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Die vorliegende Arbeit untersucht Risikofaktoren und Risikoprämien in Rohstoffmärkten und beinhaltet vier empirische Studien. Die ersten zwei Studien konzentrieren sich dabei auf Risikoprämien von verbundenen Terminmärkten für Elektrizität in Australien. In der dritten Studie wird ein Modell zur Beschreibung von extremen Preissprüngen bei Strom entwickelt. Die vierte Studie untersucht schließlich Risikoprämien in der Convenience Yield auf Rohstoffmärkten. (Für eine detailliertere Beschreibung der einzelnen Studien wird auf die jeweilige englische Zusammenfassung verwiesen.)

<p>We design algorithms for markets consisting of multiple items, and agents with budget constraints on the maximum amount of money they can afford to spend. This problem can be considered under two broad frameworks. (a) From the standpoint of Auction Theory, the agents valuation functions over the items are private knowledge. Here, a "truthful auction" computes the subset of items received by every agent and her payment, and ensures that no agent can manipulate the scheme to her advantage by misreporting her valuation function. The question is to design a truthful auction whose outcome can be computed in polynomial time. (b) A different, but equally </p><p>important, question is to investigate if and when the market is in "equilibrium", </p><p>meaning that every item is assigned a price, every agent gets her utility-maximizing subset of items under the current prices, and every unallocated item is priced at zero. </p><p>First, we consider the setting of multiple heterogeneous items and present approximation algorithms for revenue-optimal truthful auctions. When the items are homogeneous, we give an efficient algorithm whose outcome defines a truthful and Pareto-optimal auction. Finally, we focus on the notion of "competitive equilibrium", which is a well known solution concept for market clearing. We present efficient algorithms for finding competitive equilibria in markets with budget constrained agents, and show that these equilibria outcomes have strong revenue guarantees.</p> / Dissertation

This paper uses a new measure of volatility based on extreme day return occurrences and examines the relative prevailing volatility among worldwide stock markets during 1997-2009. Using several global stock market indexes of countries categorized as an emerging and developed capital markets are utilized. Additionally this study investigates well known anomalies namely Monday effect and January effect. Further using correlation analysis of co movement and extent of integration highlights the opportunities for international diversification among those markets. Evidences during this time period suggest volatility is not the only phenomena of emerging capital markets. Emerging markets offer opportunities of higher returns during volatility. Cross correlation analysis depicts markets have become more integrated during this time frame; still opportunities for higher returns prevail through global portfolio diversification.

Whether or not currency markets may be regarded as efficient or not has been a hotly debated issue in the academic literature over recent decades. Economic theory would suggest that these markets should be efficient because they are apparently good examples of a perfectly competitive market structure. On the other hand, empirical tests of the efficient market hypothesis within these currency markets unequivocally find them to be inefficient. There is still no good explanation for this conundrum and as a result a fair amount of effort is still expended on refining the empirical studies of market efficiency, a task which is taken up in the four empirical studies that comprise this thesis. Within efficient markets, prices are predicted to respond &quotquickly" with the arrival of new information and the empirical work in the thesis focuses on these issues by identifying three key areas for research, namely, price adjustment and volatility, volatility and the &quotnews", and the speed of price adjustment. In essence, the studies examine whether there is inefficient adjustment to news in terms of excessive volatility, whether or not news is actually the main driver of exchange rate volatility and whether or not &quotquickly" can be measured empirically. The empirical results reported within this thesis confirm that the Australian dollar has not been an excessively volatile currency, even though the level of volatility has been increasing; that the pattern of information flow explains a significant degree of the non constant variance in the returns of the world's most actively traded currencies, (i.e. information explains price innovation); that the reaction time to macroeconomic news occurs within seconds of a pre-scheduled announcement, and that the bulk of adjustment to fundamental value occurs within the hour. These findings are consistent with what would be expected within an efficient market. The results reported within this thesis therefore suggest that the currency markets studied are efficient, at least for the sample periods of the data used in the studies. Exchange rates adjust rapidly with information arrival albeit not completely. It is also the case that a number of additional research questions emerge from this research. For example we know that volatility is not excessive and that it is increasing. What we do not know is the point at which increasing volatility becomes excessive. We know that exchange rates react quickly with the arrival of macroeconomic news, but we do not know precisely how long it takes for volatility to return to preannouncement levels, or why the reaction to news is inconsistent. We also do not know what type of information best explains volatility above that which is explained by the systematic dissemination of information or why full adjustment to fundamental value does not occur? Answers to these questions provide a future research agenda. Answers may provide insight that will help financial economists explain the apparent failure of the speculative efficient hypothesis.

This study gives an insight into the behaviour and performance of large speculators and large hedgers in 29 US futures markets. Using a trading determinant model and priced risk factors such as net positions and sentiment index, results suggest hedgers (speculators) exhibit significant positive feedback trading in 15 (7) markets. Information variables like the S&P500 index dividend yield, corporate yield spread and the three months treasury bill rate were mostly unimportant in large players’ trading decisions. Hedgers had better market timing abilities than speculators in judging the direction of the market in one month. The poor market timing abilities and poor significance of positive feedback results suggest higher trading frequency intervals for speculators. Hedging pressures, which measure the presence of risk premium in futures markets, were insignificant mostly in agricultural markets. As a robust test of hedging pressures, price pressure tests found risk premium to be still significant for silver, crude oil and live cattle. The positive feedback behaviour and negative market timing abilities suggest hedgers in heating oil and Japanese yen destabilize futures prices, and points to a need to check CFTC’s (Commodity Futures Trading Commission) position limits regulation in these markets. In fact, large hedgers in these two markets are more likely to be leading behaviour, in that they have more absolute net positions than speculators. Alternatively stated, positive feedback hedgers in these two markets are more likely to lead institutions and investors to buy (sell) overpriced (underpriced) contracts, eventually leading to divergence of prices away from fundamentals. / Atlhought hedgers in crude oil had significant positive feedback behaviour and negative market timing skills, they would not have much of a destabilizing effect over remaining players because the mean net positions of hedgers and speculators were not far apart. While the results are statistically significant, it is suggested these could be economically significant, in that there have been no regulation on position limits at all for hedgers compared to speculators who are imposed with strict limits from the CFTC. Further, mean equations were regressed against decomposed variables, to see how much of the futures returns are attributed to expected components of variables such as net positions, sentiment and information variables. While the expected components of variables are derived by ensuring there are enough ARMA (autoregressive and moving average) terms to make them statistically and economically reliable, the unexpected components of variables measure the residual on differences of the series from its mean. When decomposing net positions against returns, it was found expected net positions to be negatively related to hedgers’ returns in mostly agricultural markets. Speculators’ expected (unexpected) positions were less (more) significant in explaining actual returns, suggesting hedgers are more prone in setting an expected net position at the start of the trading month to determine actual returns rather than readjusting their net positions frequently all throughout the remaining days of the month. While it important to see how futures returns are determined by expected and unexpected values, it is also essential to see how volatility is affected as well. / In an attempt to cover three broad types of volatility measures, idiosyncratic volatility, GARCH based volatility (variance based), and PARCH based volatility (standard deviation) are used. Net positions of hedgers (expected and unexpected) tend to have less effect on idiosyncratic volatility than speculators that tended to add to volatility, reinforcing that hedgers trading activity hardly affect the volatility in their returns. This suggest they are better informed by having a better control over their risk (volatility) measures. The GARCH model showed more reliance of news of volatility from previous month in speculators’ volatility. Hedgers’ and speculators’ volatility had a tendency to decay over time except for hedgers’ volatility in Treasury bonds and coffee, and gold and S&P500 for speculators’ volatility. The PARCH model exhibited more negative components in explaining current volatility. Only in crude oil, heating oil and wheat (Chicago) were idiosyncratic volatility positively related to return, reinforcing the suggestion for stringent regulation in the heating oil market. Expected idiosyncratic volatility was lower (higher) for hedgers (speculators) as expected under portfolio theory. Markets where variance or standard deviation are smaller than those of speculators support the price insurance theory where hedging enables traders to insure against the risk of price fluctuations. Where variance or standard deviation of hedgers is greater than speculators, this suggest the motivation to use futures contracts not primarily to reduce risk, but by institutional characteristics of the futures exchanges like regulation ensuring liquidity. / Results were also supportive that there was higher fluctuations in currency and financial markets due to the higher number of contracts traded and players present. Further, the four models (GARCH normal, GARCH t, PARCH normal and PARCH t) showed returns were leptokurtic. The PARCH model, under normal distribution, produced the best forecast of one-month return in ten markets. Standard deviation and variance for both hedgers’ and speculators’ results were mixed, explained by a desire to reduce risk or other institutional characteristics like regulation ensuring liquidity. Moreover, idiosyncratic volatility failed to accurately forecast the risk (standard deviation or variance based) that provided a good forecast of one-month return. This supports not only the superiority of ARCH based models over models that assume equally weighted average of past squared residuals, but also the presence of time varying volatility in futures prices time series. The last section of the study involved a stability and events analysis, using recursive estimation methods. The trading determinant model, mean equation model , return and risk model, trading activity model and volatility models were all found to be stable following the effect of major global economic events of the 1990s. Models with risk being proxied as standard deviation showed more structural breaks than where variance was used. Overall, major macroeconomic events didn’t have any significant effect upon the large hedgers’ and speculators’ behaviour and performance over the last decade.

In this thesis I study the investment climate in the four rapidly growing emerging economies Brazil, Russia, India and China (BRIC). The first study, Chapter 2, uses a bivariate EGARCH methodology with time varying conditional correlation to study the global and regional integration of the BRICs and to identify the existence of diversification opportunities for international investors. The second study, Chapter 3, employs a restricted version of the model to explore the relationship between equity market returns and volatility of equity returns in the BRIC countries and global oil prices. Chapter 4 is an extension of Chapter 3, and focuses on the sustainability of Russia???s economic growth in view of its large dependence on oil income. A qualitative analysis of the oil industry in Russia, including an overview of the operations of the largest oil producing companies, government regulations, oil production and proven oil reserves, is conducted for the purpose of this study. The last study, Chapter 5, uses a panel data methodology to explore the determinants of changes in sovereign bond spreads for the BRICs as an asset class and for each of the BRIC countries individually. I conclude that the regional and global level of integration of the BRICs is relatively low, and portfolio investors can enjoy sound diversification benefits particularly by taking investment positions in the Indian and Chinese equity markets. Despite the aggressive economic growth of the BRICs and their increased oil consumption, the volatility of stock returns from the BRICs does not have a significant impact on global oil prices; however, oil prices do impact the volatility of equity returns in India and China, and particularly the level of returns and volatility of equity returns in Russia. Based on this and the qualitative analysis in Chapter 4, it is concluded that in the short to medium term Russia???s continued economic growth will depend on increased reinvestment in the oil industry and in the longer term the government should diversify its revenue sources and focus on development of other sectors within the economy. Lastly, it is concluded that sovereign risk in the BRICs is driven by different global and country-specific factors, hence risk should be observed on an individual country basis and not for the BRICs as an asset class.

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

Thesis (M. Design) (Hons.) -- University of Western Sydney, Nepean, 1999. / Includes bibliographical references.

Diss. Uppsala : Univ., 2003.