Förvaltning och avkastning hos fonder har forskats om i flera studier runt om i världen. Tidigare forskning har gett varierande resultat, där vissa studier visar på att det föreligger ett samband mellan en fonds avgift och avkastning, medan andra inte kan säkerställa ett sådant resultat. Då de svenska hushållen idag sparar mer än någonsin, visar det på att fondsparande är ett aktuellt ämne för ytterligare forskning. Statistik från 2020 visar att fondförmögenheten i Sverige totalt uppgick till 4 554 miljarder kronor och har visat på en fortsatt ökande trend de senaste åren. Dock har endast få studier genomförts på den svenska kapitalmarknaden och de har i huvudsak analyserat ämnet på kort sikt, med en tidsperiod om fem år. Eftersom avgifternas påverkan på fonder är tydligast på lång sikt, ger det utrymme för fortsatt forskning inom ämnet. Syftet med följande forskning är att studera sambandet mellan svenska aktiefonders avkastning och avgift på lång sikt i förhållande till fondernas risk. Studien avgränsas till att undersöka svenska aktiefonder som har varit verksamma i minst tio år, mellan åren 2011-2020. Forskningen antar en kvantitativ forskningsmetod, vilket syftar till att testa teorier. Tillvägagångssätt sker genom en analys av urvalets regression och korrelation i samband med hypotesprövning, där variabler undersöks för att ge underlag till studiens analys av resultat. Studiens resultat visar att svenska aktiefonder i genomsnitt underpresterar den svenska marknaden på lång sikt. Forskningen visar även varierande resultat gällande korrelation mellan riskjusterad avkastning och avgift på lång sikt. Resultaten indikerar att den svenska kapitalmarknaden har en relativ marknadseffektivitet av svag form. I tillägg verkar aktivt förvaltade fonder kunna utnyttja tillfällig trendidentifiering och informationsasymmetri för att uppnå en överavkastning. Forskningen avslutas med slutsatsen att högavgiftsfonder, vilka är mer aktivt förvaltade, indikeras vara ett bättre investeringsalternativ för att uppnå en god långsiktig prestation i jämförelse med passiva fonder. / The management and return of funds have been researched in many studies around the world. Previous research has yielded varied results, with some studies showing that there is a link between a fund's fee and return, while others cannot ensure such a result. As Swedish households save more today than ever, it shows that fund saving is a current topic for further research. Statistics from 2020 show that fund assets in Sweden are 4 554 billion swedish crowns in total, a number that has continuously grown in the past years. However, only a few studies have been conducted on the Swedish capital market where the existing studies have mainly analyzed the subject in the short term, with a time period of five years. Since the impact of fund fees is most noticeable in the long term, the subject can be further explored.  The aim of this research is to study the correlation between returns and fees of Swedish equity funds in the long term in relation to the funds risk. The study is limited to examining Swedish equity funds that have been active for at least ten years, between the years 2011-2020. The study adopts a quantitative research method, which aims to test theories. This research utilizes a regression and correlation analysis in conjunction with hypothesis testing, where variables are examined to provide a basis for the study's analysis of results. The results of this study show that Swedish equity funds on average underperform the Swedish market in the long term. The research also shows varying results regarding the correlation between risk-adjusted return and fee in the long term. The results of this study indicate that the Swedish capital market has a relative weak form of market efficiency. In addition, actively managed funds seem to be able to utilize occasional trend identification and information asymmetry to achieve an excess return. The research concludes that high-fee funds, which are more actively managed, indicate to be a better investment alternative for achieving long-term performance in comparison to passive funds.

L’objectif principal de cette thèse est d’apporter de nouveaux résultats théoriques concernant la performance d’investissements basés sur des modèles stochastiques. Pour ce faire, nous considérons la stratégie optimale d’investissement dans le cadre d’un modèle d’actif risqué à volatilité constante et dont la tendance est un processus caché d’Ornstein Uhlenbeck. Dans le premier chapitre,nous présentons le contexte et les objectifs de cette étude. Nous présentons, également, les différentes méthodes utilisées, ainsi que les principaux résultats obtenus. Dans le second chapitre, nous nous intéressons à la faisabilité de la calibration de la tendance. Nous répondons à cette question avec des résultats analytiques et des simulations numériques. Nous clôturons ce chapitre en quantifiant également l’impact d’une erreur de calibration sur l’estimation de la tendance et nous exploitons les résultats pour détecter son signe. Dans le troisième chapitre, nous supposons que l’agent est capable de bien calibrer la tendance et nous étudions l’impact qu’a la non-observabilité de la tendance sur la performance de la stratégie optimale. Pour cela, nous considérons le cas d’une utilité logarithmique et d’une tendance observée ou non. Dans chacun des deux cas, nous explicitons la limite asymptotique de l’espérance et la variance du rendement logarithmique en fonction du ratio signal-sur-bruit et de la vitesse de retour à la moyenne de la tendance. Nous concluons cette étude en montrant que le ratio de Sharpe asymptotique de la stratégie optimale avec observations partielles ne peut dépasser 2/(3^1.5)∗100% du ratio de Sharpe asymptotique de la stratégie optimale avec informations complètes. Le quatrième chapitre étudie la robustesse de la stratégie optimale avec une erreur de calibration et compare sa performance à une stratégie d’analyse technique. Pour y parvenir, nous caractérisons, de façon analytique,l’espérance asymptotique du rendement logarithmique de chacune de ces deux stratégies. Nous montrons, grâce à nos résultats théoriques et à des simulations numériques, qu’une stratégie d’analyse technique est plus robuste que la stratégie optimale mal calibrée. / The aim of this thesis is to study the robustness of the optimal trading strategy. The setting we consider is that of a stochastic asset price model where the trend follows an unobservable Ornstein-Uhlenbeck process. In the first chapter, the background and the objectives of this study are presented along with the different methods used and the main results obtained. The question addressed in the second chapter is the estimation of the trend of a financial asset, and the impact of misspecification. Motivated by the use of Kalman filtering as a forecasting tool, we study the problem of parameters estimation, and measure the effect of parameters misspecification. Numerical examples illustrate the difficulty of trend forecasting in financial time series. The question addressed in the third chapter is the performance of the optimal strategy,and the impact of partial information. We focus on the optimal strategy with a logarithmic utility function under full or partial information. For both cases, we provide the asymptotic expectation and variance of the logarithmic return as functions of the signal-to-noise ratio and of the trend mean reversion speed. Finally, we compare the asymptotic Sharpe ratios of these strategies in order to quantify the loss of performance due to partial information. The aim of the fourth chapter is to compare the performances of the optimal strategy under parameters mis-specification and of a technical analysis trading strategy. For both strategies, we provide the asymptotic expectation of the logarithmic return as functions of the model parameters. Finally, numerical examples find that an investment strategy using the cross moving averages rule is more robust than the optimal strategy under parameters misspecification.

Background: This study discusses the phenomenon of luxury goods as investment assets,focusing on luxury watches in particular. The rise of globalization and increased wealth,particularly among the middle and high-income groups in developing countries, hascreated a larger potential customer base for luxury items. This has led to an increasing interest in luxury goods as investment assets, including collectibles such as cars, art, andwine. The recent development of online niche marketplaces for luxury goods has enabledthe systematic collection of data, facilitating research on Veblen goods as alternativeinvestment assets. Therefore, it is interesting to analyze the financial performance ofinvestments in luxury watches as compared to traditional assets. Purpose: The purpose of this study is to analyze the comparative performance ofinvesting in luxury watches versus traditional assets such as equities and bonds. Methodology: This study collects data on luxury watch prices and characteristics. Thehedonic pricing method is used to regress the price of the watches on their characteristics.The regression results are used to analyze the price impact of the characteristics, as well asto create a watch price index. In order to evaluate the index performance, data is collectedfor the MSCI World Index and the Bloomberg U.S. Aggregate Bond Index. For all the indices, the financial metrics of the Sharpe ratio, Treynor ratio, CAPM, and Jensen’s alphaare calculated. Conclusion: This study suggests that luxury watches, with their wide price ranges and high resale value, have been a viable option for portfolio diversification during thestudied five-year period between 2018 and 2023. The watch index yields an averagereturn of 2.01 % and a cumulative return of 49.35 %, outperforming the MSCI World Indexwith average returns of 1.38 % and the Bloomberg U.S. Aggregate Bond Index with -0.01%, and cumulative returns of 31.90 % and -0.15 %, respectively. The watch index alsooutperforms the compared indices in terms of the financial metrics Sharpe ratio, Treynorratio, CAPM, and Jensen’s alpha. The results suggest that the most important valuedrivers for luxury watches are: Brand (Audemars Piguet, Patek Philippe, and VacheronConstantin), Features (Chronograph, tourbillon, and rotating bezel) and Case Material(bronze, rose gold, and yellow gold).

This is a study where the purpose is to investigate the risk-adjusted return and the correlation between the two investments, the stock market and the condominium market. In addition to this, it was analyzed how the two investments performed during the financial crisis and the covid-19 crisis. Study is carried out to get answers to the eternal question of which of these two investments is considered the most suitable for both short-term or long-term investment goals where financial conditions are taken into account. The study conducted various tests such as Pearson correlation test, volatility and regression models. The Sharpe ratio was used to measure the risk-adjusted return. These are carefully selected to see what returns the two investments give at different risks, as well as how the investments correlate with each other during crises and conditions of economic growth. The conclusion reached by this study is that the investor should diversify and invest in both investments. This is because their risk versus return profile becomes more even by investing in both investments. When one investment does worse, the other investment will, according to the study's various tests, make the return and risk profile more stable. Despite the high correlation between the investments, diversification is useful in case of possible future economic crises. / Detta är en studie där syftet är att undersöka den riskjusterade avkastningen samt korrelationen  mellan de två investeringarna aktiemarknaden och bostadsrättsmarknaden. Utöver detta analyserades hur de två investeringarna presterade under finanskrisen och covid-19-krisen.  Studie är genomförd för att få svar på den eviga frågan om vilken av dessa två investeringar som anses vara lämpligast för både kortsiktiga eller långsiktiga investeringsmål där ekonomiska förhållanden tas i akt.  Studien genomförde olika tester som Pearson korrelationstest, volatilitet och regressionsmodeller. Sharpekvoten användes  för att mäta den riskjusterade avkastningen. Dessa är noga utvalda för att se vad de två investeringarna ger för avkastning vid olika risker, samt hur investeringarna korrelerar med varandra under kriser och förhållanden vid ekonomisk tillväxt. Slutsatsen som denna studie kom fram till är att investeraren bör diversifiera sig och investera i båda investeringarna. Detta på grund av att deras riskprofil kontra avkastning blir mer jämnare genom att investera i båda investeringarna. När den ena investeringen går sämre kommer den andra investeringen som enligt studiens olika tester att göra att avkastningen och riskprofilen blir mer stabil. Trots den höga korrelationen mellan investeringarna så är diversifiering användbar vid eventuella framtida ekonomiska kriser.

This thesis studies the increasingly prevalent concept of sustainability in a financial context. Specifically, the question as to whether negative screening implies a cost or a benefit from an investor perspective is derived from past research’s inconclusive findings. The method adopted in order to answer the question is the construction of a negatively screened portfolio. The negative screening is done on an industry basis to see if excluding firms that engage in activities related to ESG risks would increase or decrease portfolio performance. Costs or benefits are primarily estimated as the intercept, also referred to as alpha, from Carhart’s (1997) four-factor model but is complemented by both the CAPM and the Fama-French three-factor model. The results of this study indicate no significant findings, as measured in alpha, achieved from the negative screening. However, the findings suggest a lower Sharpe ratio in the screened portfolio, and that negative screening may be associated with a lower systematic risk similar to what previous research has found.

The stock market is a non-linear field, but many of the best-known portfolio optimization algorithms are based on linear models. In recent years, the rapid development of machine learning has produced flexible models capable of complex pattern recognition. In this paper, we propose two different methods of portfolio optimization; one based on the development of a multivariate time-dependent neural network,thelongshort-termmemory(LSTM),capable of finding lon gshort-term price trends. The other is the linear Markowitz model, where we add an exponential moving average to the input price data to capture underlying trends. The input data to our neural network are daily prices, volumes and market indicators such as the volatility index (VIX).The output variables are the prices predicted for each asset the following day, which are then further processed to produce metrics such as expected returns, volatilities and prediction error to design a portfolio allocation that optimizes a custom utility function like the Sharpe Ratio. The LSTM model produced a portfolio with a return and risk that was close to the actual market conditions for the date in question, but with a high error value, indicating that our LSTM model is insufficient as a sole forecasting tool. However,the ability to predict upward and downward trends was somewhat better than expected and therefore we conclude that multiple neural network can be used as indicators, each responsible for some specific aspect of what is to be analysed, to draw a conclusion from the result. The findings also suggest that the input data should be more thoroughly considered, as the prediction accuracy is enhanced by the choice of variables and the external information used for training. / Aktiemarknaden är en icke-linjär marknad, men många av de mest kända portföljoptimerings algoritmerna är baserad på linjära modeller. Under de senaste åren har den snabba utvecklingen inom maskininlärning skapat flexibla modeller som kan extrahera information ur komplexa mönster. I det här examensarbetet föreslår vi två sätt att optimera en portfölj, ett där ett neuralt nätverk utvecklas med avseende på multivariata tidsserier och ett annat där vi använder den linjära Markowitz modellen, där vi även lägger ett exponentiellt rörligt medelvärde på prisdatan. Ingångsdatan till vårt neurala nätverk är de dagliga slutpriserna, volymerna och marknadsindikatorer som t.ex. volatilitetsindexet VIX. Utgångsvariablerna kommer vara de predikterade priserna för nästa dag, som sedan bearbetas ytterligare för att producera mätvärden såsom förväntad avkastning, volatilitet och Sharpe ratio. LSTM-modellen producerar en portfölj med avkastning och risk som ligger närmre de verkliga marknadsförhållandena, men däremot gav resultatet ett högt felvärde och det visar att vår LSTM-modell är otillräckligt för att använda som ensamt predikteringssverktyg. Med det sagt så gav det ändå en bättre prediktion när det gäller trender än vad vi antog den skulle göra. Vår slutsats är därför att man bör använda flera neurala nätverk som indikatorer, där var och en är ansvarig för någon specifikt aspekt man vill analysera, och baserat på dessa dra en slutsats. Vårt resultat tyder också på att inmatningsdatan bör övervägas mera noggrant, eftersom predikteringsnoggrannheten.

Morningstar ratings are a popular way for investors to compare mutual funds. This thesis focuses on Swedish domestic equity funds. The relation of Morningstar ratings and fund flows was studied. Additionally, the short-term performance predictability using star ratings was investigated. This study found that top rated funds using Morningstar ratings received a higher fraction of positive fund flows compared to top rated funds ranked using past returns, Sharpe ratio, or Carhart's four-factor alpha. This provides some evidence towards Swedish investors using Morningstar ratings over other measures when selecting mutual funds. Additionally, all four measures performed poorly when used to predict one-, three- and twelve-month future fund flows, with no model being able to explain more than 7% of the variance in the data (measured in adjusted R-squared). Finally, the predictive power of Morningstar rating in respect to future outperformance (measured in Carhart's four-factor alpha) was evaluated. While all star ratings were statistically significant predictors, no model managed to explain more than 17% of the data's variance. Thus, Morningstar ratings were not found to be a good predictor of future outperformance. / Morningstar Ratings är ett populärt sätt för investerare att jämföra fonder. Denna uppsats fokuserar på svenska fonder som investerar på den svenska aktiemarknaden. Sambandet mellan Morningstar Ratings och fondflöden studerades. Även förmågan att på kort sikt förutsäga fonders prestation genom att använda deras Morningstar Rating undersöktes. Denna studie fann att topprankade fonder utifrån Morningstars prestationsmått fick en högre andel av positiva inflöden än om fonderna rankades efter tidigare avkastning, Sharpekvot eller Carharts alfa. Detta ger begränsat stöd till att svenska investerare använder Morningstar Ratings över andra prestationsmått vid val av fonder. Dessutom hade alla mått låg förklarande förmåga för framtida fondflöden över en, tre och tolv månader. Ingen modell kunde förklara mer än 7% av variansen i fondflödena (mätt i justerad R2). Till sist utvärderades förmågan att förutsäga framtida (Carharts) alfa genom Morningstar Rating. Trots att Morningstar Ratings kunde anses vara statistiskt viktiga för modellen, lyckades ingen modell förklara mer än 17% av variansen i alfa. Således kunde inte Morningstar Ratings anses vara en bra prediktor för framtida alfa.

The Covid-19 pandemic influenced the world with quarantines, travel bans, social distancing, and much more. Most remarkably, it brought the economy to a steep recession with changes in customer behavior and shocks to the financial markets. Combined with this, sustainable and green investing have grown in importance for firms that aim to incorporate sustainable practices in their businesses. This thesis evaluates the relationship between ESG and financial performance for Swedish issued mutual funds in the periods before, during, and after the covid pandemic. To capture the returns this study uses the Sharpe ratio, which penalizes volatility in the turns of funds and outputs risk-adjusted returns. The findings of this thesis highlight the importance of integrating non-financial metrics into portfolio management. The results found evidence that there is a difference in the performance between the two fund portfolios. Furthermore, this study will investigate the impact ESG variables have on the risk-adjusted rate of return. The results were that there is no compelling evidence of ESG variables impacting the returns. Moreover, significant insights from this study can be made to the Modern Portfolio Theory and Stakeholder Theory. By using Modern Portfolio Theory as the governing theory, a theoretical discussion has been made about the relationship between green investments and financial performance in times of sound economic markets and under financial crisis. This study is a quantitative study that has adopted the deduction approach. The authors of this thesis have retrieved 2 different portfolios, ESG and non-ESG, and compared the two groups against each other. 3 different periods have also been identified in the thesis: pre, during, and post Covid. The performance of the two portfolios has been examined during the three different stages to see how they have performed with hopes of finding empirical evidence that investing in ESG practices really is profitable. Statistical models such as OLS, heteroskedasticity, and more have been used in the study with the aim of helping the authors reach a conclusion.

Seven out of ten Swedes save voluntarily in funds, and if premium pensions and pension savings are taken into account, almost all adults save. In recent years, there has been a growing interest in sustainable funds, with more than a third choosing a sustainable fund to invest in. There is a disagreement in the existing research as to whether sustainable funds are a better option than conventional ones.  The study examined whether sustainable funds underperformed conventional funds on the variables of return, standard deviation and Sharpe ratio. The study's measurement period covered 21 April 2019 to 21 April 2024, for Swedish-registered funds in the industrial sector. The study conducted a quantitative approach using t-tests and regression analyses to examine performance across categories. The study obtained secondary data from Morningstar and used the Morningstar Sustainability Rating to categorise the funds. Funds with a rating of 1-3 were defined as conventional and sustainable as those with a rating of 4-5.  From the data collected in the study, the authors concluded that the t-test between conventional and sustainable funds was significant based on the standard deviation variable, while the other variables were not significant. Like the t-test, the regression analysis between sustainability ratings and standard deviation was significant and the other regressions were not significant. The study does not find that sustainable funds are characterised by lower returns, higher risk or lower risk-adjusted returns compared to conventional funds. / Sju av tio svenskar sparar frivilligt i fonder och tar man hänsyn till premiepensionen och pensionssparande så sparar nästan alla vuxna. Under de senare åren har det växt fram ett intresse för hållbara fonder, där mer än en tredjedel har valt en hållbar fond att investera i. Det finns en oenighet i den befintliga forskningen huruvida hållbara fonder är ett bättre alternativ än konventionella.  Studien undersökte om hållbara fonder presterade sämre än konventionella fonder utifrån variablerna avkastning, standardavvikelse och Sharpekvot. Studiens mätperiod avsåg 2019-04-21 till 2024-04-21, för svenskregistrerade fonder inom industrisektorn. Studien genomförde en kvantitativ ansats med hjälp av t-tester och regressionsanalyser för att undersöka prestationen mellan kategorierna. Studien inhämtade sekundärdata från Morningstar och har använt Morningstar Sustainability Rating för att kategorisera fonderna. Fonder som innehar 1-3 i betyg definierades som konventionella och hållbara som innehar 4-5 i betyg.  Av studiens inhämtade data, konstaterade författarna att t-testet mellan konventionella och hållbara fonder var signifikant utifrån variabeln standardavvikelse medan de övriga variablerna inte var signifikanta. Likt t-testet var regressionsanalysen mellan hållbarhetsbetyg och standardavvikelse signifikant och de övriga regressionerna var ej signifikanta. Studien kan inte konstatera att hållbara fonder kännetecknas av en lägre avkastning, en högre risk eller en lägre riskjusterad avkastning gentemot konventionella fonder.

Socially responsible investing has presented itself as a growing, multifaceted, advanced and sophisticated investment philosophy. Socially responsible investment (SRI) involves incorporating social, ethical and responsible investment objectives with financial investment objectives during the investment decision-making process. Social, ethical and responsible investment objectives are set in line with environmental, social and corporate governance (ESG) criteria which are established within the SRI strategy followed. SRI strategies include screening (negative, positive and best-of-sector), shareholder activism and cause-based investing. Although international SRI markets such as that of the United States of America and the United Kingdom are sophisticated and established markets, the South African SRI market is still relatively new and is yet to reach its full potential. Thus, as a growing market, little research regarding the long term risk-adjusted performance of SRI funds in South Africa has been conducted. The long term risk-adjusted performance of the sample of SRI funds was measured through the use of five risk-adjusted performance measures, namely the Treynor ratio, Sharpe ratio, Jensen’s alpha, Sortino ratio and Omega ratio, and through the use of three performance measurement models which included the capital asset pricing model (CAPM), Fama-French three-factor model and Carhart four-factor model. The risk-adjusted performance of the sample of SRI funds was measured with the intent to establish if these funds out- or underperformed against three benchmark categories, namely the Financial Times Stock Exchange/Johannesburg Stock Exchange (FTSE/JSE) SRI Index, a matched sample of conventional investment (non-SRI) funds and the FTSE/JSE All Share Index. The probable effect of the 2007/08 global financial crisis was also measured to analyse whether such a hazardous market event affected the performance of the SRI funds. According to the results and findings, the risk-adjusted performance of the SRI funds has improved over the research period. However, the SRI funds neither outperformed nor underperformed against the three benchmark categories over the research period. The performance measurement models’ analysis indicated that the SRI funds were less sensitive to market fluctuations, more exposed to small capitalisation portfolios, more growth-oriented, and exhibited significant momentum after the period of the 2007/08 global financial crisis. Furthermore, the analysis indicated that the SRI funds significantly underperformed against the non-SRI funds during the Performance of socially responsible investment funds in South Africa research period. Mixed results were obtained with regards to the probable effect of the 2007/08 global financial crisis on the performance of the SRI funds.