Submitted by Marcelo Bonança (marcelo.bonanca@vale.com) on 2014-10-31T17:02:59Z No. of bitstreams: 1 Dissertação_Marcelo Bonança.pdf: 792001 bytes, checksum: 5a68a41e5ddebd68c372493c95f262a8 (MD5) / Approved for entry into archive by Vitor Souza (vitor.souza@fgv.br) on 2014-11-25T17:15:41Z (GMT) No. of bitstreams: 1 Dissertação_Marcelo Bonança.pdf: 792001 bytes, checksum: 5a68a41e5ddebd68c372493c95f262a8 (MD5) / Approved for entry into archive by Vitor Souza (vitor.souza@fgv.br) on 2014-11-25T17:17:48Z (GMT) No. of bitstreams: 1 Dissertação_Marcelo Bonança.pdf: 792001 bytes, checksum: 5a68a41e5ddebd68c372493c95f262a8 (MD5) / Made available in DSpace on 2014-11-26T16:45:01Z (GMT). No. of bitstreams: 1 Dissertação_Marcelo Bonança.pdf: 792001 bytes, checksum: 5a68a41e5ddebd68c372493c95f262a8 (MD5) Previous issue date: 2014-05-19 / This study analyses the effects of diversification in risk and return among the major global mining players. To evaluate the diversification, firstly, we created a ranking that relates risk, degree of diversification and return of the companies. It was mandatory to create a data base with a series of revenues and proxies of cash generation by business, which is not fully provided by Bloomberg, Economática or other public data bases. We estimated the effects of diversification by using the CAPM to calculate the companies’ beta and basic statistics of the historical return series to find the Sharpe Index. We looked through the financial statements to understand more profoundly their businesses for a sample equivalent to 50% of the market capitalization of the top 100 mining companies of the world for the period from 2002 to 2014. Finally, we approached, as a study case, essential issues in the diversification as efficiency and discipline in capital allocation. Our study confirmed the presence of a negative correlation between risk and diversification degree. It also showed evidences which suggest that focused companies have better discipline in capital allocation, and hence, generate more value to their shareholders. / Neste trabalho, medimos os efeitos da diversificação sob o aspecto de risco e retorno entre os grandes players globais de mineração. Para avaliar a diversificação, primeiramente, foi criado um ranking que relaciona risco, grau de diversificação e retorno das empresas. Foi necessário montar um banco de dados com séries de receita e de proxies de geração de caixa por negócios, o qual não se encontra prontamente disponível na Bloomberg, Economática ou em outras bases de dados públicas. Estimamos os efeitos da diversificação fazendo o uso do CAPM para calcular o beta das empresas e das estatísticas básicas das séries históricas de retornos para encontrar o Índice de Sharpe. Examinamos os demonstrativos financeiros das empresas para entender com maior profundidade seus negócios para uma amostra equivalente a 50% do valor de mercado das top 100 empresas de mineração do mundo para o período entre 2002 e 2014. Por fim, abordamos, sob a forma de estudo de caso, questões relevantes na diversificação como a eficiência e a disciplina na alocação de capital. Nosso estudo confirmou que existe uma correlação negativa entre o risco e o grau de diversificação e que há sinais que sugerem que as companhias mais focadas possuem maior disciplina na alocação do capital, e, com isso geram mais valor para seus acionistas.

nÃo hà / Este artigo analisa grÃfica e quantitativamente a performance, mensurada sob vÃrias mÃtricas de risco-retorno, de estratÃgias ativas disponÃveis para um investidor brasileiro que opte por compor carteiras dinÃmicas de aÃÃes transacionadas na Bolsa de Valores de SÃo Paulo. As estratÃgias adotadas se baseiam: (i) em âapostarâ em aÃÃes que se mostraram vencedoras em Sharpe e Treynor no ano anterior, compondo carteiras equal-weighted ou (ii) em definir os pesos a partir da otimizaÃÃo destas duas mÃtricas de performance, as mais usuais no mercado financeiro. Em suma, em perÃodos de boom econÃmico-financeiro, ou seja, atà 2007 e durante 2009, ao lidar com o trade-off entre o uso de tÃcnicas mais sofisticadas de composiÃÃo de carteira, o investidor brasileiro teria obtido um retorno nominal acumulado bastante superior quando do uso da otimizaÃÃo do Ãndice de Sharpe â acima de 4000% entre julho de 1995 e dezembro de 2007, por exemplo â, vis-Ã-visas demais estratÃgias e mesmo quando comparado aos maiores fundos de investimento em aÃÃes ou ainda aos benchmarks de mercado e setoriais, ao quais nÃo ultrapassaram 2500%. Em termos de performance risco-retorno, as estratÃgias de aposta nas vencedoras em Sharpe ou Treynor se mostram as mais adequadas. Em perÃodos de crise financeira, analisando sob todas as mÃtricas de ganho ou performance, o investidor deveria ter optado por uma postura passiva. / This paper analyzes the risk-return performance, graphically and quantitatively - measured under various metrics, of active strategies available for a Brazilian investor who chooses to compose dynamic portfolios with stocks traded in BOVEPSA, Bolsa de Valores de SÃo Paulo. The strategies used here are based on: (i) "betting" in Sharpe and Treynor winners securities the previous year, composing an equalweighted portfolio or (ii) optimizing these two widely used performance metrics, and the defining the weights. To summarize, in periods of economic boom - until 2007 and during 2009 - when dealing with the trade-off between using more sophisticated portfolio composition techniques, the Brazilian investor would have gotten a much higher accumulated nominal return when using the Sharpe index optimization â over 4000% between July 1995 and December 2007, for example â vis-Ã-vis other strategies and even when compared to larger stock mutual funds or to the market and industry benchmarks, which does not exceed 2500%. In terms of risk-return performance, the betting strategies based on Sharpe and Treynor winners are the most appropriate. In periods of financial crisis, observing any performance measure, an investor should have chosen for a passive strategy.

This diploma thesis "A Performance Comparison of in Czech Republic available mutual funds and ETFs from the view of CZK investor" elaborates on collective investing in Czech Republic; focusing on mutual funds and their exchange traded alternatives in ETFs. In the thesis, a history of Czech collective investments' development is briefly mentioned and of ETFs' beginnings in the US, also a legislative framework for the mutual funds in CZ is shortly discussed; furthermore, different approaches to fund classification based on various criteria are provided. An impact of fund fees and expenses is also analysed. A Current situation on the capital market of funds and ETFs and its trends are showed in many graphs and tables. In the second part of the thesis, author introduces not only the basic ones but also the more sophisticated methods of portfolio's or fund's performance measurements, including yields, risks, risk-adjusted yields etc... The third and last chapter aims at application of the previously mentioned methods on a selection of 20 funds and ETFs; therefore building a financial model enabling that. The analysis is viewed as from the CZK investor, thus all calculations are made in CZK.

This study is a thesis ending a 120 credit masters program in Mathematics with specialization Financial Mathematics and Mathematical Statistics at the Royal Institute of Technology (KTH). The subject of Smart beta is defined and studied in an index fund context. The portfolio weighting schemes tested are: equally weighting, maximum Sharpe ratio, maximum diversification, and fundamental weighting using P/E-ratios. The outcome of the strategies is measured in performance (accumulated return), risk, and cost of trading, along with measures of the proportions of different assets in the portfolio. The thesis goes through the steps of collecting, ordering, and ”cleaning” the data used in the process. A brief explanation of historical simulation used in estimation of stochastic variables such as expected return and covariance matrices is included, as well as analysis on the data’s distribution. The process of optimization and how rules for being UCITS compliant forms optimization programs with constraints is described. The results indicate that all, but the most diversified, portfolios tested outperform the market cap weighted portfolio. In all cases, the trading volumes and the market impact is increased, in comparison with the cap weighted portfolio. The Sharpe ratio maximizer yields a high level of return, while keeping the risk low. The fundamentally weighted portfolio performs best, but with higher risk. A combination of the two finds the portfolio with highest return and lowest risk. / Denna studie är ett examensarbete som avslutar ett 120 poängs mastersprogram i Matematik med inriktning mot Finansiell Matematik och Matematisk Statistik på Kungliga Tekniska Högskolan (KTH). Ämnet Smart beta studeras i kontexten av en indexfond, där de olika testade principerna för viktning i portföljerna är: likaviktad, maximerad Sharpe-kvot, maximerad diversifiering, och fundamental viktning användandes av P/E-tal. Utfallet i testerna utvärderas i ackumulerad avkastning, portföljrisk, kostnad att handla i portföljen, och ett antal mått på fördelningen av tillgångarna. Studien går stegvis igenom processen för att samla in, ordna, och ”tvätta” data. En kort förklaring av historisk simulering, metoden för att estimera stokastiska variabler såsom kovariansmatriser, är inkluderad, såväl som en analys av distributionen av data. Processen för att optimera portföljerna och hur regler för att vara en UCITS-fond kan omformas till optimeringsvillkor beskrivs. Resultaten indikerar att alla utom den mest diversifierade portföljen har högre ackumulerad avkastning än den marknadsviktade portföljen under testperioden. I alla testade fall ökar handelsvolymen liksom marknadspåverkan när en annan strategi än marknadsviktad används. Portföljen med maximerad Sharpe-kvot ger en hög avkastning med bibehållen låg risk. Den fundamentalt viktade portföljen ger bäst avkastning, men med en litet förhöjd risk. Kombinationen av de båda metoderna ger den portföljen med högst ackumulerad avkastning och samtidigt lägst risk under testperioden.

We consider a mechanistic non-linear machine learning approach to learning signals in financial time series data. A modularised and decoupled algorithm framework is established and is proven on daily sampled closing time-series data for JSE equity markets. The input patterns are based on input data vectors of data windows preprocessed into a sequence of daily, weekly and monthly or quarterly sampled feature measurement changes (log feature fluctuations). The data processing is split into a batch processed step where features are learnt using a Stacked AutoEncoder (SAE) via unsupervised learning, and then both batch and online supervised learning are carried out on Feedforward Neural Networks (FNNs) using these features. The FNN output is a point prediction of measured time-series feature fluctuations (log differenced data) in the future (ex-post). Weight initializations for these networks are implemented with restricted Boltzmann machine pretraining, and variance based initializations. The validity of the FNN backtest results are shown under a rigorous assessment of backtest overfitting using both Combinatorially Symmetrical Cross Validation and Probabilistic and Deflated Sharpe Ratios. Results are further used to develop a view on the phenomenology of financial markets and the value of complex historical data under unstable dynamics.

The 2007–2009 financial crisis led to a decrease in consumer and investor confidence worldwide (SARB, 2008:2). Along with the weakened business sentiment and consumer demand, tightened funding conditions in financial markets, increased inflationary pressures, and declining global manufacturing activities, the world economic recession that followed the collapse of the world financial sector led to an estimated wealth destruction of approximately US$50 trillion (SARB, 2008:2; Aisen & Franken, 2010:3; Karunanayake et al., 2010). Apart from this estimate, the International Monetary Fund (IMF) also projected that the global bank balance sheets in advanced countries suffered losses of approximately US$4 trillion during the period 2009–2010 (Aisen & Franken, 2010:3). As a result, investors have become more risk-adverse (Guiso et al., 2013:1), and the consequences of the financial crisis, made insurable profitable investment decisions extremely difficult as market volatility tends to increase during crises periods (Karunanayake et al., 2010; Schwert, 1989:83). With the financial environment in distress, some fund managers consider equities as the preferred asset class to protect the purchasing power of their clients (Ivan, 2013). However, the studies of Ennis and Sebastian (2003) and Nicholas (2004) found evidence that hedge funds will outperform equity markets during a downswing in financial markets. In addition, hedge funds are considered market-neutral due to these investment funds’ unrestricted investment flexibility and more efficient market timing abilities (Ennis & Sebastian, 2003). Hedge funds are also considered to be more unconventional assets for improving portfolio diversification (Lamm, 1999:87), where the variation of investment strategies available in a hedge fund has the ability to satisfy investors with several different risk preferences (Shin, 2012). Still, a number of previous studies have debated conflicting evidence regarding the performance of hedge funds and the persistence in outperforming other markets. This led to the objective of this study; to evaluate the risk-adjusted performance of US and EU hedge funds compared to the associated world equity markets over the 2007–2009 financial crisis. The evidence from this study confirmed the dominance of hedge funds over the CAC 40, DAX, S&P 500 and Dow Jones, from 2004 to 2011, emphasising that the performance of the US and EU hedge funds would overshadow a normal buy-and-hold strategy on the world equity markets under investigation. Overall, the Sharpe-, Sortino-, Jensen’s alpha-, Treynor- and Calmar ratios illustrated that US hedge funds outperformed both EU hedge funds and the associated equity markets over this period. The presence of non-normality among the return distributions led to the use of the Omega ratio as the proper benchmark, which also confirmed the outperformance of US hedge funds over EU hedge funds and associated world equity markets. / MCom (Risk Management), North-West University, Vaal Triangle Campus, 2014

Performance measurement is an integral part of investment analysis and risk management. Investment performance comprises two primary elements, namely; risk and return. The measurement of return is more straightforward compared with the measurement of risk: the latter is stochastic and thus requires more complex computation. Risk and return should, however, not be considered in isolation by investors as these elements are interlinked according to modern portfolio theory (MPT). The assembly of risk and return into a risk-adjusted number is an essential responsibility of performance measurement as it is meaningless to compare funds with dissimilar expected returns and risks by focusing solely on total return values. Since the advent of MPT performance evaluation has been conducted within the risk-return or mean-variance framework. Traditional, liner performance measures, such as the Sharpe ratio, do, however, have their drawbacks despite their widespread use and copious interpretations. The first problem explores the characterisation of hedge fund returns which lead to standard methods of assessing the risks and rewards of these funds being misleading and inappropriate. Volatility measures such as the Sharpe ratio, which are based on mean-variance theory, are generally unsuitable for dealing with asymmetric return distributions. The distribution of hedge fund returns deviates significantly from normality consequentially rendering volatility measures ill-suited for hedge fund returns due to not incorporating higher order moments of the returns distribution. Investors, nevertheless, rely on traditional performance measures to evaluate the risk-adjusted performance of (these) investments. Also, these traditional risk-adjusted performance measures were developed specifically for traditional investments (i.e. non-dynamic and or linear investments). Hedge funds also embrace a variety of strategies, styles and securities, all of which emphasises the necessity for risk management measures and techniques designed specifically for these dynamic funds. The second problem recognises that traditional risk-adjusted performance measures are not complete as they do not implicitly include or measure all components of risk. These traditional performance measures can therefore be considered one dimensional as each measure includes only a particular component or type of risk and leaves other risk components or dimensions untouched. Dynamic, sophisticated investments – such as those pursued by hedge funds – are often characterised by multi-risk dimensionality. The different risk types to which hedge funds are exposed substantiates the fact that volatility does not capture all inherent hedge fund risk factors. Also, no single existing measure captures the entire spectrum of risks. Therefore, traditional risk measurement methods must be modified, or performance measures that consider the components (factors) of risk left untouched (unconsidered) by the traditional performance measures should be considered alongside traditional performance appraisal measures. Moreover, the 2007-9 global financial crisis also set off an essential debate of whether risks are being measured appropriately and, in-turn, the re-evaluation of risk analysis methods and techniques. The need to continuously augment existing and devise new techniques to measure financial risk are paramount given the continuous development and ever-increasing sophistication of financial markets and the hedge fund industry. This thesis explores the named problems facing modern financial risk management in a hedge fund portfolio context through three objectives. The aim of this thesis is to critically evaluate whether the novel performance measures included provide investors with additional information, to traditional performance measures, when making hedge fund investment decisions. The Sharpe ratio is taken as the primary representative of traditional performance measures given its widespread use and also for being the hedge fund industry’s performance metric of choice. The objectives have been accomplished through the modification, altered use or alternative application of existing risk assessment techniques and through the development of new techniques, when traditional or older techniques proved to be inadequate. / PhD (Risk Management), North-West University, Potchefstroom Campus, 2014

Performance measurement is an integral part of investment analysis and risk management. Investment performance comprises two primary elements, namely; risk and return. The measurement of return is more straightforward compared with the measurement of risk: the latter is stochastic and thus requires more complex computation. Risk and return should, however, not be considered in isolation by investors as these elements are interlinked according to modern portfolio theory (MPT). The assembly of risk and return into a risk-adjusted number is an essential responsibility of performance measurement as it is meaningless to compare funds with dissimilar expected returns and risks by focusing solely on total return values. Since the advent of MPT performance evaluation has been conducted within the risk-return or mean-variance framework. Traditional, liner performance measures, such as the Sharpe ratio, do, however, have their drawbacks despite their widespread use and copious interpretations. The first problem explores the characterisation of hedge fund returns which lead to standard methods of assessing the risks and rewards of these funds being misleading and inappropriate. Volatility measures such as the Sharpe ratio, which are based on mean-variance theory, are generally unsuitable for dealing with asymmetric return distributions. The distribution of hedge fund returns deviates significantly from normality consequentially rendering volatility measures ill-suited for hedge fund returns due to not incorporating higher order moments of the returns distribution. Investors, nevertheless, rely on traditional performance measures to evaluate the risk-adjusted performance of (these) investments. Also, these traditional risk-adjusted performance measures were developed specifically for traditional investments (i.e. non-dynamic and or linear investments). Hedge funds also embrace a variety of strategies, styles and securities, all of which emphasises the necessity for risk management measures and techniques designed specifically for these dynamic funds. The second problem recognises that traditional risk-adjusted performance measures are not complete as they do not implicitly include or measure all components of risk. These traditional performance measures can therefore be considered one dimensional as each measure includes only a particular component or type of risk and leaves other risk components or dimensions untouched. Dynamic, sophisticated investments – such as those pursued by hedge funds – are often characterised by multi-risk dimensionality. The different risk types to which hedge funds are exposed substantiates the fact that volatility does not capture all inherent hedge fund risk factors. Also, no single existing measure captures the entire spectrum of risks. Therefore, traditional risk measurement methods must be modified, or performance measures that consider the components (factors) of risk left untouched (unconsidered) by the traditional performance measures should be considered alongside traditional performance appraisal measures. Moreover, the 2007-9 global financial crisis also set off an essential debate of whether risks are being measured appropriately and, in-turn, the re-evaluation of risk analysis methods and techniques. The need to continuously augment existing and devise new techniques to measure financial risk are paramount given the continuous development and ever-increasing sophistication of financial markets and the hedge fund industry. This thesis explores the named problems facing modern financial risk management in a hedge fund portfolio context through three objectives. The aim of this thesis is to critically evaluate whether the novel performance measures included provide investors with additional information, to traditional performance measures, when making hedge fund investment decisions. The Sharpe ratio is taken as the primary representative of traditional performance measures given its widespread use and also for being the hedge fund industry’s performance metric of choice. The objectives have been accomplished through the modification, altered use or alternative application of existing risk assessment techniques and through the development of new techniques, when traditional or older techniques proved to be inadequate. / PhD (Risk Management), North-West University, Potchefstroom Campus, 2014

The 2007–2009 financial crisis led to a decrease in consumer and investor confidence worldwide (SARB, 2008:2). Along with the weakened business sentiment and consumer demand, tightened funding conditions in financial markets, increased inflationary pressures, and declining global manufacturing activities, the world economic recession that followed the collapse of the world financial sector led to an estimated wealth destruction of approximately US$50 trillion (SARB, 2008:2; Aisen & Franken, 2010:3; Karunanayake et al., 2010). Apart from this estimate, the International Monetary Fund (IMF) also projected that the global bank balance sheets in advanced countries suffered losses of approximately US$4 trillion during the period 2009–2010 (Aisen & Franken, 2010:3). As a result, investors have become more risk-adverse (Guiso et al., 2013:1), and the consequences of the financial crisis, made insurable profitable investment decisions extremely difficult as market volatility tends to increase during crises periods (Karunanayake et al., 2010; Schwert, 1989:83). With the financial environment in distress, some fund managers consider equities as the preferred asset class to protect the purchasing power of their clients (Ivan, 2013). However, the studies of Ennis and Sebastian (2003) and Nicholas (2004) found evidence that hedge funds will outperform equity markets during a downswing in financial markets. In addition, hedge funds are considered market-neutral due to these investment funds’ unrestricted investment flexibility and more efficient market timing abilities (Ennis & Sebastian, 2003). Hedge funds are also considered to be more unconventional assets for improving portfolio diversification (Lamm, 1999:87), where the variation of investment strategies available in a hedge fund has the ability to satisfy investors with several different risk preferences (Shin, 2012). Still, a number of previous studies have debated conflicting evidence regarding the performance of hedge funds and the persistence in outperforming other markets. This led to the objective of this study; to evaluate the risk-adjusted performance of US and EU hedge funds compared to the associated world equity markets over the 2007–2009 financial crisis. The evidence from this study confirmed the dominance of hedge funds over the CAC 40, DAX, S&P 500 and Dow Jones, from 2004 to 2011, emphasising that the performance of the US and EU hedge funds would overshadow a normal buy-and-hold strategy on the world equity markets under investigation. Overall, the Sharpe-, Sortino-, Jensen’s alpha-, Treynor- and Calmar ratios illustrated that US hedge funds outperformed both EU hedge funds and the associated equity markets over this period. The presence of non-normality among the return distributions led to the use of the Omega ratio as the proper benchmark, which also confirmed the outperformance of US hedge funds over EU hedge funds and associated world equity markets. / MCom (Risk Management), North-West University, Vaal Triangle Campus, 2014

本研究以近15年台灣股票市場所有上市、上櫃、下市、下櫃股票為樣本，利用每季公布之財務報表的資料，市值、現金流量與股價比率、本益比、資產報酬率、負債比率、報酬率之標準差等指標作為篩選股票依據。 首先，先用財務報表的資料建構出Smart Beta Factor，結合主成分分析將各股評分，作為股票篩選之指標。第一步驟先把市值較低、成交金額過低的股票刪除，並依照不同指標篩選出五倍符合投資組合之股票數，接著運用主成分分析評分後的指標將各公司排序，選出分數高的作為投資組合，以達到分散風險的目標。 本文所討論之Smart Beta Factors有Size、Quality、Value、Momentum、Volatility，並將各Smart beta factor結合主成分分析，計算分數以選出優良股票，並以等權重方式進行資產配置，希望能建構出最有利的投資組合，使得獲利穩定成長。 / In this study, using nearly 15 years quarterly financial statement of stock market in Taiwan as samples. Not only use the financial statement to construct the smart beta factor, also use the principle components analysis to calculate the scores of all the stocks, then choose the stock by the scores. First, delete the stocks of low market value and the stocks of low turnover rate. Second, selected five times the number of the investment portfolio by different indicators, then elect the number of investment portfolio stocks by the highest scores calculated by principal component analysis. To achieve the goal of risk diversification. The smart beta factors discussed in the paper are Size, Quality, Value, Momentum, Volatility, also the multiple factor. To combine the method of principal component analysis, calculate the score to select the stocks, in order to contract the portfolio which has the best performance, and can make stable growth of profits.