27 resultados para Volatility Models, Volatility, Equity Markets
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We would like to thank Philipp Schwarz and Julia Gückel for their dedicated support in preparing this paper and our colleagues and students of the School of Engineering and the Business School for our fruitful discussions.
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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics
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This paper analyses, through a dynamic panel data model, the impact of the Financial and the European Debt crisis on the equity returns of the banking system. The model is also extended to specifically investigate the impact on countries who received rescue packages. The sample under analysis considers eleven countries from January 2006 to June 2013. The main conclusion is that there was in fact a structural change in banks’ excess returns due to the outbreak of the European Debt Crisis, when stock markets were still recovering from the Financial Crisis of 2008.
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This study focuses on the implementation of several pair trading strategies across three emerging markets, with the objective of comparing the results obtained from the different strategies and assessing if pair trading benefits from a more volatile environment. The results show that, indeed, there are higher potential profits arising from emerging markets. However, the higher excess return will be partially offset by higher transaction costs, which will be a determinant factor to the profitability of pair trading strategies. Also, a new clustering approach based on the Principal Component Analysis was tested as an alternative to the more standard clustering by Industry Groups. The new clustering approach delivers promising results, consistently reducing volatility to a greater extent than the Industry Group approach, with no significant harm to the excess returns.
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The aim of this work project is to find a model that is able to accurately forecast the daily Value-at-Risk for PSI-20 Index, independently of the market conditions, in order to expand empirical literature for the Portuguese stock market. Hence, two subsamples, representing more and less volatile periods, were modeled through unconditional and conditional volatility models (because it is what drives returns). All models were evaluated through Kupiec’s and Christoffersen’s tests, by comparing forecasts with actual results. Using an out-of-sample of 204 observations, it was found that a GARCH(1,1) is an accurate model for our purposes.
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This paper develops the model of Bicego, Grosso, and Otranto (2008) and applies Hidden Markov Models to predict market direction. The paper draws an analogy between financial markets and speech recognition, seeking inspiration from the latter to solve common issues in quantitative investing. Whereas previous works focus mostly on very complex modifications of the original hidden markov model algorithm, the current paper provides an innovative methodology by drawing inspiration from thoroughly tested, yet simple, speech recognition methodologies. By grouping returns into sequences, Hidden Markov Models can then predict market direction the same way they are used to identify phonemes in speech recognition. The model proves highly successful in identifying market direction but fails to consistently identify whether a trend is in place. All in all, the current paper seeks to bridge the gap between speech recognition and quantitative finance and, even though the model is not fully successful, several refinements are suggested and the room for improvement is significant.
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This paper is mainly concerned with the tracking accuracy of Exchange Traded Funds (ETFs) listed on the London Stock Exchange (LSE) but also evaluates their performance and pricing efficiency. The findings show that ETFs offer virtually the same return but exhibit higher volatility than their benchmark. It seems that the pricing efficiency, which should come from the creation and redemption process, does not fully hold as equity ETFs show consistent price premiums. The tracking error of the funds is generally small and is decreasing over time. The risk of the ETF, daily price volatility and the total expense ratio explain a large part of the tracking error. Trading volume, fund size, bid-ask spread and average price premium or discount did not have an impact on the tracking error. Finally, it is concluded that market volatility and the tracking error are positively correlated.
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As nonprofits do not have access to the same capital markets as for-profit enterprises, organizations usually scramble for funding to keep up with their mission. This scenario can be changed through the use of the right financial engineering. This Work Project aims at studying an innovative financing mechanism based on the concept of quasi-equity for organizations devoted to social ends to cope with their capital needs. A quasi-equity investment model is built for the Portuguese social business SPEAK, and an in-depth assessment of its current financial, organizational and impact situations is conducted. This is a pioneer case study in Portugal.
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In this work we are going to evaluate the different assumptions used in the Black- Scholes-Merton pricing model, namely log-normality of returns, continuous interest rates, inexistence of dividends and transaction costs, and the consequences of using them to hedge different options in real markets, where they often fail to verify. We are going to conduct a series of tests in simulated underlying price series, where alternatively each assumption will be violated and every option delta hedging profit and loss analysed. Ultimately we will monitor how the aggressiveness of an option payoff causes its hedging to be more vulnerable to profit and loss variations, caused by the referred assumptions.
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This thesis examines the effects of macroeconomic factors on inflation level and volatility in the Euro Area to improve the accuracy of inflation forecasts with econometric modelling. Inflation aggregates for the EU as well as inflation levels of selected countries are analysed, and the difference between these inflation estimates and forecasts are documented. The research proposes alternative models depending on the focus and the scope of inflation forecasts. I find that models with a Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) in mean process have better explanatory power for inflation variance compared to the regular GARCH models. The significant coefficients are different in EU countries in comparison to the aggregate EU-wide forecast of inflation. The presence of more pronounced GARCH components in certain countries with more stressed economies indicates that inflation volatility in these countries are likely to occur as a result of the stressed economy. In addition, other economies in the Euro Area are found to exhibit a relatively stable variance of inflation over time. Therefore, when analysing EU inflation one have to take into consideration the large differences on country level and focus on those one by one.
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This work project presents a road map for making deals under the umbrella support of a private equity investor. Fundraising, investment analysis, asset monitoring, and divestment are stages in the process that are covered in-depth and clarified in terms of action plan and procedures. Moreover, private equity brings tangible and intangible efficiency to the economy and companies, not only by providing finance to grow and expand but also by forcing superior organizational organics that foster sustainable business positions. In a world domain, Europe as been a second liner as compared to US in terms of size within the private equity sector, but it is quickly maturing and converging to US numbers. In this sense, Portugal has been improving in both numbers and regulations in order to leverage on its strategic location and position itself as a key player to address future business challenges coming from emerging markets such as Africa and Latin America.
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This paper analyses the Portuguese stock market since it reopened in 1977, with a special focus on the evolution of the statistic and stochastic characteristics of the market return throughout this 36 year period. The market return for the period of time between 1977 and 2012 (September 28th) is estimated and then compared with the return that would have been achieved with Government bonds and treasury bills, which allows us to confirm that the hierarchy of return / risk across the different financial instruments is verified. The market risk premium for this 36 year period is also estimated and a comparison with other markets is performed, suggesting that the Portuguese market’s risk has not been compensated by an adequate return. The study also examines the evolution of the Portuguese market’s volatility in the 1977-2012 period and compares it with other markets, showing the existence of extremely high peaks during the first 11 years, but indicating a downwards trend throughout the whole period under analysis. Finally, the correlation between market returns for Portugal and for other countries and the degree of integration are estimated and their evolution throughout time is assessed, leading to the conclusion that the performance of the Portuguese stock market has become increasingly correlated with major European markets – correlation with some markets close to 0.70 from 2000 onwards-, but that country-specific risk factors are still relevant.