The 2008 financial crisis provides a valuable opportunity to study empirical data of market volatility during severe financial crisis. In this thesis, we study the implied volatility of VIX options during the crisis (2008) and a relatively calm period (2011). We present a method of calculating the implied volatility of VIX options and fit the implied volatilities using a 4th degree spline interpolation and propose method of extracting risk neutral density from fitted data. We analyze the slope and the level of the fitted implied volatility of VIX options during those periods. The results show that the level of the implied volatility of VIX options is higher and the slope is flatter during the distressed market compared to the relative calm periods.

The thesis investigates the impact of the fundamental news announcements on the movements of the VIX volatility index and the VIX Futures prices. The theoretical part of the thesis explains the construction of the VIX Index and the VIX Futures, describes the most important fundamental news for the US economy and presents a methodology for the modelling of the relationship between the news announcements and the VIX index movements with a simple linear regression model. In the empirical part of the thesis, we analyze the impact of 105 US fundamental news, from the Reuters Eikon database, on the VIX Index movements on theday of the news announcements as well as on the subsequent day. We find a strong relationship between the surprise component of the news and the VIX Index movements on the day of the news announcement, with the statistically significant news explaining 5-10% of the total return variance (for news with small number of observations up to 30-50%) on the announcement day. In the second part of the empirical study, simple trading system is proposed in order to utilize the possible impact of the economic news on the next-day (after announcement) returns of VIX futures in order to achieve speculative profits. Although the models seem to possess some limited out-sample profitability for some of the news, the results are for most of the cases statistically insignificant and the potential profits from the news trading seem to be relatively low.

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Cette étude tente d’améliorer le modèle standard de prévision de l’indice de volatilité VIX à l’aide du Search Volume Index (SVI) rapporté par Google Trends à l’échelle journalière. La volatilité des marchés étant basée sur la peur et la recherche de gains économiques des agents de marché, Google Trends permet un accès direct et virtuellement immédiat aux désirs et aux inquiétudes de ceux-ci. Durant la période de janvier 2010 à décembre 2016, les séries de 15 termes de recherche liés à l’économie sont utilisées pour tenter d’améliorer les modèles ARIMA et SARIMA recommandés dans la prévision du VIX. Contrairement aux études similaires effectuées à l’échelle hebdomadaire, les résultats démontrent qu’il n’y a pas d’amélioration des prévisions causée par l’addition des données Google Trends aux modèles.

This study investigates how term structure dynamics of VIX futures can be exploited forabnormal returns. To be able to access volatility as a tradeable asset, the trading strategiesonly trades ETFs which are designed to replicate the movements of VIX futures index. Itis established that such ETFs are unsuitable for buy-and-hold investments because of thenegative roll yield it usually suffers, caused by the slope of the VIX term structure.Consequently, these conditions create opportunities for strategies that use direct andinverse VIX ETFs to be profitable. The study is a quantitative study that uses historicalprice data to back test three different trading strategies. The strategies are tested over theperiod 11-oct-2011 to 31-mar-2020. The authors have deliberately chosen to delimit thestudy by not testing the performance of the ETFs, not statistically test the risk-adjustedreturns and not perform a regression to calculate optimal hedge ratios for the strategies.The results from this study shows that its possible for strategies that exploit the termstructure dynamics of VIX futures to generate abnormal returns.

<p>Volatility forecast plays a central role in the financial decision making process. An intrinsic purpose of any investor is profit earning. For that purpose investors need to estimate the risk. One of the most efficient</p><p>methods to this end is the volatility estimation. In this theses I compare the CBOE Volatility Index, (VIX) with the actual volatility on an index at the Nordic Market. The actual volatility is defined as the one-day-ahead prediction as calculated by using the GARCH(1,1) model. By using the VIX model I performed consecutive predictions 30 days ahead between February the 2nd, 2007 to March</p><p>the 6th, 2007. These predictions were compared with the GARCH(1,1) one-day-ahead predictions for the same period. To my knowledge, such comparisons have not been performed earlier on the Nordic Market. The conclusion of the study was that the VIX predictions tends to higher values then the GARCH(1,1) predictions except for large prices upward jumps, which indicates that the VIX is not able to predict future shocks.</p><p>Except from these jumps, the VIX more often shows larger value than the GARCH(1,1). This is interpreted as an uncertainly of the prediction. However, the VIX predictions follows the actual volatility reasonable</p><p>well. I conclude that the VIX estimation can be used as a reliable estimator of market volatility.</p>

<p>I denna uppsats jämförs hur väl tre historiskt baserade konditionella GARCH-modeller samt en naiv historisk modell predikterar volatiliteten för Standard & Poors 500 Composite index år 2006, jämfört med den optionsbaserade volatiliteten från Chicago Board Option Exchange volatilitetsindex VIX. Både de konditionella, den naiva historiska- och VIX volatilitetsprognoser utvärderas mot den historiskt observerade volatiliteten för urvalsperioden. För att utvärdera respektive modells prediktionsförmåga används tre utvärderingsmått; Regressionsanalys med Walds koefficienttest, det genomsnittliga prognosfelet modellerat med Root Mean Square Error (RMSE), samt Theil’s U-statistikan.</p><p>Undersökningen visar att det är tröskel-GARCH-modellen TGARCH som bäst predikterar volatiliteten för S&P 500 men att en kombination av TGARCH och VIX tillför ytterligare förklaringsgrad till modellen.</p>

I denna uppsats jämförs hur väl tre historiskt baserade konditionella GARCH-modeller samt en naiv historisk modell predikterar volatiliteten för Standard &amp; Poors 500 Composite index år 2006, jämfört med den optionsbaserade volatiliteten från Chicago Board Option Exchange volatilitetsindex VIX. Både de konditionella, den naiva historiska- och VIX volatilitetsprognoser utvärderas mot den historiskt observerade volatiliteten för urvalsperioden. För att utvärdera respektive modells prediktionsförmåga används tre utvärderingsmått; Regressionsanalys med Walds koefficienttest, det genomsnittliga prognosfelet modellerat med Root Mean Square Error (RMSE), samt Theil’s U-statistikan. Undersökningen visar att det är tröskel-GARCH-modellen TGARCH som bäst predikterar volatiliteten för S&amp;P 500 men att en kombination av TGARCH och VIX tillför ytterligare förklaringsgrad till modellen.

Volatility forecast plays a central role in the financial decision making process. An intrinsic purpose of any investor is profit earning. For that purpose investors need to estimate the risk. One of the most efficient methods to this end is the volatility estimation. In this theses I compare the CBOE Volatility Index, (VIX) with the actual volatility on an index at the Nordic Market. The actual volatility is defined as the one-day-ahead prediction as calculated by using the GARCH(1,1) model. By using the VIX model I performed consecutive predictions 30 days ahead between February the 2nd, 2007 to March the 6th, 2007. These predictions were compared with the GARCH(1,1) one-day-ahead predictions for the same period. To my knowledge, such comparisons have not been performed earlier on the Nordic Market. The conclusion of the study was that the VIX predictions tends to higher values then the GARCH(1,1) predictions except for large prices upward jumps, which indicates that the VIX is not able to predict future shocks. Except from these jumps, the VIX more often shows larger value than the GARCH(1,1). This is interpreted as an uncertainly of the prediction. However, the VIX predictions follows the actual volatility reasonable well. I conclude that the VIX estimation can be used as a reliable estimator of market volatility.

No / Ritual and ritual specialists have often been dissociated from power in the writings of prehistorians and archaeologists. From ethnographic and ethnohistoric accounts, however, ritual specialists often exert disproportionate control over the maintenance, manipulation, and elaboration of social codes and practices. Their roles in ritual practice (orthopraxy in non-literate societies) and its effect on decision-making accord them considerable social and political importance. Due to this involvement they become the targets of ritual sanctions that include punitive rites, ritualized deaths, and suppression during periods of rapid social change, both from within their own societies and from without. The present article derives from a re-analysis of the Vix (Côte-d'Or, Burgundy) human skeletal remains, specifically with reference to the age, sex and health status of the interred individual. An evaluation of the social roles of this so-called `Princess' is then attempted, integrating this biological information with that derived from a consideration of the grave inclusions and their imagery in the context of competitive feasting and social change in the late Hallstatt period.