This paper discusses the indicators of financial success for Swedish companies from 1995 until 2005. Quarterly data on 42 Swedish companies were collected from the Datastream data base and analysed by using both portfolio analyses and parametric analysis. In this study, financial success is measured by using the acclaimed concepts of the Sharpe ratio and the Jensen’s Alpha. The Sharpe ratios of the companies are studied between 1995-2005 and this discussion is complemented by analysis of the Jensen’s Alpha in the second half of that time period i.e. 2000-2005. The relationship between these performance metrics and certain company-characteristics such as the book-to-market ratio, the ROA measure and capital structure is studied. The conclusion is that companies that have a high degree of profitability and maintain high book-to-market ratios outperform other companies in terms of generating excess returns to shareholders. Another interesting observation is the fact that company size does not have any significant relationship to company performance.

There are different types of risk, examples include credit risk, liquidity risk and financial risk. In DeMarzo & Berk (2011, s. 293) is a study presented which is based on the yield of different types of financial assets between 1925 and 2009, the study show that a high risk gave substantially higher reward. With the study as a background, it is interesting to study practical risk management within participants of the financial markets of Sweden. In risk management there are several theories about whether risk can be calculated and analyzed with scientific methods in practice. To generate new empirical data a qualitative method was used in the form of interviews. The selection, which was strategic, was based on mailed questionnaire sent to participants of the Swedish fund market. Theory can be problematic to apply in practice, since reality is often simplified in theory, as discussed by Franklin (2004). Franklin’s thoughts are accompanied by Baird (2010) in a similar discussion. The main model of the study is Value at Risk, which is recovered from Hull (2011) but has its origin from the financial company JP Morgan. Other models that are applied in the study are Capital Asset Pricing Model, CAPM, and the Sharpe ratio. There are known critiques against these models, which are discussed in this study. In the study it is shown that all the participants applied the model Value at Risk. The report also indicates that standard deviation has a central role in risk management. All the respondents were well aware of the critique against Value at Risk. To manage the flaws of the model they also used stress tests as a complement. The analysis of the study indicates that practical and theoretical application in many aspects are similar, the most apparent one being Value at Risk. Even though there are some differences, CAPM was indicated to have no practical use for any of the participants. Two vital factors for whether a model can be applied practically are the model’s simplicity and the need for assumptions to correlate with reality. Having completed this study, the conclusion that the participants successfully applied theoretical risk management models in practice can be validated.

The concept of emerging markets came to surface in early 1980 and constituted of only eight countries from the two continents of South America and Asia. The globalization of financial markets has since raised the importance of emerging capital markets. We take a quantitative approach to investigate the performance of emerging markets compared to developed markets. The aim of the study is to conclude if emerging markets offers investment value and if logic in portfolio theory can be used to improve the chance of creating a relatively better performing investment. Included markets in our study are Brazil, Russia, India, China, Colombia, Indonesia, Vietnam, Egypt, Turkey and South Africa. S&P 500 is our benchmark for developed market performance. Sample period is 2002-01-01 to 2011-12-31 and monthly return data, creating 120 data points on each index.   The weighting schemes used for the portfolios are min variance optimization, geographical location and high and low correlation. All investments are scored on performances in correlation to S&P 500, inflation adjusted growth, currency effect, Sharpe ratio, skewness and kurtosis. Rankings are done on the separate categories, on the individual overall ranking on only countries and one overall ranking on all investments. A brief overview of the overall ranking for all investments suggest that medium performing investments are overrepresented (12/20) and the low and high is underrepresented (3/20 and 5/20). Of note is that the min variance portfolio outperforms its components, the geographical portfolios have a wide range and the high correlated portfolio outperforms the low. The country to portfolio ratio over each grade suggests only a small skew of the results. There is no low scoring portfolio but the other two ratios are close to 50/50, suggesting that on average the portfolios create diversification benefits. Furthermore normality of returns seem to be violated and then the concept of volatility as a risk measure is significantly impaired also currency risk can be of high importance, currency effects ranged from -48% to 28.7%. Assuming non-normality seems more accurate than assuming normality; therefore we need to improve on volatility as a tool to measure risk. So one direction for further research we see a need is in the concept of volatility. The initial reason for this research came from small investors’ seemingly intuitive knowledge that emerging markets are a suitable investment option. We have concluded that they in fact are, therefore we suggest that a qualitative study is conducted to investigate this seemingly natural intuition.

Since most financial institutions use the Sharpe Ratio to evaluate the performance of mutual funds, the objective of most fund managers is to select the portfolio that can generate the highest Sharpe Ratio. Traditionally, they can revise the objective function of the Markowitz mean-variance portfolio model and resolve non-linear programming to obtain the maximum Sharpe Ratio portfolio. In the scenario with short sales allowed, this project will propose a closed-form solution for the optimal Sharpe Ratio portfolio by applying Cauchy-Schwarz maximization. This method without using a non-linear programming computer program is easier than traditional method to implement and can save computing time and costs. Furthermore, in the scenarios with short sales disallowed, we will use Kuhn-Tucker conditions to find the optimal Sharpe Ratio portfolio. On the other hand, an efficient frontier generated by Markowitz mean-variance portfolio model normally has higher risk higher return characteristic, which often causes dilemma for decision maker. This research applies generalized loss function to create a family of decision-aid performance measures called IRp which can well tradeoff return with risk. We compare IRp with Sharpe Ratio and utility functions to confirm that IRp measures are approapriate to evaluate portfolio performance on efficient frontier and to improve asset allocation decisions. In addition, empirical data of domestic and international investment instruments will be used to examine the feasibility and fitness of the new proposed method and IRp measures. This study applies the methods of Cauchy-Schwarz maximization in multivariate statistical analysis and loss function in quality engineering to portfolio decisions. We believe these new applications will complete portfolio model theory and will be meaningful for academic and business fields.

Sharpekvoten är ett av de mest frekvent använda prestationsmåtten för fonder. Kvoten beskriver en fonds riskjusterade avkastning genom att dividera dess överavkastning med dess standardavvikelse. Måttet har emellertid fått kritik på flera områden och visat sig vara missvisande under vissa scenarion, något som även denna studie påvisar. Studien bygger på en kvantitativ metod där ett stickprov används för att beskriva den studerade populationen; Sverigefonder. Studiens resultat visar att Sverigefonders avkastning inte är normaldistribuerad, något som är ett grundantagande vid Sharpekvots-beräkningen då fondens standardavvikelse används. Resultaten visar att samtliga observationers avkastningsdistribution antingen är positiv eller negativs skev, vilket leder till att standardavvikelsen konsekvent över- eller underskattar tillgångens risk. Tidigare studier betonar att även avkastningsdistributionens skevhet har betydelse vid investeringar. Denna aspekt återspeglas dock inte i den traditionella Sharpekvoten och författaren presenterar därför en egen modifikation av måttet där avkastningsdistributionens skevhet adderas. Studiens resultat bör tolkas ur ett behavior-finance-perspektiv, där människor antas ha olika tidshorisont för investeringar, inte antas agera rationellt, samt påverkas känslomässigt av marknadshändelser. Med det som utgångspunkt adderar avkastningsdistributionens skevhet värdefull information för investeraren, bortom fondens medelavkastning och standardavvikelse som enligt modern portföljteori är de enda två aspekterna en investerare har preferenser om. En ytterligare aspekt som påvisas i studien är att det tycks finnas en osund informationsassymetri mellan spararna och fondkommissionerna, samt strukturella incitament för att behålla denna. Detta kan ses som en förklaringsgrund till det minskade förtroendet som växt fram för de aktivt förvaltade fonderna. Författaren föreslår ökad transparens från fondkommissionernas sida och ser en presentation av en skevhetsjusterad Sharpekvot som ett steg på vägen. Studien bidrar till tidigare forskning genom att empiriskt påvisa fördelen med en modifikation av Sharpekvoten som adderar informationsvärde för investerarna. / The Sharpe ratio is one of the most frequently used performance measures for funds. The ratio is describing a fund’s risk adjusted return by dividing its excess return by its standard deviation. The measure has been subject to critique in several areas and has shown to be misleading under certain scenarios, something that this study also indicates. The study is conducted based on a quantitative method where a sample is used to describe the target population; Sverigefonder. The results of the study shows that Sverigefonders return is not normally distributed, something that is elementary assumed when calculating the Sharpe ratio by the usage of the standard deviation. The results show that all the observations’ return distribution either is positively or negatively skewed. The implication of that is that the standard deviation consistently either over- or under estimates the asset’s risk. Previous studies emphasize that the skewness of the return distribution is of importance as well when investing. This aspect is not reflected though in the traditional Sharpe ratio and the author is therefor presenting an own modification of the performance measure where the skewness is added to the ratio. The results of the study should be interpreted from a behavior finance perspective, where investors are assumed to have different time horizons for investing, act irrational, and reacting emotionally to market events. With those aspects as the premise, the skewness of the return distribution is adding valuable information for the investor, beyond the fund’s average return and standard deviation, which are the only two aspects that the investor has a preference regarding according to modern portfolio theory. One additional aspect that is shown in the study is that there seems to exist an unhealthy information asymmetry between the investors and the fund commissions, and structural incentives to keep it. This can be seen as a suggestion of explanation to the lowered trust for the actively managed funds. The author is proposing enhanced transparency for the fund commissions and sees the presenting of a skewness-adjusted Sharpe ratio as a step in that direction. This study is contributing to previous research by empirically showing the advantage off presenting a modification of the Sharpe ratio, which adds additional information to the investors.

In this thesis, portfolio optimisation is used to evaluate if a specific sample of portfolios have a higher risk level or lower expected return, compared to what may be obtained through optimisation. It also compares the return of optimised portfolios with the return of the original portfolios. The risk analysis software Aegis Portfolio Manager developed by Barra is used for the optimisations. With the expected return and risk level used in this thesis, all portfolios can obtain a higher expected return and a lower risk. Over a six-month period, the optimised portfolios do not consistently outperform the original portfolios and therefore it seems as though the optimisation do not improve the return of the portfolios. This might be due to the uncertainty of the expected returns used in this thesis.

Purpose: The main purpose of this study is to study the 45 funds, divided into three differentdivisions, then the result will provide a greater understanding of how returns change with ahigher risk. Methodology: The study is based on a quantitative approach. The survey was conducted bygathering raw data from databases and secondary data from literature, printed and electronicsources. Theoretical perspectives: The study is based on the theory: the efficient markethypothesis, which argues that future returns can not be calculated as the market is fullyinformed. The study is therefore studying historical yields. Empirical foundation: Empirical data are acquired from www.morningstar.se, andtherefore also treated on this page. The material is then divided into documents and time axes. Conclusions: The study has shown that high-risk funds give a higher percentage returns thanmedium-and low-risk funds. However, does not imply a higher risk automatically earn ahigher return when the low-risk funds have shown a higher yield than medium-risk funds. Animportant factor to study when you are looking for the fund which generated the highest ROIis the Sharpe ratio. Although this study demonstrates that high-risk funds have a higherSharpe ratio than competing risk groups.

This master thesis analyses socially responsible investments. Socially Responsible Investment aims to create a positive impact on society and the environment. Its aim is to evaluate and analyze funds’ performance and methods of assessment. The added value of the theme lies in the potential for further development of sustainable investment, focusing on the current opportunities that investors can use on the Czech market.

This paper analyses the difference in risk-adjusted returns between Sin-stocks and SRI-investing for the period 2001-2021. The analysis was conducted by creating two optimally risky portfolios according to the Modern Portfolio Theory, one comprised of only Sin-stocks and one with only high ESG scoring companies. The Sin-stocks contained stocks from four different sectors, alcohol, gambling, tobacco and weapons while the companies for the SRI-portfolio was chosen from the FTSE4Good index. The regression models were chosen to follow both the CAPM, and the Fama & French three factor model and the regressions were in the end conducted with the GARCH model which showed results that both the SRI-portfolio and the Sin-portfolio had a general excess return over the market. The two portfolios were also compared with the help of Sharpe Ratio and Jensen’s Alpha. The Sharpe ratio as well as the Jensen’s Alpha showed that the Sin-portfolio had the highest risk-adjusted returns. In conclusion, the SRI-portfolio as well as the Sin-portfolio both outperformed the market during the time period 2001-2021 and they were both less volatile than the market.

In this thesis, the aim is to investigate whether a pairs trading strategy on Swedish stocks can generate a higher risk-adjusted return compared to a buy-and-hold strategy on a benchmark index. The benchmark index is the OMX Stockholm Benchmark-index (OMXSBPI), which is an index that should reflect the Swedish market in general. With a statistical focus, a trading algorithm is built which is then evaluated on data between the years 2018 to 2021. The statistical concepts this thesis is based on are stationarity and cointegration and it is the Augmented Dickey-Fuller test that forms the basis for being able to test these concepts. The risk-adjusted return for the strategy is evaluated using the popular measure Sharpe ratio, which is then compared to the Sharpe ratio for the OMXSBPI-index. The results obtained in this study can not confirm that the pairs trading strategy is better than a buy-and-hold strategy on the OMXSBPI-index in terms of risk-adjusted return. One indication, however, is that the strategy seems to perform better in conditions when the market is declining. In 2018, the index went down by 7.7060 while the strategy went up by 7.5100 percent. As it is data for only one year, it is not possible to determine whether it is due to chance or a potential edge of the strategy.