu, Wei Xu, and Yue Kuen Kwok. "Willow tree algorithms for pricing VIX derivatives under stochastic volatility models." International Journal of Financial Engineering 07, no. 01 (2020): 2050003. http://dx.doi.org/10.1142/s2424786320500036.

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VIX futures and options are the most popular contracts traded in the Chicago Board Options Exchange. The bid-ask spreads of traded VIX derivatives remain to be wide, possibly due to the lack of reliable pricing models. In this paper, we consider pricing VIX derivatives under the consistent model approach, which considers joint modeling of the dynamics of the S&P index and its instantaneous variance. Under the affine jump-diffusion formulation with stochastic volatility, analytic integral formulas can be derived to price VIX futures and options. However, these integral formulas invariably i

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23

Shaikh, Imlak, and Puja Padhi. "The Behavior of Option’s Implied Volatility Index: a Case of India VIX." Verslas: Teorija ir Praktika 16, no. 2 (2015): 149–58. http://dx.doi.org/10.3846/btp.2015.463.

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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

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24

OROSI, GREG. "A NOVEL METHOD FOR ARBITRAGE-FREE OPTION SURFACE CONSTRUCTION." Annals of Financial Economics 14, no. 04 (2019): 1950021. http://dx.doi.org/10.1142/s2010495219500210.

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In this paper, we provide an alternative framework for constructing an arbitrage-free European-style option surface. The main motivation for our work is that such a construction has rarely been achieved in the literature so far. The novelty of our approach is that we perform the calibration and interpolation in the put option space. To demonstrate the applicability of our technique, we extract the model-free implied volatility from S&P 500 index options. Subsequently, we compare its information content to that of the CBOE VIX index. Our empirical tests indicate that information content of

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Tanha, Hassan, and Michael Dempsey. "The Information Content of ASX SPI 200 Implied Volatility." Review of Pacific Basin Financial Markets and Policies 19, no. 01 (2016): 1650002. http://dx.doi.org/10.1142/s0219091516500028.

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In Australia, the equivalent of a US VIX indicator has recently become available. In response, we consider whether the information captured in the implied volatility of options on the Australian SPI 200 Futures index is superior to the information content of a generalized autoregressive conditional heteroskedasticity (GARCH) approach to volatility prediction. We conclude that the implied volatility of at-the-money (ATM) call options on the SPI 200 Index futures is more powerful, dominating other modes of moneyness options as well as GARCH predictions.

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26

Srinivasan, Palamalai. "Macroeconomic Information and the Implied Volatility: Evidence from India VIX." Theoretical Economics Letters 07, no. 03 (2017): 490–501. http://dx.doi.org/10.4236/tel.2017.73037.

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FUKASAWA, M., I. ISHIDA, N. MAGHREBI, K. OYA, M. UBUKATA, and K. YAMAZAKI. "MODEL-FREE IMPLIED VOLATILITY: FROM SURFACE TO INDEX." International Journal of Theoretical and Applied Finance 14, no. 04 (2011): 433–63. http://dx.doi.org/10.1142/s0219024911006681.

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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

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LUONG, CHUONG, and NIKOLAI DOKUCHAEV. "ANALYSIS OF MARKET VOLATILITY VIA A DYNAMICALLY PURIFIED OPTION PRICE PROCESS." Annals of Financial Economics 09, no. 03 (2014): 1450006. http://dx.doi.org/10.1142/s2010495214500067.

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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

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Fousekis, Panos, and Vasilis Grigoriadis. "Causality between stock market and “fear gauge” indices: An empirical analysis with E-statistics." Applied Finance Letters 7, no. 1 (2018): 13–21. http://dx.doi.org/10.24135/afl.v7i1.75.

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This study investigates empirically the validity of three hypotheses that have been advanced to explain the tendency of stock market and volatility indices to move in opposite directions, using the notion of Brownian distance correlation. We consider three stock market-implied volatility index pairs, namely, the S&P 500 and the VIX, the DAX 100 and the V1XI, and the N225 and the JNIV. The empirical results support the leverage hypothesis relative to the volatility feedback hypothesis for the pairs S&P 500 and VIX, and N225 and JNIV, and the representativeness and affect heuristics hypo

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Shaikh, Imlak, and Puja Padhi. "Macroeconomic Announcements and the Implied Volatility Index: Evidence from India VIX." Margin: The Journal of Applied Economic Research 7, no. 4 (2013): 417–42. http://dx.doi.org/10.1177/0973801013500168.

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Shaikh, Imlak, and Puja Padhi. "The forecasting performance of implied volatility index: evidence from India VIX." Economic Change and Restructuring 47, no. 4 (2014): 251–74. http://dx.doi.org/10.1007/s10644-014-9149-z.

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Shaikh, Imlak. "On the Relationship between Economic Policy Uncertainty and the Implied Volatility Index." Sustainability 11, no. 6 (2019): 1628. http://dx.doi.org/10.3390/su11061628.

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This article examines the effects of economic policy uncertainty (EPU) on the implied volatility index. The implied volatility index of various markets has been analyzed in relation to scheduled macroeconomic announcements, such as EPU and equity market policy uncertainty (EMPU) indices. The study highlights that EPU contains important information to explain the diverse market effects of the U.S., which is gauged into the volatility index. Estimates obtained in an autoregressive conditional heteroscedasticity framework indicate the persistence of volatility during spikes in the EPU. More impor

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Jackwerth, Jens, and Grigory Vilkov. "Asymmetric Volatility Risk: Evidence from Option Markets*." Review of Finance 23, no. 4 (2018): 777–99. http://dx.doi.org/10.1093/rof/rfy025.

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Abstract Asymmetric volatility concerns the relation of returns to future expected volatility. Much is known from option prices about the marginal risk-neutral distributions (RNDs) of S&P 500 returns and of relative changes in future expected volatility (VIX). While the bivariate RND cannot be inferred from the marginals, we propose a novel identification based on long-dated index options. We estimate the risk-neutral asymmetric volatility implied correlation (AVIC) and find it to be significantly lower than its realized counterpart. We interpret the economics of the asymmetric volatility

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Onan, Mustafa, Aslihan Salih, and Burze Yasar. "Impact of macroeconomic announcements on implied volatility slope of SPX options and VIX." Finance Research Letters 11, no. 4 (2014): 454–62. http://dx.doi.org/10.1016/j.frl.2014.07.006.

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Wirjanto, Tony S., and Anyi Zhu. "Implied volatility surfaces during the period of global financial crisis." International Journal of Financial Engineering 05, no. 01 (2018): 1850001. http://dx.doi.org/10.1142/s2424786318500019.

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This paper adopts a parametric regression approach to model and calibrate implied volatility surface during the period of the global financial crisis. Due to its relatively low computational cost, it facilitates comparison across a great number of different competing models. The proposed regression models are backtested against historical S&P 500 prices during both volatile and non-volatile periods as proxied by the VIX index around the same time period, and the fits of the models are assessed. Furthermore both an equally weighted scheme and an alternative scheme based on observed implied

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Barletta, Andrea, Elisa Nicolato, and Stefano Pagliarani. "The short-time behavior of VIX-implied volatilities in a multifactor stochastic volatility framework." Mathematical Finance 29, no. 3 (2018): 928–66. http://dx.doi.org/10.1111/mafi.12196.

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Brunhuemer, Alexander, Gerhard Larcher, and Lukas Larcher. "Analysis of Option Trading Strategies Based on the Relation of Implied and Realized S&P500 Volatilities." ACRN Journal of Finance and Risk Perspectives 10, no. 1 (2021): 166–203. http://dx.doi.org/10.35944/jofrp.2021.10.1.010.

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In this paper, we examine the performance of certain short option trading strategies on the S&P500 with backtesting based on historical option price data. Some of these strategies show significant outperformance in relation to the S&P500 index. We seek to explain this outperformance by modeling the negative correlation between the S&P500 and its implied volatility (given by the VIX) and through Monte Carlo simulation. We also provide free testing software and give an introduction to its use for readers interested in running further backtests on their own.

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Kotyza, Pavel, Katarzyna Czech, Michał Wielechowski, Luboš Smutka, and Petr Procházka. "Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?" Agriculture 11, no. 2 (2021): 93. http://dx.doi.org/10.3390/agriculture11020093.

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Securitization of the agricultural commodity market has accelerated since the beginning of the 21st century, particularly in the times of financial market uncertainty and crisis. Sugar belongs to the group of important agricultural commodities. The global financial crisis and the COVID-19 pandemic has caused a substantial increase in the stock market volatility. Moreover, the novel coronavirus hit both the sugar market’s supply and demand side, resulting in sugar stock changes. The paper aims to assess potential structural changes in the relationship between sugar prices and the financial mark

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van Dijk, Marcel, Cornelis de Graaf та Cornelis Oosterlee. "Between ℙ and ℚ: The ℙℚ Measure for Pricing in Asset Liability Management". Journal of Risk and Financial Management 11, № 4 (2018): 67. http://dx.doi.org/10.3390/jrfm11040067.

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Insurance companies issue guarantees that need to be valued according to the market expectations. By calibrating option pricing models to the available implied volatility surfaces, one deals with the so-called risk-neutral measure Q , which can be used to generate market consistent values for these guarantees. For asset liability management, insurers also need future values of these guarantees. Next to that, new regulations require insurance companies to value their positions on a one-year horizon. As the option prices at t = 1 are unknown, it is common practice to assume that the parameters o

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Sinha, Sonalika, and Bandi Kamaiah. "Estimating Option-implied Risk Aversion for Indian Markets." IIM Kozhikode Society & Management Review 6, no. 1 (2017): 90–97. http://dx.doi.org/10.1177/2277975216677600.

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What do nearly 1.5 lakh observations of options data say about risk preferences of Indian investors? This paper explores a nonparametric technique to compute probability density functions (PDFs) directly from NIFTY 50 option prices in India, based on the utility preferences of the representative investor. Use of probability density functions to estimate investor expectations of the distribution of future levels of the underlying assets has gained tremendous popularity over the last decade. Studying option prices provides information about the market participants’ probability assessment of the

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Chittineni, Jyothi. "The Impact of COVID-19 Pandemic on the Relationship between India’s Volatility Index and Nifty 50 Returns." Indian Journal of Finance and Banking 4, no. 2 (2020): 58–63. http://dx.doi.org/10.46281/ijfb.v4i2.731.

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The paper intends to re-examine the relationship between India’s Implied Volatility Index (IVIX) and Nifty 50 Returns during this COVID-19 pandemic. The study results are important for two reasons, one is to understand whether Indian VIX is fulfilling the purpose of measuring the near future volatility of Nifty 50 during this pandemic, and secondly, it reports the impact of COVID-19 on the investors’ perceptions about the returns and its volatility. The study results documented that the Nifty return and IVIX are moving independently during the COVID-19 pandemic and there is no association betw

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Löwen, Celina, Bilal Kchouri, and Thorsten Lehnert. "Is this time really different? Flight-to-safety and the COVID-19 crisis." PLOS ONE 16, no. 5 (2021): e0251752. http://dx.doi.org/10.1371/journal.pone.0251752.

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During periods of market stress, risk-averse investors reallocate their investments from stocks to gold in a bid to hedge risks. Market participants interpret the induced gold price increase as an indication of safe-haven purchases and a signal of increased uncertainty in the general economic and financial conditions, thereby causing higher gold price volatility. The aim of this paper is to analyze whether this flight to safety effect can be observed during the COVID-19 crisis, which is considered to be a one-of-a-kind crisis and obviously of different origin compared to previous (financial) c

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Bernis, Guillaume, Riccardo Brignone, Simone Scotti, and Carlo Sgarra. "A Gamma Ornstein–Uhlenbeck model driven by a Hawkes process." Mathematics and Financial Economics 15, no. 4 (2021): 747–73. http://dx.doi.org/10.1007/s11579-021-00295-0.

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AbstractWe propose an extension of the $$\Gamma $$ Γ -OU Barndorff-Nielsen and Shephard model taking into account jump clustering phenomena. We assume that the intensity process of the Hawkes driver coincides, up to a constant, with the variance process. By applying the theory of continuous-state branching processes with immigration, we prove existence and uniqueness of strong solutions of the SDE governing the asset price dynamics. We propose a measure change of self-exciting Esscher type in order to describe the relation between the risk-neutral and the historical dynamics, showing that the

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"Option Writing: Using VIX to Improve Returns." Journal of Derivatives, December 1, 2018. http://dx.doi.org/10.3905/jod.2018.26.2.038.

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Buy-write and put-write strategies have been shown to match market returns with lower volatility, resulting in higher risk-adjusted performance. The strategies benefit from the fact that the implied volatility of options is generally higher than actual realized volatility. In this article, we show that this premium is higher at elevated levels of implied volatility (as represented by the VIX index level). Based on this finding, we propose a simple conditional strategy in which one sells options at elevated levels of the VIX. Using data from 1990 through 2018, we find that this conditional stra

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Duan, Jin-Chuan, and Chung-Ying Yeh. "Jump and Volatility Risk Premiums Implied by VIX." SSRN Electronic Journal, 2008. http://dx.doi.org/10.2139/ssrn.966682.

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Clements, Adam, Yin Liao, and Yusui Tang. "Moving beyond Volatility Index (VIX): HARnessing the term structure of implied volatility." Journal of Forecasting, June 7, 2021. http://dx.doi.org/10.1002/for.2797.

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Woebbeking, Fabian. "Cryptocurrency volatility markets." Digital Finance, August 2, 2021. http://dx.doi.org/10.1007/s42521-021-00037-3.

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AbstractBy computing a volatility index (CVX) from cryptocurrency option prices, we analyze this market’s expectation of future volatility. Our method addresses the challenging liquidity environment of this young asset class and allows us to extract stable market implied volatilities. Two alternative methods are considered to compute volatilities from granular intra-day cryptocurrency options data, which spans over the COVID-19 pandemic period. CVX data therefore capture ‘normal’ market dynamics as well as distress and recovery periods. The methods yield two cointegrated index series, where th

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Chakrabarti, Prasenjit. "Examining Contemporaneous Relationship between Return of Nifty Index and India VIX." International Journal of Financial Management 5, no. 2 (2015). http://dx.doi.org/10.21863/ijfm/2015.5.2.011.

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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.

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Duan, Jin-Chuan, and Chung-Ying Yeh. "Price and Volatility Dynamics Implied by the VIX Term Structure." SSRN Electronic Journal, 2011. http://dx.doi.org/10.2139/ssrn.1788252.

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Bahadur G. C., Surya, and Ranjana Kothari. "The Forecasting Power of the Volatility Index: Evidence from the Indian Stock Market." IRA-International Journal of Management & Social Sciences (ISSN 2455-2267) 4, no. 1 (2016). http://dx.doi.org/10.21013/jmss.v4.n1.p21.

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<div><p><em>Stock market volatility is a measure of risk in investment and it plays a key role in securities pricing and risk management. </em><em>The paper empirically analyzes the relationship between India VIX and volatility in Indian stock market. </em><em>India VIX is a measure of implied volatility which reflects markets’ expectation of future short-term stock market volatility.</em><em> It is a volatility index based on the index option prices of Nifty. </em><em>The study is based on time series data comprising of daily c

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