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In practice, we often meet data in the form of observations of several variables at various points in time. These data are called time series. We present various approaches in time series analysis; graphical models, vector autoregres- sive models and vector moving-average models. We try to get information about mutual relationship of the variables and then to model their behavior. The used techniques are illustrated on log returns of monthly average exchange rates. The programs are processed in the software Mathematica 7 and can be found on the CD. 1

<p>This paper evaluates if international stock markets are exposed to fluctuation in the</p><p>exchange rate and whether this exposure is related to exports, imports and inflation. Eight</p><p>countries are studied: Australia, Belgium, Brazil, Hong Kong, Sweden, Switzerland, the</p><p>United Kingdom and the United States. The empirical investigation covers the period</p><p>from 1995 to 2004 and the estimation is conducted using the framework of Patro, D.K.,</p><p>Wald, J.K. and Wu, Y. (2002). The empirical findings show that all international stock</p><p>markets are exposed to exchange rate risk, except for Brazil. The amount of exchange rate</p><p>exposure is found to be sensitive to a country’s export, import and inflation. The results</p><p>imply that there are predictable relationship between changes in the return of the national</p><p>stock index return and fluctuation in the exchange rate. In addition, imports and exports</p><p>as well as inflation may be useful in predicting exchange rate risks.</p>

This paper evaluates if international stock markets are exposed to fluctuation in the exchange rate and whether this exposure is related to exports, imports and inflation. Eight countries are studied: Australia, Belgium, Brazil, Hong Kong, Sweden, Switzerland, the United Kingdom and the United States. The empirical investigation covers the period from 1995 to 2004 and the estimation is conducted using the framework of Patro, D.K., Wald, J.K. and Wu, Y. (2002). The empirical findings show that all international stock markets are exposed to exchange rate risk, except for Brazil. The amount of exchange rate exposure is found to be sensitive to a country’s export, import and inflation. The results imply that there are predictable relationship between changes in the return of the national stock index return and fluctuation in the exchange rate. In addition, imports and exports as well as inflation may be useful in predicting exchange rate risks.

This thesis analyses financial stability in eight members of the Executives’ Meeting of East Asia-Pacific Central Banks (EMEAP) economies. One of the factors that may increase financial imbalances (and hence it affects financial stability of an economy) is the accumulated outstanding debt of the economic agents. For example, the corporate sector’s outstanding debt can negatively affect activity of lenders and hence the capabilities of the economy. Since banks are important financial intermediaries in most financial systems, the financial status of banking sector is also important to analyse financial stability of a country. Macroeconomic conditions and financial system structure are some of the important factors that can affect financial conditions (financial soundness) of banks and hence the banking sector. Financial soundness of banks can secure the stability of the financial system. Chapter 2 shows that financial imbalances that arise from accumulated outstanding debt within the corporate sector have a negative effect on the technical capabilities (total factor productivity) of the economy. Therefore, monetary authority (central bank) should control over the debt level. To address this, chapter 2 focuses on the design of monetary policy rule for a small open economy in the context of a Dynamic Stochastic General Equilibrium (DSGE) model. This model is extended to show the effects of financial imbalances on the economy. Real exchange rate is another important factor that affects the firm’s real marginal cost, aggregate supply and aggregate demand as discussed in this chapter. The derived optimal monetary policy rule indicates that the monetary authority responds to financial imbalances through output gap when financial imbalances exist due to accumulated outstanding debt. Moreover, the optimal policy rule shows that the response of the monetary authority to exchange rate movements is indirect, through the domestic inflation and output gap. Chapter 3 describes the effect of the financial system structure on financial stability through investigating the financial soundness of the banking sector. Bank financial soundness is the measure of the stability of the financial system and is defined by return on assets, equity capital-asset ratio and return volatility. The first two items increase financial soundness, whereas return volatility decreases financial soundness of a bank. The structure of the financial system is described as market-based or bank-based. Given interrelations between financial sectors and between economies of the EMEAP countries, chapter 3 uses the global (infinite dimensional) vector autoregressive (VAR) model that has been proposed recently to estimate the generalised impulse responses of financial stability measure. Results show that the market-based financial system can increase financial stability through increasing financial soundness of the banking system. Chapter 4 uses nonperforming loans (NPLs) (as one of the main factors behind Asian financial crisis in 1997/8) to analyse financial soundness of banks. NPLs determine loans default rates that decreases banks’ financial soundness. Chapter 4 tests the resistance of the banking system of the EMEAP countries to large macroeconomic shocks (stresses) in a stress-test framework, computing frequency distributions of default rates in three main macroeconomic scenarios (baseline model, stressed real GDP growth and stressed real interest rate). Default rate indicates the possible loss of banks and hence it is an indicator of credit risk which weakens banks’ financial strength. The stress-test indicates that stressing real GDP growth with negative extreme shocks leads to an increase in frequency of higher default rates (in comparison with the baseline model), whereas positive shock to real interest rate may secure financial stability through increasing the frequency of lower default rates and decreasing frequency of higher default rate.

For many years, incompatible computer-aided design (CAD) packages that are based on Non-uniform Rational B-Spline (NURBS) technology carried out the exchange of models and data through either neutral file formats (IGES or STEP) or proprietary formats that have been accepted as quasi industry standards. Although it is the only available solution at the current time, the exchange process most often produces unsatisfactory results. Models that are impeccable in the original modeling system usually end up with gaps or intersections between surfaces on another incompatible system. Issues such as loss of information, change of data accuracy, inconsistent tolerance, and misinterpretation of the original design intent are a few examples of problems associated with migrating models between different CAD systems. While these issues and drawbacks are well known and cost the industry billions of dollars every year, a solution to eradicate problems from their sources has not been developed. Meanwhile, researchers along with the industries concerned with these issues have been trying to resolve such problems by finding means to repair the migrated models either manually or by using specialized software. Designing in recent years is becoming more knowledge intensive and it is essential for NURBS to take its share of the ever increasing use of knowledge. NURBS are very powerful modeling tools and have become the de facto standard in modeling. If we stretch their strength and make them knowledge driven, benefits beyond current expectations can be achieved easily. This dissertation introduces knowledge guided NURBS with theoretical and practical foundations for supporting design intent capturing, retrieval, and exchange among dissimilar CAD systems. It shows that if NURBS entities are tagged with some knowledge, we can achieve seamless data exchange, increase robustness, and have more reliable computations, all of which are ultimate objectives many researchers in the field of CAD have been trying to accomplish for decades. Establishing relationships between a NURBS entity and its origin and destinations can aid with seamless CAD model migration. The type of the NURBS entity and the awareness of any irregularities can lead to more intelligent decisions on how to proceed with many computations to increase robustness and achieve a high level of reliability. As a result, instead of having models that are hardly modifiable because of migrating raw numerical data in isolation, the knowledge driven migration process will produce models that are editable and preserve design intent. We have addressed the issues not only theoretically but also by developing a prototype system that can serve as a test bed. The developed system shows that a click of a button can regenerate a migrated model instead of repairing it, avoiding delay and corrective processes that only limit the effective use of such models.

Exchange rate forecasting is hard issue for most of floating exchange rate economies. Studying exchange rate is very attractive matter since almost no model could beat random walk in short run yet. Relative yields and information in relative yield curves are contemporary topics in empirical literature and this study follows Chen and Tsang (2009) who model exchange rate changes with relative factors obtained from Nelson-Siegel (1987) yield curve model and find that relative factor model can forecast exchange rate change up to 2 years and perform better than random walk in short run. Analysis follows the methodology defined by Chen and Tsang (2009) and TL/USD, TL/EUR exchange rate changes are modeled by the relative factors namely relative level, relative slope and relative curvature. Basically, 162 weekly datasets from 09.01.2007 to 16.03.2010 are used and the relative factors for each week are estimated. Afterwards, regression analysis is made and results show that relative level and relative curvature factors are significant up to 4-6 weeks horizon but relative slope does not provide any valuable information for exchange rate prediction in Turkish financial market. Length of forecasting horizon of relative factor model is too short when compared to other exchange rate models. Since it is accepted that exchange rates follow random walk, we provided some tests to compare performance of the model. Similar to the literature, only short run performance of relative factor model is compared to random walk model and concluded that the relative factor model does not provide better forecasting performance in Turkish financial market

Bayesian inference for stochastic volatility models using MCMC methods highly depends on actual parameter values in terms of sampling efficiency. While draws from the posterior utilizing the standard centered parameterization break down when the volatility of volatility parameter in the latent state equation is small, non-centered versions of the model show deficiencies for highly persistent latent variable series. The novel approach of ancillarity-sufficiency interweaving has recently been shown to aid in overcoming these issues for a broad class of multilevel models. In this paper, we demonstrate how such an interweaving strategy can be applied to stochastic volatility models in order to greatly improve sampling efficiency for all parameters and throughout the entire parameter range. Moreover, this method of "combining best of different worlds" allows for inference for parameter constellations that have previously been infeasible to estimate without the need to select a particular parameterization beforehand. / Series: Research Report Series / Department of Statistics and Mathematics

This thesis solves the use of Modelica models in Matlab/Simulink enviroment. The first part is focused on Modelica language and Functional Mock-up Interface, a standard way for model exchange and co-simulation of dynamic models, which is supported by most Modelica oriented tools. Based on this standard FMUtoolbox was created and it provides the ability to import and simulate models exported as Functional Mock-up Unit. The tool provides a Simulink block, graphical and command-line interface.