[pt] O objetivo deste trabalho é analisar a eficiência na precificação de três dos Exchange-Traded Funds brasileiros mais líquidos (BOVA11, SMAL11 e PIBB11), buscando determinar se eles seguem com bastante proximidade os índices que procuram replicar, comparando com o que é observado na literatura internacional no que diz respeito ao desempenho de ETFs estrangeiros. Inicialmente verificou-se a estratégia de replicação adotada, bem como a qualidade dessa replicação a partir da avaliação do tracking error observado nesses fundos. Em seguida buscou-se avaliar se há algum desvio na precificação entre o preço de negociação e o valor patrimonial líquido (NAV) do respectivo ETF, ou seja, se o ativo está sendo negociado, na média, com prêmio ou desconto. Por fim, foi analisada a persistência dos prêmios ou descontos encontrados, isto é, quanto tempo leva até o preço de mercado e o NAV voltarem ao equilíbrio. Os resultados encontrados mostram que os fundos BOVA11 e PIBB11 adotam uma estratégia de full replication, enquanto o SMAL11 apresenta uma estratégia de otimização. O tracking error encontrado está em linha com aqueles observados em ETFs europeus e os três fundos estudados são negociados, na média, com desconto. Finalmente, tanto BOVA11 e PIBB11 levam sete dias para voltarem ao equilíbrio, bastante acima da média observada na literatura internacional, enquanto o SMAL11 leva apenas dois dias para isso, o que é inesperado já que é o fundo menos líquido dentre os analisados. Os resultados indicam que as ferramentas de arbitragem não estão sendo utilizadas de maneira eficiente. / [en] The objective of this study is to analyze the pricing efficiency of three of the most liquid brazilian Exchange-Traded Funds (BOVA11, SMAL11 and PIBB11) and determine if they follow closely the indexes they try to replicate, comparing with the international literature regarding the foreign ETFs performance. Firstly, this study verifies which strategy is adopted by each fund, as well as the quality of this replication by evaluating the tracking error observed in these funds. Then it is analyzed if there is any deviation between the trading price and the net asset value (NAV) of the respective ETF, that is, if the security is being traded, on average, with a premium or discount. Finally, it is evaluated the persistence of those premiums and discounts found, that is, how much time it takes until the trading price and the NAV go back to equilibrium. The results showed that both BOVA11 and PIBB11 adopt a full replication strategy, while SMAL11 presents an optimization strategy. The tracking error found is in line with those observed in European ETFs and the three funds are traded, on average, with a discount. Finally, both BOVA11 and PIBB11 take seven days to go back to equilibrium, while SMAL11 only takes two days, an unexpected result as this is the least liquid fund of the three that are part of this study. Therefore, the arbitrage tools are not being used efficiently.

Diese Dissertation hat zum Ziel, digitale Vermögenswerte statistisch zu durchleuchten und damit einen Beitrag zur Integration digitaler Vermögenswerte in die digitale Gesellschaft zu leisten. Die Kapitel dieser Arbeit lassen sich unter den Schlagworten Abbildung und Analyse der Marktdynamiken von digitalen Vermögenswerten, sowie Investitionen in digitale Vermögenswerte zusammenfassen. Das erste Kapitel, Abbildung der Marktdynamiken digitaler Vermögenswerte, evaluiert die derzeit existierenden Indizes für Kryptowährungen (KWen) sowohl qualitativ als auch quantitativ. Als Grundlage für die Analyse des KW-Sektors ist zunächst eine geeignete Abbildung von dessen Marktdynamiken nötig. Die schnelle Entwicklung des KW-Sektors, seine hohe Volatilität und das häufige Aufkommen und Verschwinden von KWen stellen die Emittenten von KW-Indizes vor Herausforderungen. Jeder Index geht mit diesen Herausforderungen anders um und so unterscheiden sich die methodischen Ansätze der Indizes ebenso wie ihre statistischen Eigenschaften. Das zweite Kapitel, Analyse der Marktdynamiken von digitalen Vermögenswerten, untersucht die Dynamiken des KW-Sektors. Damit sich der KW-Sektor etablieren und in die Finanzwelt integriert werden kann, müssen zunächst die zugrunde liegenden Dynamiken verstanden werden. Wir modellieren die nicht-stationären Renditen und deren Volatilität durch zwei stochastische Differentialgleichungen und schätzen deren Parameter auf Bayes’sche Weise. Dabei identifizieren wir verschiedene Muster des KW-Sektors in Bezug auf Renditen, Volatilität und Sprünge. Im dritten Kapitel, Investitionen in digitale Vermögenswerte, konstruieren wir einen ETF auf den CRIX (vgl. Trimborn and Härdle, 2018), einen Index für den KW-Sektor. Dabei beleuchten wir die zugrundeliegenden Mechanismen, identifizieren potentielle Risiken und schätzen die Kostenstruktur eines solchen KW-ETFs ab. Damit ebnen wir den Weg für die Implementierung dieses neuartigen Finanzprodukts. / This dissertation aims to shed light on the new asset class „digital assets“ from a statistical perspective and thus contributes to the integration of digital assets into the digital society. The chapters of this thesis can be summarized by the keywords tracking, understanding, and investing in digital assets. The first chapter, tracking digital assets, evaluates the currently existing cryptocurrency (CC) indices both qualitatively and quantitatively. As a basis for the analysis of the CC sector, it is first necessary to find an appropriate mapping of the market dynamics. The rapid development of the CC sector, its high volatility and the frequent emergence and disappearance of CCs pose challenges for the issuers of CC indices. Each index deals with these challenges differently, and so the methodological approaches of the indices differ, as do their statistical properties. The second chapter, understanding digital assets, examines the dynamics of the CC sector. For the CC sector to become established and integrated, the underlying dynamics must first be understood. Therefore, we model the non-stationary returns and volatility by two stochastic differential equations and estimate their parameters in a Bayesian manner. Thereby, we identify several patterns on the dynamics of the CC sector with respect to returns, volatility and jumps. The third chapter, investing in digital assets, aims to pave the way for the integration of digital assets into the financial sector. As investments in digital assets remain risky due to high volatility and frequent disappearance of CCs, ETFs are a suitable tool to invest in this sector. We construct an ETF on the CRIX (cf. Trimborn and Härdle, 2018), an index for the CC sector. In doing so, we reveal the underlying mechanisms, risks and costs of such a new financial product and pave the way for its implementation.

Recently, there are more and more literatures discuss on the issues of investment strategies of leveraged ETFs. In our works, we concentrate our issues on optimal leverage of ETF of S&P 500 index. Based on ARMA-GARCH model¡¦s assumption, we find out that the forecasting optimal leverage can be shown in a formula which contains return and characteristic function. In this paper, we use MA(1)-GARCH(1,1) to forecast volatility based on 1008 rolling window to forecast one day ahead¡¦s volatility; and our estimation time is start from 1954 to March 2011. In this paper, we present four dynamic leverage models (Normal, Student T, VG, and Best model¡¦s leverage) to find out the payoffs under these models. In our model, the forecasting accuracy is just about 55% which is slightly higher than SPX raise probability. But during long-term compound effect, the dynamic leverage models can out-perform than constant leverage. There may exist some important factors in these results, one of them is the crash forecasting ability. During 1980 to 2011 SPX has 14 big crashes and these models can effectively avoid 10 big crashes. In short-term investment horizon none of these five models are always outperform than others but in long-term investment horizon the strategy of best model¡¦s leverage can always earn money when investment horizon is 2400 days.

This paper presents the role of alternative energy technologies in displacing fossil fuels as the world's primary energy source. To that end, a CAPM-GARCH multi-factor market model is used to investigate the relationship between returns on oil and alternative energy stocks. Results show that an increase in oil prices and the broad market have a statistically significant and positive impact on alternative energy stock returns. Furthermore, the alternative energy sector is substantially more risky than the broad market but has the potential for higher returns. This highlights the infancy and inherently risky nature of the alternative energy sector today, but demonstrates the potential for substantial future investment gain as alternative energy technologies become more mature and widely available. Interestingly, estimation of the alternative energy index model indicated the presence of abnormal returns which was not the case for the solar index model, implying that the abnormal returns were generated from a different sectoral component of the alternative energy index.

本篇研究以台灣首檔指數股票型基金(Exchange Traded Fund)-台灣卓越50證券投資信託基金，台灣證券交易所股票交易代碼0050，英文名稱：Taiwan Top50 Tracker Fund (簡稱TTT)為研究對象，以個案研究方式探討其在台灣當時之市場環境下在短期內進行多項法規修訂與首創獨步全球的集合實物申購機制，促成其資產規模的成長創下世界紀錄，由上市時的42.87億元，至2004年6月30日達448.61億，短短1年的時間，資產規模增加10.46倍；而基金單位數也持續成長至1,003百萬個單位，較掛牌時的116百萬個單位也大幅成長8.65倍。而該產品開發團隊發展出全球首創之『集合實物申購』初級市場營運模式，順利讓政府相關特殊基金得以將其部份持有股票進行轉換，使得台灣50指數ETF中65.6%的基金資產規模源自於此，本次報告將分析及證明其關鍵地位。

The first essay examines cross-sectional differences between money market mutual funds (MMMFs), in the context of the sponsoring fund family. While extant studies have shown that fund family characteristics impact the management of open-end equity mutual funds, results of this study’s analysis find that fund family characteristics also affect the management of MMMF assets, contributing to differences in the maturity of the fund’s holdings, expenses, and realized returns. I find that an MMMF is not simply a transitional account with a short-term low-risk investment objective, but rather, a critical role player within the fund family. Differences in maturity, yield, and expenses in MMMFs can be explained by family-specific characteristics, including diversification and cash management strategies at the family level. The second essay examines implications of substitutability of two similar financial assets: conventional index mutual funds and exchange traded funds (ETFs). I seek to explain the coexistence of these fund types, since both offer a claim on the same underlying index return process, but have different organizational structures. This study compares conventional open-end index funds with matched ETFs on various underlying indexes. Aggregate flows are used to detect substitution and clientele effects. I show that conventional funds and ETFs are substitutes, while ETFs have smaller tracking errors and lower fund expenses. However, I find that these fund types are not perfect substitutes, and their coexistence can be explained by a clientele effect that segregates them into different market niches.

本研究以台灣投資人的角度，探討是否可利用指數股票型基金來建構投資組合，以期能較投資於單一市場能有更佳的投資績效。同時利用期貨契約進行價格、匯率風險之規避。 在2002年8月至2005年1月的研究期間，本研究之投資組合現貨部分，是利用24支於美國證券交易所上市之指數股票型基金與台灣TTT，套用傳統之Markowitz平均數—變異數模式，並考慮不同程度之Home-Bias下，建構出六群組的投資組合。避險策略部分，乃使用交叉避險模型，利用S&P500指數期貨、美元指數期貨、台股期貨進行避險，以期達到持有期間風險最小之目的。並根據匯率的波動情形，再將樣本區分為匯率波動較和緩與相對劇烈的兩子期間。以探討在上述投資策略下，國際投資組合在避險前後是否同樣具有分散風險之優勢，以及避險前後的績效差異，最終希望能對台灣投資人在投資決策上有一適當建議。 本文重要結論如下： 1.本文選取之指數股票型基金，大多數具有複製指數報酬之能力。但是，其投資風險並非僅單純反應當地股市之變動，而是存在部分風險來自掛牌市場的變動。 2.台灣人利用投資指數股票型基金，的確能達到風險分散之目的。避險後，能更加強投資組合在風險分散上的優勢，平均而言，與僅投資於台灣股市相比，未避險之投資組合能降低標準差約15%，避險後之投資組合能再降低標準差約33%。 3.管投資人欲規避的是價格風險或是匯率風險，維持一貫的風險趨避態度並以期貨契約管理，反而是一種機會的損失。如果希望能在價格風險因子呈現有利走勢時仍要避險，不宜使用本研究所使用之追求變異最小之避險模型來設定策略。 4.用期貨契約進行最適避險策略，以等比例投資組合的避險績效最佳。可能之原因為，等比例投資組合其權重相等，配合此避險策略，能同時兼顧匯率風險與股市風險，故避險效果較佳。

Magister Commercii - MCom / The notion of market efficiency posits that stock prices fully reflect all available information in a timely manner. The efficient market hypothesis (EMH) proposed by Fama (1970) systematically rules out the profitability of information driven investing, and implicitly promulgates a passive market capitalisation weighted investment strategy such as indexing. The appeal of passive strategies has largely been driven by the growth of passive tracking instruments, which allow investors to earn underlying index performance by purchasing a single security such as an exchange traded fund (ETF). On the contrary, proponents of behavioural finance suggest that investors are irrational and subject to psychological biases. Furthermore, the noisy market hypothesis of Siegel (2006) asserts that the deviations from the economic ideal of rationality proposed by the EMH, introduces noise in the market which could lead prices to deviate from their intrinsic values. The resultant drag in performance of market capitalisation weighted indices suggests that the optimal cap-weighted market portfolio promulgated by the modern portfolio theory (MPT) of Markowitz (1952), ceases to be the most mean-variance approach to asset allocation. With the goal of testing the applications of ETF’s, this study first evaluates the performance of passive sector ETF’s in the global equity market. In addition, motivated by the potential inefficiencies of capweighted portfolios, the study tests optimisation based asset allocation techniques, and technical analysis based market timing strategies. The study employs the S&P Global 1200 sector indices and their respective sector ETF’s to test their performances and applications in passive and active investment strategies, over the period from July 5th, 2002 to February 6th, 2015. The ETF’s are evaluated based on their tracking ability and price efficiency. All 10 sector ETF’s possess insignificant tracking errors and successfully replicate the performance of their underlying indices. In addition, the globalsector ETF’s are not price efficient over the study period, as they possess persistent price deviations from their net asset values (NAV’s). Furthermore, the ETF trading strategy based on the relationship between ETF returns and price deviations, proves to be effective in outperforming the passive buy and hold strategy in the majority of the sectors. The sector decomposition of the cap-weighted S&P Global 1200 index which is employed as the market proxy, reveals that its sector allocation remains fairly stable throughout the study period. In contrast, the optimal historical sector composition incurs large changes in sector exposure from year to year and provides substantially superior performance relative to the cap-weighted market portfolio. The cap-weighted portfolio tends to overweight cyclical sectors and underweight resilient sectors during major economic downturns. The long-only, long-short and market neutral strategies developed from the S&P Global 1200 index and its constituent sector indices provide exceptional risk-adjusted performance, and more meanvariance efficient portfolios than the cap-weighted market proxy. The relaxation of the longonly constraint also improves the optimised portfolios risk-adjusted performance, mainly through risk reduction benefits. The performance of the optimised global sector based portfolios also resembles the performances of the global style based optimised portfolios developed by Hsieh (2010), thereby suggesting that the two approaches are analogous. The 3 technical market timing strategies tested in this research provide varying results. The sector momentum portfolios experience significant positive returns during bull markets, however the portfolios incur significant drawdowns during periods of economic turmoil such as the 2008 global financial crisis. As a result, all sector momentum portfolios provide inferior risk-adjusted returns relative to the passive cap-weighted buy and hold strategy. The exponential moving average (EMA) trend timing strategy promulgated by Hsieh (2010) provides impressive risk-management attributes and superior risk-adjusted performance relative to passive buy and hold benchmarks. Similarly, the alternative technical charting heuristics trend timing strategy helps reduce drawdowns during market crashes, however the charting strategy provides inferior cost and risk-adjusted performance relative to the capweighted buy and hold approach due to larger timing errors and longer hedging periods in comparison to the EMA strategy. In addition, the global tactical sector allocation (GTSA) model tests the EMA and technical charting trend timing tools in the context of a global sector portfolio, and the model provides outstanding cost and risk-adjusted performances relative to the passive investing alternatives. The portfolio based GTSA model highlights the benefits of portfolio diversification and successfully hedges market exposure during economic downturns.

This thesis is focused on some of the new instruments on capital markets -- specifically on Investment Certificates, Warrants, Exchange Traded Funds and Contracts for Difference. It shows fundamental principle of behavior, important specifications and comparison to other investment products. The text further examine overall instruments' offering especially on the European markets and compare trading possibilities of the main brokers in the Czech Republic. The work analyses price changes of the instruments and related underlying assets and examine risk and profitability with respect to the latest global financial crisis.

The study describes how cointegration-based techniques can be employed in order to construct profitable trading strategies that exploit mispricing events between similar securities. Particularly, the Johansen Maximum Likelihood Estimation and the Kalman filter approaches are applied to the universe of 200 most liquid ETF stocks traded on NYSE and NASDAQ. The results show that the strategies are quite sensitive to transaction costs, but are still able to maintain profitability even after accounting for a conservative level of transaction costs. While the Kalman filter produces better results on daily data, the 15-minute timeframe is dominated by portfolios constructed by the Johansen cointegration test. Both strategies achieve significantly higher risk-adjusted returns on the intraday timeframe. The study also reveals a performance decline of both strategies in the period of 2013-2015 and outlines possible interpretation of such event.