In this thesis we examine the effect of foreign exchange interventions in small open economy, focusing on the Czech experience. In the first part we model volatility development before and after the intervention using GARCH model. In the second part we estimate relationship between macroeconomical variables using vector autoregressive model. In this part we estimate impulse response function of exchange rate and inflation. In second part of VAR modeling we provide counterfactual analysis, which compare actual development of variables with alternative scenario in which the interventions would not happen . Our results suggest that the interventions is associated with few months delayed decrease in volatility. Base on scenario analysis the interventions increased inflation by approximately 1.5 % and without the intervention the economy would in deflation around -1 % nowadays. KEYWORDS: Vector autoregression, Volatility modelling, Monetary policy, Intervention Author's e-mail: jantimko16@gmail.com Supervisor's e-mail: tomas.holub@cnb.cz

This paper examines the potential of Bitcoin, a decentralized digital currency, to pose competition to fiat currencies. To accomplish that, Bitcoin would have to become efficient as a store of value. Thus far, high volatility makes it inferior in that respect. We analyze the dynamics and drivers of Bitcoin volatility using GARCH and HAR models. Moreover, we test for presence of asymmetries displayed by stock, commodity and currency markets. That way we can conclude, whether volatility of Bitcoin behaves similarly to currencies, commodities or stocks. Lastly we reveal interconnections between these markets and market for Bitcoin. We find significant evidence for the leverage effect documented for stock market. Furthermore, the effect of trading volume, documented for currency markets, displays an opposite sign in our research. Results of spillover estimation suggest Bitcoin is the most interconnected with commodity market. Thus, we conclude Bitcoin does not behave similarly to currencies in terms of volatility; hence is not a good candidate to substitute them. JEL Classification E1, G1, G2, O3 Keywords Bitcoin, volatility, GARCH, leverage effect Author's e-mail 24805288@fsv.cuni.cz Supervisor's e-mail dedek@fsv.cuni.cz

Thesis (M.M. (Finance & Investment))--University of the Witwatersrand, Faculty of Commerce, Law and Management, Graduate School of Business Administration, 2015. / e period 2000:q1 – 2014:q3 in South Africa. In addition, the paper examines the impact that the exchange rate volatility exerts on the different forms of capital flows. Consequently, the aim of the study is to examine whether the volatility in the exchange rate is a significant determinant of foreign investor capital into South African markets as well as to empirically establish the dynamic relationship that can be observed between capital flows and exchange rate volatility. A trade weighted exchange rate was constructed from which the conditional variance GARCH (1,1) model is applied to estimate exchange rate volatility. The findings from the multiple regression analysis reveal that exchange rate volatility has a statistically significant negative impact on the aggregated capital flows to South Africa. Using the bi-variate vector autoregressions (VARs), the Granger-causality test, impulse response and variance decomposition, the results show there is a dynamic interrelationship between exchange rate volatility and the aggregated and disaggregated capital flows. Furthermore, the VAR specifications results reveal that portfolio flows exhibits a strong bi-directional causality with exchange rate volatility as well as explaining a significant percentage of innovations in exchange rate volatility. This suggests that fluctuations in the exchange rate can be explained by portfolio flows into South Africa’s capital markets. The recommendations for authorities resulting from the findings include, a monetary policy that mitigates the rand exchange rate volatility in an effort to attenuate the adverse subduing effects it has on capital flows in South Africa. Further broadening financial instruments and derivatives available for investors to hedge against exchange rate volatility and a meticulous management of portfolio flows is imperative to ensure prevention of its destabilizing effect on the exchange rate.

This thesis consists of eight studies that cover topics in the increasingly influential field of futures- commodities, macroeconomic volatility and financial development. Chapter 2 considers the case of Argentina and provides a first thorough examination of the timing of the Argentine debacle. By applying a group of econometric tests for structural breaks on a range of GDP growth series over a period from 1886 to 2003 we conclude that there are two key dates in Argentina's economic history (1918 and 1948) that need to be inspected closely in order to further our understanding of the Argentine debacle. Chapters 3 and 4 investigated the time-varying link between financial development and economic growth. By employing the logistic smooth transition framework to annual data for Brazil covering the period 1890-2003 we found that financial development has a mixed (either positive or negative) time- varying effect on growth, which depends on trade openness thresholds. We also find a positive impact of trade openness on growth while a mainly negative one for the various political instability measures. Chapter 5 studied the convergence properties of inflation rates among the countries of the European Monetary Union over the period 1980-2013. By applying recently developed panel unit root/stationarity tests overall we are able to accept the stationarity hypothesis. Similarly, results from the univariate testing procedure indicated a mixed evidence in favour of convergence. Hence next we employ a clustering algorithm in the context of multivariate stationarity tests and we statistically detect three absolute convergence clubs in the pre-euro period, which consist of early accession countries. We also detect two separate clusters of early accession countries in the post-1997 period. For the rest of the countries/cases we find evidence of divergent behaviour. For robustness check we additionally employ a pairwise convergence Bayesian framework, which broadly confirms our findings. Finally, we show that in the presence of volatility spillovers and structural breaks time-varying persistence will be transmitted from the conditional variance to the conditional mean. Chapter 6 focuses on the negative consequences that the five years of austerity (2010-2014) imposed on the Greek economy and the society in general. To achieve that goal we summarize the views of three renowned economists, namely Paul De Grauwe, Paul Krugman and Joseph Stiglitz on the eurozone crisis as well as the Greek case. In support of their claims we provide solid evidence of the dramatic effects that the restrictive policies had on Greece. Chapter 7 analyzes the properties of inflation rates and their volatilities among five European countries over a period 1960-2003. Unlike to previous studies we investigate whether or not the infl ation rate and its volatility of each individual country displayed time-varying characteristics. By applying various power ARCH processes with structural breaks and with or without in-mean effects the results indicated that the conditional means, variances as well as the in-mean effect displayed time-varying behaviour. We also show that for France, Italy and Netherlands the in-mean effect is positive, whereas that of Austria and Denmark is negative. Chapter 8 examines the stochastic properties of different commodity time series during the recent fi nancial and EU sovereign debt crisis (1997-2013). By employing the Bai-Perron method we detect five breaks for each of the commodity returns (both in the mean and in the variance). The majority of the breaks are closely associated with the two aforementioned crises. Having obtained the breaks we estimated the power ARCH models for each commodity allowing the conditional means and variances to switch across the breakpoints. The results indicate overall that there is a time-varying behaviour of the conditional mean and variance parameters in the case of grains, energies and softs. In contrast, metals and soya complex show time-varying characteristics only in the conditional variance. Finally, conducting a forecasting analysis using spectral techniques (in both mapped and unmapped data) we find that the prices of corn remained almost stable while for wheat, heating oil, wti and orange juice the prices decreased further, though slightly. In the case of natural gas, coffee and sugar overall the prices experienced significant defl ationary pressures. As far as the prices of oats, platinum, rbob, cocoa, soybean, soymeal and soyoil is concerned, they showed an upward trend. Chapter 9 examines the effect of health and military expenditures, trade openness and political instability on output growth. By employing a pooled generalised least squares method for 19 NATO countries from 1993 to 2010 we fi nd that there is a negative impact of health and military expenditures, and political instability on economic growth whereas that of trade openness is positive.

We study the half-hourly electricity generation by coal and by gas in the UK over a period of three years from 2012 to 2014. As a highly frequent time series, daily cycles along with seasonality and trend across days can be seen in the data for each fuel. Taylor (2003), Taylor et al. (2006), and Taylor (2008) studied time series of the similar features by introducing double seasonality into the methods for a single univariate time series. As we are interested in the continuous variation in the generation within a day, the half-hourly observations within a day are considered as a continuous function. In this way, a time series of half-hourly discrete observations is transformed into a time series of daily functions. The idea of a time series of functions can also seen in Shang (2013), Shang and Hyndman (2011) and Hyndman and Ullah (2007). We improve their methods in a few ways. Firstly, we identify the systematic effect due to the factors that take effect in a long term, such as weather and prices of fuels, and the intrinsic differences between the days of the week. The systematic effect is modeled and removed before we study the day-by-day random variation in the functions. Secondly, we extend functional principal component analysis (PCA), which was applied on one group of functions in Shang (2013), Shang and Hyndman (2011) and Hyndman and Ullah (2007), into partial common PCA, in order to consider the covariance structures of two groups of functions and their similarities. A test on the goodness of the approximation to the functions given by the common eigenfunctions is also proposed. The idea of bootstrapping residuals from the approximation seen in Shang (2014) is employed but is improved with non-overlapping blocks and moving blocks of residuals. Thirdly, we use a vector autoregressive (VAR) model, which is a multivariate approach, to model the scores on common eigenfunctions of a group such that the cross-correlation between the scores can be considered. We include Lasso penalties in the VAR model to select the significant covariates and refit the selection with ordinary least squares to reduce the bias. Our method is compared with the stepwise procedure by Pfaff (2007), and is proved to be less variable and more accurate on estimation and prediction. Finally, we propose the method to give the point forecasts of the daily functions. It is more complicated than the methods of Shang (2013), Shang and Hyndman (2011) and Hyndman and Ullah (2007) as the systematic effect needs to be included. An adjustment interval is also given along with a point forecast, which represents the range within which the true function might vary. Our methods to give the point forecast and the adjustment interval include the information updating after the training period, which is not considered in the classical predicting equations of VAR and GARCH seen in Tsay (2013) and Engle and Bollerslev (1986).

The dynamic conditional correlation (DCC) model and its variants have been widely used in modeling the volatility of multivariate time series, with applications in portfolio construction and risk management. While popular for its simplicity, the DCC uses only two parameters to model the correlation dynamics, regardless of the number of assets. The flexible dynamic conditional correlation (FDCC) model attempts to remedy this by grouping the stocks into various clusters, each with its own set of parameters. However, it assumes the grouping is known apriori. In this thesis we develop a systematic method to determine the number of groups to use as well as how to allocate the assets to groups. We show through simulation that the method does well in identifying the groups, and apply the method to real data, showing its performance. We also develop and apply a Bayesian approach to this same problem. Furthermore, we propose an instantaneous measure of correlation that can be used in many volatility models, and in fact show that it outperforms the popular sample Pearson's correlation coefficient for small sample sizes, thus opening the door to applications in fields other than finance.

<p>The purpose of this paper is to investigate the impact of the EMU on the long-run covariance between the member countries stock indices returns, to see whether country diversification opportunities have changed or not. The degree to which investors are able to reduce risk by diversifying their portfolio depends on the correlation between assets. Investors should dislike an increase in correlation between returns. Therefore it is of great interest to investigate whether the covariance between the EMU countries has increased or not. I use GARCH (1.1) covariance model for estimation, with the extension that I allow the slope to differ in the regression equation. A dummy variable is included to find any regime shift in the data. The exchange rate of the EMU countries were fixed in January 1999 and therefore the dummy takes the value one from 1999-2004 and zero otherwise. I find that the long-run covariance in EMU area has increased making it less attractive to diversify portfolios within the area. The covariance’s between countries where the control countries is included (Sweden and Switzerland) has also been affected of the euro introduction. But still I find evidence of a high integrated market even before the euro introduction, indicating that EU, rather than EMU, has had the greatest impact on member countries markets. Maybe the higher level of integration also is due to trade linkage between the countries resulting from EU and EMU.</p>

<p>Denna uppsats ämnar undersöka hur volatilitetstransmissionen mellan sex aktiemarknader i</p><p>världen ser ut och att utreda vilka aktiemarknader som har mest inflytande över den svenska</p><p>börsens volatilitet. Uppsatsen syftar även till att utforska om graden av volatilitetsspridning</p><p>ökat sedan IT-kraschen. Vid utförandet av denna studie används en ekonometrisk tvåstegsmodell</p><p>inkluderande GARCH och VAR. Resultaten pekar på att det sprids volatilitet</p><p>mellan aktiemarknaderna och att utländska innovationer står för en långvarig påverkan på den</p><p>inhemska volatiliteten. Undersökningen visar att svenska börsen är den aktiemarknad som</p><p>påverkas mest av utländska chocker och att den inte har någon nämnvärd påverkan på de</p><p>andra aktiemarknaderna. Vidare påvisar resultaten att IT-kraschen lett till att utländska</p><p>innovationer fått en större betydelse i Sverige liksom att den svenska börsens volatilitet blivit</p><p>mer beroende av Nasdaqs.</p>

<p>Enligt teorin om öppen ränteparitet (UIP) ska den förväntade nominella växelkursförändringen motsvara räntedifferensen mellan två länder. I själva verket visar de flesta studier att teorin inte håller och att det förekommer ett signifikant negativt samband mellan variablerna istället för det positiva sambandet som följer av teorin (Froot&Thaler 1990, McCallum 1994). Även i denna uppsats konstateras ett negativt samband, vilket innebär att UIP kan förkastas för Sverige och USA under perioden 1994:1-2006:2. En amerikansk investerare som köper svenska statsskuldväxlar får således förutom en högre ränta även avkastning i form av en apprecierande växelkurs. I uppsatsen undersöks om avvikelsen från teorin kan förklaras utifrån förekomsten av en riskpremie för det mindre landet Sverige. Genom att använda den statistiska metoden GARCH-M kan det konstateras att växelkursens avkastning påverkas av dess volatilitet och således har effekt på avvikelsen från UIP. Tecknet för sambandet är dock felaktigt utifrån definitionen av en riskpremie. Det kan dock konstateras att det förekommer en riskpremie för Sverige som påverkas av inflationsdifferensen och statsskuldsdifferensen mellan länderna.</p>

The purpose of this paper is to investigate the impact of the EMU on the long-run covariance between the member countries stock indices returns, to see whether country diversification opportunities have changed or not. The degree to which investors are able to reduce risk by diversifying their portfolio depends on the correlation between assets. Investors should dislike an increase in correlation between returns. Therefore it is of great interest to investigate whether the covariance between the EMU countries has increased or not. I use GARCH (1.1) covariance model for estimation, with the extension that I allow the slope to differ in the regression equation. A dummy variable is included to find any regime shift in the data. The exchange rate of the EMU countries were fixed in January 1999 and therefore the dummy takes the value one from 1999-2004 and zero otherwise. I find that the long-run covariance in EMU area has increased making it less attractive to diversify portfolios within the area. The covariance’s between countries where the control countries is included (Sweden and Switzerland) has also been affected of the euro introduction. But still I find evidence of a high integrated market even before the euro introduction, indicating that EU, rather than EMU, has had the greatest impact on member countries markets. Maybe the higher level of integration also is due to trade linkage between the countries resulting from EU and EMU.