94 resultados para implied volatility

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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The purpose of this thesis is to investigate scheduled market announcements’ effects on Euro implied volatility. Timeline selected for this study ranges from 2005 to 2009. The method chosen is so-called event study approach, in which five days prior to a news announcement stand for a pre-event period, and five days after the announcement form a post-event period. Statistical research method employed is Mann-Whitney-Wilcoxon test, which examines two evenly-sized distributions’ equality, in this case the distributions being the pre- and post-event periods. Observations are based on daily data of US dollar nominated Euro at-the-money call options. Research results partially back up previous literature’s view of uncertainty increasing prior to the news announcement. After the exact contents of the news is public, uncertainty levels measured by implied volatility tend to lower.

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Volatility has a central role in various theoretical and practical applications in financial markets. These include the applications related to portfolio theory, derivatives pricing and financial risk management. Both theoretical and practical applications require good estimates and forecasts for the asset return volatility. The goal of this study is to examine the forecast performance of one of the more recent volatility measures, model-free implied volatility. Model-free implied volatility is extracted from the prices in the option markets, and it aims to provide an unbiased estimate for the market’s expectation on the future level of volatility. Since it is extracted from the option prices, model-free implied volatility should contain all the relevant information that the market participants have. Moreover, model-free implied volatility requires less restrictive assumptions than the commonly used Black-Scholes implied volatility, which means that it should be less biased estimate for the market’s expectations. Therefore, it should also be a better forecast for the future volatility. The forecast performance of model-free implied volatility is evaluated by comparing it to the forecast performance of Black-Scholes implied volatility and GARCH(1,1) forecast. Weekly forecasts for six years period were calculated for the forecasted variable, German stock market index DAX. The data consisted of price observations for DAX index options. The forecast performance was measured using econometric methods, which aimed to capture the biasedness, accuracy and the information content of the forecasts. The results of the study suggest that the forecast performance of model-free implied volatility is superior to forecast performance of GARCH(1,1) forecast. However, the results also suggest that the forecast performance of model-free implied volatility is not as good as the forecast performance of Black-Scholes implied volatility, which is against the hypotheses based on theory. The results of this study are consistent with the majority of prior research on the subject.

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The paper studies the relationship between implied volatility and realized volatility by utilizing regression analysis and correlations.

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In this study we used market settlement prices of European call options on stock index futures to extract implied probability distribution function (PDF). The method used produces a PDF of returns of an underlying asset at expiration date from implied volatility smile. With this method, the assumption of lognormal distribution (Black-Scholes model) is tested. The market view of the asset price dynamics can then be used for various purposes (hedging, speculation). We used the so called smoothing approach for implied PDF extraction presented by Shimko (1993). In our analysis we obtained implied volatility smiles from index futures markets (S&P 500 and DAX indices) and standardized them. The method introduced by Breeden and Litzenberger (1978) was then used on PDF extraction. The results show significant deviations from the assumption of lognormal returns for S&P500 options while DAX options mostly fit the lognormal distribution. A deviant subjective view of PDF can be used to form a strategy as discussed in the last section.

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The goal of this research was to make an overall sight to VIX and how it can be used as a stock market indicator. Volatility index, often referred as the fear index, measures how much does it cost for investor to protect his/hers S&P 500 position from fluctuations with options. Over the relatively short history of VIX it has succesfull timing coordinator and it has told about the market state adding its own psychological view of the amount of fear and greed.

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The goal of this research was to make an overall sight to VIX® and how it can be used as a stock market indicator. Volatility index often referred as the fear index, measures how much it costs for investor to protect his/her S&P 500 position from fluctuations with options. Over the relatively short history of VIX it has been a successful timing coordinator and it has given incremental information about the market state adding its own psychological view of the amount of fear and greed. Correctly utilized VIX information gives a considerable advantage in timing market actions. In this paper we test how VIX works as a leading indicator of broad stock market index such as S&P 500 (SPX). The purpose of this paper is to find a working way to interpret VIX. The various tests are made on time series data ranging from the year 1990 to the year 2010. The 10-day simple moving average strategy gave significant profits from the whole time when VIX data is available. Strategy was able to utilize the increases of SPX in example portfolio value and was able to step aside when SPX was declining. At the times when portfolio was aside of S it was on safety fund like on treasury bills getting an annual yield of 3 percent. On the other side just a static number’s of VIX did not work as indicators in a profit making way.

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The objective of the study is to extend the existing hedging literature of the commodity price risks by investigating what kind of hedging strategies can be used in companies using bitumen as raw material in their production. Five different alternative swap hedging strategies in bitumen markets are empirically tested. Strategies tested are full hedge strategy, simple, conservative, and aggressive term structure strategies, and implied volatility strategy. The effectiveness of the alternative strategies is measured by excess returns compared to no hedge strategy. In addition, the downside risk of each strategy is measured with target absolute semi-deviation. Results indicate that any of the tested strategies does not outperform the no hedge strategy in terms of excess returns in all maturities. The best-performing aggressive term structure strategy succeeds to create positive excess returns only in short maturities. However, risk seems to increase hand-in-hand with the excess returns so that the best-performing strategies get the highest risk metrics as well. This implicates that the company willing to gain from favorable price movements must be ready to bear a greater risk. Thus, no superior hedging strategy over the others is found.

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Research has highlighted the adequacy of Markov regime-switching model to address dynamic behavior in long term stock market movements. Employing a purposed Extended regime-switching GARCH(1,1) model, this thesis further investigates the regime dependent nonlinear relationship between changes in oil price and stock market volatility in Saudi Arabia, Norway and Singapore for the period of 2001-2014. Market selection is prioritized to national dependency on oil export or import, which also rationalizes the fitness of implied bivariate volatility model. Among two regimes identified by the mean model, high stock market return-low volatility regime reflects the stable economic growth periods. The other regime characterized by low stock market return-high volatility coincides with episodes of recession and downturn. Moreover, results of volatility model provide the evidence that shocks in stock markets are less persistent during the high volatility regime. While accelerated oil price rises the stock market volatility during recessions, it reduces the stock market risk during normal growth periods in Singapore. In contrast, oil price showed no significant notable impact on stock market volatility of target oil-exporting countries in either of the volatility regime. In light to these results, international investors and policy makers could benefit the risk management in relation to oil price fluctuation.

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The aim of this study is to investigate volatility spillover-effect and market integration between BRIC countries. Motivated by existing literature of market integration between developed and emerging markets, we will investigate market linkages using multivariate asymmetric GARCH BEKK model. The increasing globalization of the financial markets and consequent higher volatility transfer between markets makes it more important to understand market integration between BRIC countries. We investigate the stock market integration and volatility transfer between the BRIC countries form 1998 to 2007, using daily data. The empirical results show that there are international diversification benefits among Brazil, Russia, China and India. U.S. influence to these countries has been week, even though U.S. economy has been leading the global financial markets. From Finnish point of view, diversification benefits are robust but we find some correlation with Russia and China.

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In this literature review the theorethical framework of Financial transaction taxes and their assumed effect on market volatility is assessed. The empirical evidence from various studies is compared against the theory and a simple empirical review of the Finnish stock market is conducted. The findings implicate that financial transaction taxes can not reduce volatility and their actual effect on markets is dependend by many other factors as well. Some evidence even suggests that transactions taxes may actually raise volatility.

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This thesis examines the impact of foreign exchange rate volatility to the extent of use of foreign currency derivatives. Especially the focus is on the impacts of 2008 global financial crisis. The crisis increased risk level in the capital markets greatly. The change in the currency derivatives use is analyzed by comparing means between different periods and in addition, by linear regression that enables to analyze the explanatory power of the model. The research data consists of financial statements figures from fiscal years 2006-2011 published by firms operating in traditional Finnish industrial sectors. Volatilities of the chosen three currency pairs is calculated from the daily fixing rates of ECB. Based on the volatility the sample period is divided into three sub-periods. The results suggest that increased FX market volatility did not increase the use foreign currency derivatives. Furthermore, the increased foreign exchange rate volatility did not increase the power of linear regression model to estimate the use foreign currency derivatives compared to previous studies.