<p>The purpose of the thesis has been to explore the use of hedge fund styles when constructing portfolios of hedge funds (i.e. funds of hedge funds). The central question is if the use of hedge fund styles can significantly explain and improve risk adjusted returns (characterized by Sharpe ratios). The study has been done in collaboration with Optimized Portfolio Management AB who desire further knowledge and evaluation of hedge fund styles for their fund of hedge funds.</p><p>To be able to create successful ex ante portfolios we have explored various prediction models for both risk and return. Our findings indicate that return prediction is problematic using simple models such as regression since the risk exposure of the indices appear to change significantly over time. One can however using exponentially weighted moving averages (EWMA) achieve relatively promising estimations of future returns. </p><p>Covariance matrix estimation seems to be more straightforward. We have achieved promising results using both traditional EWMA models as well as improved estimators using principal component analysis.Covariance prediction models were evaluated separately using a minimum-variance portfolio optimization technique and provided a significant risk reduction compared to the aggregated hedge fund universe (represented by a naively diversified portfolio). Combinations of risk and return prediction models were evaluated using traditional mean-variance portfolio construction methods, which were optimized for Sharpe ratios. These provided a significant increase in risk adjusted returns relative to the aggregated hedge fund universe. The allocation is however discouraging due to serious instability over time.</p><p>Our findings indicate that there indeed is an advantage of taking hedge fund styles into consideration when constructing funds of hedge funds in a risk adjusted perspective. However, further research into return prediction needs to be done in order to stabilize portfolio allocation. An alternative seems to be tactical style allocation on a more fundamental analysis basis.</p>

<p><strong>Purpose:</strong> Aims of this paper is to evaluate a comparative study between China and Russia funds in respect of the risks and returns. We also want to examine what has affected the funds in their respective domestic stock market.                                                            </p><p><strong>Method:</strong> The study is based on qualitative methodology to complement the quantitative survey by first gathering of secondary data from Morningstar, and fund manager´s stories on fund and banking companies' websites.  Primary data is conducted by the interview with fund manager. The sample consists of all land funds for China and Russia has found more than 10 years on the stock market.</p><p><strong>R</strong><strong>esults and Conclusion</strong>: The survey shows that China funds will generate better in decline than Russia Funds in both return and risk-adjusted Sharpe ratio. Because the China funds had better risk diversification and its holdings spread across different industry area while Russia funds is more directed towards oil and gas industry. The upturn managed Russia Funds better to recovery than China Funds in terms of return and risk-adjusted Sharpe ratio, which was due to China funds were cautiously optimistic, with the government's stimulus package, while Russia Funds earned at the price of oil in the world increased and a greater willingness to take risks of the global financial system. During the 10 years period, Russia funds better growth compared to China Funds in the total seen by far. For Russia have large oil resources and raw materials including exporting to the fast growing Asian. In China, due to good growth in the consumption good and growing middle class in the country, but also increased projects in financial and infrastructure.</p>

<p>In this thesis, we conduct a case study by applying simple technical trading rules on Chinese stock market. The technical trading rules we tested are moving average rules and trading range breakout rules. The stock indices we tested are SSE A (Shanghai A) and SZSE (Shenzhen A) share, these shares are limited to the Chinese domestic traders. Our main trading rule frameworks are mainly from Brock, Lakonishok& Lebaron (1992), which including the most basic technical trading rules and covered various length of period, however we add the 25 days moving average to our frame work. We obtained our data from DataStream; the data are the daily closing prices of two indices we mentioned above.</p><p>We compared the mean return and Sharpe ratio with buy and hold. We further calculated breakeven transaction costs to test whether the technical trading rules can still add wealth to investors after adjusting the transaction costs. Our results showed that most technical trading rules perform better than buy and hold. VMA perform better than FMA and TRB, short period (25 and 50 days) performed better than longer period. On mean return, our data violated the assumption of parametric statistical test. We performed non-parametric tests, all the trading rules showed statistical significance at 95% level than buy and hold except FMA (1, 25,0), all the trading rules resulted higher Sharpe ratio than buy and hold. On transaction costs, 7 trading rules on SSE A are performed poorer than buy and hold, all the other rules provided positive breakeven transaction costs. Across the entire trading rule, both stock markets offered positive break-even transaction costs, 0.436% for SSE A and 1.369% for SZSE A. and they are both higher than the maximum transaction costs one bears.</p>

The purpose of the thesis has been to explore the use of hedge fund styles when constructing portfolios of hedge funds (i.e. funds of hedge funds). The central question is if the use of hedge fund styles can significantly explain and improve risk adjusted returns (characterized by Sharpe ratios). The study has been done in collaboration with Optimized Portfolio Management AB who desire further knowledge and evaluation of hedge fund styles for their fund of hedge funds. To be able to create successful ex ante portfolios we have explored various prediction models for both risk and return. Our findings indicate that return prediction is problematic using simple models such as regression since the risk exposure of the indices appear to change significantly over time. One can however using exponentially weighted moving averages (EWMA) achieve relatively promising estimations of future returns. Covariance matrix estimation seems to be more straightforward. We have achieved promising results using both traditional EWMA models as well as improved estimators using principal component analysis.Covariance prediction models were evaluated separately using a minimum-variance portfolio optimization technique and provided a significant risk reduction compared to the aggregated hedge fund universe (represented by a naively diversified portfolio). Combinations of risk and return prediction models were evaluated using traditional mean-variance portfolio construction methods, which were optimized for Sharpe ratios. These provided a significant increase in risk adjusted returns relative to the aggregated hedge fund universe. The allocation is however discouraging due to serious instability over time. Our findings indicate that there indeed is an advantage of taking hedge fund styles into consideration when constructing funds of hedge funds in a risk adjusted perspective. However, further research into return prediction needs to be done in order to stabilize portfolio allocation. An alternative seems to be tactical style allocation on a more fundamental analysis basis.

In this thesis, we conduct a case study by applying simple technical trading rules on Chinese stock market. The technical trading rules we tested are moving average rules and trading range breakout rules. The stock indices we tested are SSE A (Shanghai A) and SZSE (Shenzhen A) share, these shares are limited to the Chinese domestic traders. Our main trading rule frameworks are mainly from Brock, Lakonishok&amp; Lebaron (1992), which including the most basic technical trading rules and covered various length of period, however we add the 25 days moving average to our frame work. We obtained our data from DataStream; the data are the daily closing prices of two indices we mentioned above. We compared the mean return and Sharpe ratio with buy and hold. We further calculated breakeven transaction costs to test whether the technical trading rules can still add wealth to investors after adjusting the transaction costs. Our results showed that most technical trading rules perform better than buy and hold. VMA perform better than FMA and TRB, short period (25 and 50 days) performed better than longer period. On mean return, our data violated the assumption of parametric statistical test. We performed non-parametric tests, all the trading rules showed statistical significance at 95% level than buy and hold except FMA (1, 25,0), all the trading rules resulted higher Sharpe ratio than buy and hold. On transaction costs, 7 trading rules on SSE A are performed poorer than buy and hold, all the other rules provided positive breakeven transaction costs. Across the entire trading rule, both stock markets offered positive break-even transaction costs, 0.436% for SSE A and 1.369% for SZSE A. and they are both higher than the maximum transaction costs one bears.

This paper investigates whether an Islamic screened benchmark index shows a different risk adjusted performance in comparison to a non-screened benchmark index. In contrast to other papers this study analyzes daily observations in the years from 2007 to 2012, a period heavily affected by the financial crisis. The Capital Asset Pricing Model and the Jensen measure of abnormal returns are used to estimate and compare the indexes mean risk-adjusted returns. The results show that the Islamic index does not reveal any different level of daily mean risk-adjusted returns compared to the conventional non-screened index. Hence, Muslims who align their investments according to the teachings of Islam are not worse off than non-restricted investors following the screened Islamic index.

This report covers a study testing the possibility of adding portfolio optimization by mean-variance analysis as a tool to extend the concept of momentum strategies in contrast to naive allocation formed by Jegadeesh &amp; Titman (1993). Further these active investment strategies are compared with a passive benchmark as well as a randomly selected portfolio over the entire study-period. The study showed that the naive allocation model outperformed the mean-variance model both economically as well as statistically. No indication where obtained for a lagged return effect when letting a mean-variance model choose weights for a quarterly holding period and the resulting investment recommendation is to follow a naive investment strategy within a momentum framework.

Aim: Based on portfolio theory, which highlights diversification, and CSR, which describes the value of social and ethical responsibility of corporations, this study examines whether there is a difference in risk-adjusted performance between ethical and traditional mutual funds. Ethical funds are limited in their opportunities of diversification and should therefore be limited in their potential perfomance. On the other hand, a focus on social and ethical responsibility can be profitable. Method: The study uses a quantitative approach where we used 25 mutual fund in each category, ethical and conventional mutual funds. The mutual funds and their data has been obtained from www.morningstar.se and www.pensionmyndigheten.se. Historical performance between 2009-2013 were processed to obtain the Sharpe ratio and M2. For comparison a independent t-test is used. Result &amp; Conclusions: Although ethical and traditional mutual funds have different diversification opportunities, the results indicate no significant difference in risk-adjusted performance between ethical and conventional funds.

The traditional way to analyze stocks and portfolios within the area of finance have been restricted to Sharpe and Markovitz. The Omega function and its properties enlighten the field of finance and differs from the traditional ways when it comes to the volatility of the stocks. The Omega function, the Sharpe performance criteria and mean-variance model by Markovitz will be used. All calculations are done in Matlab and the data sheets are excel tables. The aim of this thesis is to investigate the nordic small cap market by using the Omega function, Sharpe performance criteria and the mean variance model by Markovitz. In order to to see how the purposed methods differs.

Submitted by Hubertus Schlögl (tassilo.schloegl@web.de) on 2018-02-01T16:37:02Z No. of bitstreams: 1 Macroeconomic Indicators and Systematic Risk - Is there a difference between Emerging and Developed Markets? Hubertus Tassilo Schlögl 338933 - EESP.pdf: 877788 bytes, checksum: 2e7cfedabad96e3c0375688472e9cb5e (MD5) / Approved for entry into archive by Josineide da Silva Santos Locatelli (josineide.locatelli@fgv.br) on 2018-02-01T17:55:54Z (GMT) No. of bitstreams: 1 Macroeconomic Indicators and Systematic Risk - Is there a difference between Emerging and Developed Markets? Hubertus Tassilo Schlögl 338933 - EESP.pdf: 877788 bytes, checksum: 2e7cfedabad96e3c0375688472e9cb5e (MD5) / Made available in DSpace on 2018-02-02T11:15:26Z (GMT). No. of bitstreams: 1 Macroeconomic Indicators and Systematic Risk - Is there a difference between Emerging and Developed Markets? Hubertus Tassilo Schlögl 338933 - EESP.pdf: 877788 bytes, checksum: 2e7cfedabad96e3c0375688472e9cb5e (MD5) Previous issue date: 2018-01-16 / This explorative study is about the influencing effects of US macroeconomic announcements on changes in systematic risk with the focus on the difference between emerging and developed markets. Seven different US macroeconomic indicators have been examined and used to estimate betas as a proxy for the systematic risk around the announcement dates. In the period from 1996 until 2017, betas have been estimated over a three-month pre- and post window, resulting in 27 announcements per US macroeconomic indicator. The study also tries to provide insights of the consequences for portfolio managers, based on patterns of changes in betas and their relationship with changes in Sharpe ratios. The study results reveal that betas change consistently over the sample period, however, to a small magnitude. Also, the changes in mean Sharpe ratios around these announcement dates have not been found as statistical significant. However, the study results indicate that there is a positive relationship between changes in Sharpe ratios and changes in betas for developed countries as the Pearson correlation coefficient illustrates. / O seguinte estudo analisa a influência das publicações de dados macroeconómicos nas variações do risco sistemático, salientando os diferentes efeitos sobre os mercados emergentes e os países desenvolvidos. Foram examinados sete diferentes indicadores macroeconómicos dos EUA, sendo estes utilizados para determinar uma estimativa dos valores do risco sistémico perto das datas das publicações macroeconómicos dos EUA. No período entre 1996 e 2017, os betas foram estimados sobre um intervalo de tempo de três meses antes e depois de cada publicação, resultando em 27 publicações por cada indicador do EUA. Nesta análise também se tenta explicar as consequências destes efeitos para os gestores de carteiras, baseando-se em padrões de variações dos betas e a sua relação com as variações dos Sharpe Ratios. Os resultados desta análise evidenciam que os betas variam consistentemente ao longo do período da amostra, ainda que numa baixa magnitude. Além disso, as variações no valor médio dos Sharpe Ratios nas datas próximas aos relativos anúncios económicos não são estatisticamente significativas. Contudo, os resultados desta análise indicam que existe uma relação positiva entre variações dos Sharpe Ratios e variações nos betas dos países desenvolvidos, como o coeficiente de correlação de Pearson demonstra.