Volatility is an important variable in financial markets, risk management and making investment decisions. Different volatility models are beneficial tools to use when predicting future volatility. The purpose of this study is to compare the accuracy of various volatility models, including ARCH, GARCH and extensions of the GARCH framework. The study applies these volatility models to the Swedish and American Fixed Income Market for government bonds. The performance of these models is based on out-of-sample forecasting using different loss functions such as RMSE, MAE and MSE, specifically investigating their ability to forecast future volatility. Daily volatility forecasts from daily bid prices from Swedish and American 2, 5- and 10-year governments bonds will be compared against realized volatility which will act as the proxy for volatility. The result show US government bonds, excluding the US 2 YTM, did not show any significant negative volatility, volatility asymmetry or leverage effects. In overall, the ARCH and GARCH models outperformed E-GARCH and GJR-GARCH except the US 2-year YTM showing negative volatility, asymmetry, and leverage effects and the GJR-GARCH model outperforming the ARCH and GARCH models. / Volatilitet är en viktig variabel på finansmarknaden när det kommer till både riskhantering samt investeringsbeslut. Olika volatilitets modeller är fördelaktiga verktyg när det kommer till att göra prognoser av framtida volatilitet. Syftet med denna studie är att jämföra det olika volatilitetsmodellerna ARCH, GARCH och förlängningar av GARCH-ramverket för att ta reda på vilken av modellerna är den bästa att prognosera framtida volatilitet. Studien kommer tillämpa dessa modeller på den svenska och amerikanska marknaden för statsskuldväxlar. Prestandan för modellerna kommer baseras på out-of-sample prognoser med hjälp av det olika förlustfunktionerna RMSE, MAE och MSE. Förlustfunktionernas används endast till att undersöka deras förmåga till att prognostisera framtida volatilitet. Dagliga volatilitetsprognoser baseras på dagliga budpriser för amerikanska och svenska statsobligationer med 2, 5 och 10 års löptid. Dessa kommer jämföras med verklig volatilitet som agerar som Proxy för volatiliteten. Resultatet tyder på att amerikanska statsobligationer förutom den tvååriga, inte visar signifikant negativ volatilitet, asymmetri i volatilitet samt hävstångseffekt. De tvååriga amerikanska statsobligationerna visar bevis för negativ volatilitet, hävstångseffekt samt asymmetri i volatiliteten. ARCH och GARCH modellerna presterade övergripande sett bäst för både svenska och amerikanska statsobligationer förutom den tvååriga där GJR-GARCH modellen presterade bäst.

Volatility managing strategies have gained attention over the last few years due to theiralleged ability to increase portfolio return and mitigate risk. This thesis examines the performance and risk of a portfolio using such a strategy on the Swedish equity market. The strategy is dependent on the forecasting of volatility. Different volatility forecasting models are evaluated using different refitting intervals. The GARCH(1,1) model using a monthly refitting interval is found to be the most precise. When comparing it to the buy-and-hold portfolio, the results of the risk and return of the portfolio are ambiguous and the volatility managing strategy is only found to be beneficial when using a fixed volatility target when transaction costs are accounted for. Regarding distributional characteristics, the volatility managing strategy displays features of a lighter-tailed distribution in comparison to the buy-and-hold portfolio when using a dynamic volatility target. However, for the fixed target, the distributional characteristics are incoherent. Lastly, the volatility managing strategy is not found beneficial to the investor during a shorter period of high volatility. This thesis provides support for using a volatility managing strategy with a fixed volatility target for generating a higher return compared to the benchmark. However, it does not support conclusive evidence for obtaining a higher return without increasing the risk level of the investment. / Användningen av volatilitetshanterande strategier har fått ökad uppmärksamhet under de senaste åren. Därför undersöker detta arbete avkastningen och risken hos en portfölj som använder en sådan strategi på den svenska aktiemarknaden. Investeringsstrategin är baserad på prognosen av volatilitet. Olika modeller för volatilitetsprediktion utvärderas för olika tidsintervall för att hitta modellen med högst precision. Denna studie finner att en GARCH(1,1) modell som omanpassar sig månadsvis resulterar i den mest exakta prediktionen. Med hänsyn till risk och avkastning så är resultaten för volatilitetsstrategin tvetydiga i jämförelse med en köp-och-behåll strategi. Volatilitetsstrategin är endast fördelaktig när ett fast volatilitetsmål används då transaktionskostnader inkorporeras. Med avseende på fördelningsegenskaper, så visar en volatilitetsstrategi med ett rörligt volatilitetsmål på egenskaper hos en fördelning med lättare svansar, i jämförelse med köp-och-behåll portföljen. För det fasta volatilitetsmålet så är fördelningsegenskaperna inkoherenta. Volatilitetsstrategin är inte fördelaktig för investeraren under en kortare period med hög volatilitet. Detta examensarbete ger underlag för användandet av en volatilitetshanterande strategi med ett fast volatilitetsmål för att uppnå en högre avkastning i relation till referensportföljen. Det bevisar dock inte att en högre avkastning går att uppnå utan att öka risken hos portföljen.

This research investigates to what extent the ARCH model and the GARCH model forecasts one-day-ahead out-of-sample daily volatility (conditional variance) in European AT1 CoCo bonds compared to the Random Walk model. The research also investigates how different orders of ARCH and GARCH models affect the forecasting accuracy. Specifically, the models investigated are the Random Walk model, ARCH(1), ARCH(2), ARCH(3), GARCH(1,1), GARCH(1,2), GARCH(2,1), and the GARCH(2,2)model. The data set used in this report is 47 European AT1 CoCo bonds from 20 different issuers.The results show that 42 out of 47 CoCo bonds have daily log returns that are conditional heteroscedastic. Five CoCo bonds with homoscedastic daily log returns were CoCo bonds with significant low liquidity. The results show that the GARCH model outperforms both the Random Walk model and the ARCH model, under the assumption that the innovations follow a normal distribution. The results also show that a higherorder of ARCH or GARCH does not necessarily lead to more accurate forecasts. The GARCH(1,1) model provided the most accurate predictions. The conclusion is that the GARCH models provide accurate volatility forecasts in CoCo bonds compared to the ARCH-model, and the Random Walk model. However, the ARCH model and the GARCH model fail to forecast the daily volatility in CoCo bondswith insufficient liquidity. Furthermore, a higher order of ARCH or GARCH models does not necessarily lead to better forecast results. / Denna uppsats undersöker till vilken utsträckning som ARCH och GARCH-modeller kan prediktera daglig volatilitet i AT1 CoCo-obligationer (eng. Additional Tier-1 Contingent Convertible Bonds), jämfört med Random Walk-modellen. Uppsatsen undersöker även hur olika parametrar I ARCH och GARCH-modeller påverkar resultatet i prediktionerna. De modeller som undersöks är Random Walk-modellen, ARCH(1), ARCH(2), ARCH(3), GARCH(1,1), GARCH(1,2), GARCH(2,1), och GARCH(2,2)-modellen. Datasetet som har använts i denna forskning består av 47 Europeiska AT1 CoCo obligationer från 20 olika emittenter. Resultatet visar att 42 av 47 CoCo-obligationer har betingat heteroskedastisk daglig avkastningsdata. Fem CoCo-obligationer med homoskedastisk avkastningsdata är obligationer med signifikant låg likviditet. Vidare visar resultatet visar att GARCH modellen överpresterar jämfört med både Random Walk-modellen och ARCH-modellen, under antagandet att innovationstermen följer en normal distribution. Resultatet visar även att en högre ordning av ARCH eller GARCH inte nödvändigtvis leder till ett bättre resultat i prediktonerna. GARCH(1,1)-modellen är modellen som predikterar den dagliga volatiliten i CoCo-obligationerna med bäst resultat. Slutsatsen är att GARCH-modellen predikterar volatiliteten i CoCo-obligationer bättre jämfört med ARCH-modellen och Random Walk-modellen. Däremot kan inte ARCH-modellen eller GARCH-modellen modellera CoCo-obligationer med signifikant låg likviditet. Vidare så medför en högre ordning i ARCH eller GARCH-modellen inte nödvändigtvis till bättre prediktioner.

South Africa has become more dependent on portfolio inflow to finance investment and consumption due to the low rate of government and household savings. Therefore, it is important from South Africa‟s perspective to maintain a stable portfolio inflow in order to ensure that the current account deficit does not reach unsustainable levels. However, portfolio inflow is anything but stable in South Africa. The risk associated with this is that when foreigners‟ expectations of South Africa shift, due to any form of instability or risk within the country or even internationally, it leads to massive withdrawals or outflow of funds, which in turn causes the currency to depreciate. The portfolio balance theory on the other hand states that an increase in portfolio inflow leads to the appreciation of the nominal exchange rate, and that this is perceived to work against economic growth. The main objective of this research is to determine the nature of the relationship between exchange rate volatility and portfolio flows, and the extent to which volatility in the exchange rate affect South Africa‟s portfolio inflow. The research uses Vector Autoregressive (VAR) models and quarterly data, ranging from 1995 to 2012 to investigate this relationship. From the VAR models a Granger causality test, as well impulse response functions is used to shed light on the influence of a one-unit shock in both foreign portfolio inflow and exchange rate volatility on the other variables in the model. Exchange rate volatility is measured using both Autoregressive Conditional Heteroscedasticity (ARCH) family models and the conventional standard deviation, in order to control for possible biasness caused by the choice of instrument of volatility. The results showed the nature of the relationship between exchange rate volatility and foreign portfolio inflow to South Africa‟s capital markets can be described as country-dependent and time-varying. South Africa‟s portfolio inflow exhibits high volatility and low persistence that are characteristics normally associated with “hot money”, which is largely driven by foreign investors‟ appetite for short-term speculative gains. The study identified the consistent presence of bidirectional causality between the exchange rate volatility and foreign portfolio inflow to South Africa, irrespective of the measurement of exchange rate volatility. The results also revealed that net portfolio flows are associated with exchange rate appreciation and that foreign portfolio inflow react much stronger to changes in exchange rate volatility than vice versa. / MCom (Risk Management), North-West University, Potchefstroom Campus, 2015

South Africa has become more dependent on portfolio inflow to finance investment and consumption due to the low rate of government and household savings. Therefore, it is important from South Africa‟s perspective to maintain a stable portfolio inflow in order to ensure that the current account deficit does not reach unsustainable levels. However, portfolio inflow is anything but stable in South Africa. The risk associated with this is that when foreigners‟ expectations of South Africa shift, due to any form of instability or risk within the country or even internationally, it leads to massive withdrawals or outflow of funds, which in turn causes the currency to depreciate. The portfolio balance theory on the other hand states that an increase in portfolio inflow leads to the appreciation of the nominal exchange rate, and that this is perceived to work against economic growth. The main objective of this research is to determine the nature of the relationship between exchange rate volatility and portfolio flows, and the extent to which volatility in the exchange rate affect South Africa‟s portfolio inflow. The research uses Vector Autoregressive (VAR) models and quarterly data, ranging from 1995 to 2012 to investigate this relationship. From the VAR models a Granger causality test, as well impulse response functions is used to shed light on the influence of a one-unit shock in both foreign portfolio inflow and exchange rate volatility on the other variables in the model. Exchange rate volatility is measured using both Autoregressive Conditional Heteroscedasticity (ARCH) family models and the conventional standard deviation, in order to control for possible biasness caused by the choice of instrument of volatility. The results showed the nature of the relationship between exchange rate volatility and foreign portfolio inflow to South Africa‟s capital markets can be described as country-dependent and time-varying. South Africa‟s portfolio inflow exhibits high volatility and low persistence that are characteristics normally associated with “hot money”, which is largely driven by foreign investors‟ appetite for short-term speculative gains. The study identified the consistent presence of bidirectional causality between the exchange rate volatility and foreign portfolio inflow to South Africa, irrespective of the measurement of exchange rate volatility. The results also revealed that net portfolio flows are associated with exchange rate appreciation and that foreign portfolio inflow react much stronger to changes in exchange rate volatility than vice versa. / MCom (Risk Management), North-West University, Potchefstroom Campus, 2015

What are the main macroeconomic factors that help understand economic growth in Brazil since 1870? Are institutions (and changes in institutions) a deep cause of economic growth in Brazil? Are these effects fundamentally and systematically different? Does the intensity and the direction (the sign) of these effects vary over time, in general and, in particular, do they vary with respect to short- versus long-run considerations? This thesis tries to answer these questions focusing on within country over long periods of time. It uses the power-ARCH (PARCH) econometric framework with annual time series from 1870 to 2003. The results suggest that financial development (domestic and international) exhibit the most robust first-order effects on growth and its volatility. Political instability, trade openness and public deficit play important yet secondary roles since the effects of the first two do not extent to the long-run (that is, they are restricted to the short-run) and those off the latter are sensitive to the measures of the variables used in our analysis.

This thesis deals with various issues regarding determinants of US corporate credit spreads. These spreads are estimated as the difference between yields to maturity for corporate bonds and default-free instruments (Treasury bonds) of the same maturity. Corporate credit spreads are considered as measures of default risk. However, the premium required by investors for holding risky rather than risk-free bonds will incorporate a compensation not only for the default risk but also for other factors related to corporate bonds such as market liquidity or tax differential between corporate and Treasury bonds. In this study we firstly examine the relationship between bond ratings and credit spreads given that bond rating changes are expected to carry some informational value for debt investors. The findings indicate that bond ratings generally carry some informational value for corporate bond investors. The Granger causal relationship is more evident for negative watch lists and during periods of uncertainty in financial markets. In line with previous studies, our results suggest that changes in credit spreads are significantly related to interest rate levels, systematic risk factors (Fama and French) factors and equity returns.

An arched structure provides an effective load carrying system for large span structures. When it comes to long span roof structures, timber arches are one of the best solutions from both structural and aesthetical point of view. Glulam arched structures are often designed using slender elements due to economic consideration. Such slender cross-section shape increases the risk of instability. Instability analysis of straight members such as beam and column are explicitly defined in Eurocode. However, for instability of curved members no analytical approach is provided in the code, thus some numerical method is required. Nonetheless, an approximation is frequently used to obtain the effective buckling length for the arched structures in the plane of arches. In this master thesis a linear buckling analysis is carried out in Abaqus to obtain an optimal effective buckling length both in-plane and out-of-plane for circular glulam arched structures. The elastic springs are used to simulate the overall stiffness of the bracing system. The results obtained by the FE simulations are compared with a simple approximation method. Besides, the forces acting on the bracings system is obtained based on 3D geometric nonlinear stress analysis of the timber trusses. Our findings conclude that the approximation method overestimates the effective buckling length for the circular glulam arched structures. In addition, the study indicates that the position of the lateral supports along the length of the arch is an important design aspect for buckling behaviour of the arched structures. Moreover, in order to acquire an effective structure lateral supports are needed both in extrados and intrados. Furthermore, instead of using elastic spring elements to simulate the overall stiffness of the bracing system, a full 3D simulation of two parallel arches was performed. It was shown that the springs are stronger than the real bracing system for the studied arch.

Σκοπός της παρούσας μελέτης είναι να εξετάσουμε την σχέση που υπάρχει μεταξύ της χρηματιστηριακής αγοράς και αυτής των αποδόσεων των ομολόγων σε τέσσερις χώρες της Ευρωπαϊκής Ένωσης (Γερμανίας, Ιταλίας, Ισπανίας και Γαλλίας) για την περίοδο από τον Δεκέμβριο 1999 έως τον Δεκέμβριο του 2012. Προσπαθήσαμε να εξετάσουμε το κατά πόσο υπάρχουν συσχετίσεις μεταξύ των δύο περιουσιακών στοιχείων σε μεγάλο χρονικό διάστημα χρησιμοποιώντας πολυμεταβλητά μοντέλα. Τα δεδομένα που πήραμε είναι οι ημερήσιες αποδόσεις των 10ετών ομολόγων και τα κλεισίματα των χρηματιστηριακών αγορών των χωρών αυτών για κάθε μία ξεχωριστά. Ξεκινάμε την ερευνά μας χρησιμοποιώντας το μοντέλο του GARCH του Bollerslev (1990). Τέλος μέσω της συνολοκλήρωσης με την διαδικασία του Johansen test θα εξετάσουμε το κατά πόσο οι σειρές μας ολοκληρώνονται μακροχρόνια επηρεάζοντας η μία την άλλη καθώς και την μεταξύ τους εξάρτηση και την αιτιότητα των εν λόγω σχέσεων. Η εργασίας μας έχει ως στόχο να μας δείξει το κατά πόσο υπάρχει μακροχρόνια συσχέτιση μεταξύ των δύο αυτών αγορών, ώστε να βοηθά τους διαχειριστές και οικονομικούς αναλυτές να δημιουργούν το χαρτοφυλάκιο με το μικρότερο κίνδυνο και την μεγαλύτερη απόδοση. Τα αποτελέσματα μας δείχνουν μία μακροχρόνια συσχέτιση μεταξύ αυτών των δύο αγορών και ότι η μία αγορά επηρεάζει την άλλη σε βάθος χρόνου, οπότε είναι χρήσιμο σε ένα χαρτοφυλάκιο να υπάρχουν και τα δύο περιουσιακά στοιχεία. / The purpose of this study is to look at the relationship between stock market and bond market in four European Countries (Germany, France, Spain and Italy) for the period of December 1999 to December 2012. We attempt to examine whether the correlations between two classes of assets are time varying by using multivariate conditional volatility models. The data we are daily yields on 10-year bonds and the closures of the stock markets of these countries for each one individually. We start our investigation by applying GARCH model of Bollerslev (1990). Finally, through co integration with the process of Johansen test will look at whether our series completed long influencing each other and their mutual dependence and causality of these relations. Our paper aims to show us whether there is a long correlation between these two markets in order to help managers and financial analysts to create a portfolio with less risk and greater efficiency. Our results show a long-term correlation between these two markets and one market affects the other in the long run, so it is useful to have a portfolio of both assets.

published_or_final_version / Dentistry / Master / Master of Dental Surgery