Mit zunehmender wirtschaftlicher Bedeutung der Emerging Markets steigt der Bedarf an Unternehmensbewertungen im Kontext dieser Länder. Ihre besonderen Charakteristika erschweren jedoch eine Anwendung der in Industrieländern standardmäßig verwendeten Methoden. Ausgehend von idealisierenden Bedingungen wird in einer integrativen Betrachtung der Frage nachgegangen, wie die vorherrschenden Bedingungen (insbesondere Länderrisiken und Investmentbarrieren) in einem grenzüberschreitenden Bewertungskalkül berücksichtigt werden können.

Titel: Portföljförvaltarens kamp mot index Syftet: Syftet med denna studie är att beskriva och analysera aktiv fondförvaltning genomriskjusterad avkastning. Metod: En kvantitativ studie har genomförts för att uppfylla syftet och besvara studiensfrågeställning för undersökningsperioden 2018–2022. Riskjusterade prestationsmåtten somanvänds är jensens alfa, sharpe- och treynorkvoten. Empiriskt resultat: Studien är baserad på 21 aktivt förvaltade fonder som är registrerad iSverige. Vidare har dessa fonder placeringsinriktning på industrisektorn samt har 80% av sittinnehav på svenska aktier. Slutsats: Mer än hälften av alla fonder genererade ett positivt jensens alfa. Dock visar etttvåsidigt t-test att inget alfavärde var statistiskt signifikant med både 90% och 95%konfidensgrad.Nyckelord: Riskjusterad avkastning, Aktiv fondförvaltning, Treynokvot, Sharpekvot, Jensensalfa, Marknadsindex, Capital Asset Pricing Model (CAPM) och Modern Portföljteori. / Title: Fund manager’s battle against index. Purpose: The purpose of this study is to describe and analyze active funds through riskadjusted returns. Methodology: The study uses a quantitative research method with data from secondarysources that contains fund’s net asset value (NAV). The research period of this study is 2018 to 2022. The study uses jensens alpha, treynor- and sharperatio as risk adjusted measurements. Empirical foundation: This study uses 21 active mutual funds that are registered in Sweden.The mutual funds that were obtained has an investment strategy that focuses on industry.Furthermore, these mutual funds have 80% holdings in Swedish stocks. Conclusion: More than half of the active mutual funds generated a positive jensens alpha.However, according to a two-sided t-test of a 90% and 95% confidence level, none of themutual fund’s alpha showed to be statistically significant and therefore no conclusions weremade.

För att investerare ska placera kapital mot hållbara investeringar krävs insikt om det finns en premie som valet av hållbara aktiefonder innebär eller om dessa motsvarar eller till och med överavkastar mot konventionella fonder. I denna uppsats undersöker vi hur den riskjusterade avkastningen, mätt som Jensens alpha, ser ut för hållbara och konventionella fonder. Studien undersökte 51 aktiefonder med hemvist i Sverige för åren 2017-2021 där datan samlades in från Avanza och hållbarhetsbetyg från Morningstar användes för klassificering av konventionella respektive hållbara fonder. Resultaten pekar på att hållbara aktiefonder har en riskjusterad avkastning som är 0,2 procentenheter högre än konventionella aktiefonder över hela tidsramen. Studien undersökte även förhållandet mellan riskjusterad avkastning och förvaltningsavgiften och fann ett marginellt positivt samband utifrån en regressionsanalys. Studien bidrar till forskningsområdet genom att närmare undersöka ett individuellt land till skillnad från tidigare studier och på senare årtal vilket ger en mer nutida förståelse för hållbara och konventionella aktiefonder på den svenska fondmarknaden. / For investors looking at placing their capital in sustainable equity funds, there is a need for knowledge as to how sustainable funds compare to their conventional peers. Do they demand a premium, have the same returns or even outperform? In this paper we look at the risk adjusted return, Jensen's alpha, on the Swedish fund market between the year 2017-2021 and how sustainable funds compare to conventional ones. The results indicate that sustainable funds outperform conventional funds with 0,2 percentage points over the entire time frame. The study also examined the relationship between fund fees and risk adjusted returns and found a marginal positive relationship from a regression analysis. The study contributes to the scientific field by closer examining a single country for a later time frame, giving a more contemporary understanding of sustainable and conventional funds on the Swedish fund market.

Thesis (MSc (Mathematical Sciences))--University of Stellenbosch, 2011. / Imported from http://etd.sun.ac.za / ENGLISH ABSTRACT: In this thesis, we propose to use Levy processes to model the dynamics of asset prices. In the first part, we deal with single asset options and model the log stock prices with a Levy process. We employ pure jump Levy processes of infinite activity, in particular variance gamma and CGMY processes. We fit the log-returns of six stocks to variance gamma and CGMY distributions and check the goodness of fit using statistical tests. It is observed that the variance gamma and the CGMY distributions fit the financial market data much better than the normal distribution. Calibration shows that at given maturity time the two models fit into the option prices very well. In the second part, we investigate the effect of dependence structure to multivariate option pricing. We use the new concept of Levy copula introduced in the literature by Tankov [40]. Levy copulas allow us to separate the dependence structure from the behavior of the marginal components. We consider bivariate variance gamma and bivariate CGMY models. To model the dependence structure between underlying assets we use the Clayton Levy copula. The empirical results on six stocks indicate a strong dependence between two different stock prices. Subsequently, we compute bivariate option prices taking into account the dependence structure. It is observed that option prices are highly sensitive to the dependence structure between underlying assets, and neglecting tail dependence will lead to errors in option pricing. / AFRIKAANSE OPSOMMING: In hierdie proefskrif word Levy prosesse voorgestel om die bewegings van batepryse te modelleer. Levy prosesse besit die vermoe om die risiko van spronge in ag te neem, asook om die implisiete volatiliteite, wat in finansiele opsie pryse voorkom, te reproduseer. Ons gebruik suiwer–sprong Levy prosesse met oneindige aktiwiteit, in besonder die gamma– variansie (Eng. variance gamma) en CGMY–prosesse. Ons pas die log–opbrengste van ses aandele op die gamma–variansie en CGMY distribusies, en kontroleer die resultate met behulp van statistiese pasgehaltetoetse. Die resultate bevestig dat die gamma–variansie en CGMY modelle die finansiele data beter pas as die normaalverdeling. Kalibrasie toon ook aan dat vir ’n gegewe verstryktyd die twee modelle ook die opsiepryse goed pas. Ons ondersoek daarna die gebruik van Levy prosesse vir opsies op meervoudige bates. Ons gebruik die nuwe konsep van Levy copulas, wat deur Tankov[40] ingelei is. Levy copulas laat toe om die onderlinge afhanklikheid tussen bateprysspronge te skei van die randkomponente. Ons bespreek daarna die simulasie van meerveranderlike Levy prosesse met behulp van Levy copulas. Daarna bepaal ons die pryse van opsies op meervoudige bates in multi–dimensionele exponensiele Levy modelle met behulp van Monte Carlo–metodes. Ons beskou die tweeveranderlike gamma-variansie en – CGMY modelle en modelleer die afhanklikheidsstruktuur tussen onderleggende bates met ’n Levy Clayton copula. Daarna bereken ons tweeveranderlike opsiepryse. Kalibrasie toon aan dat hierdie opsiepryse baie sensitief is vir die afhanlikheidsstruktuur, en dat prysbepaling foutief is as die afhanklikheid tussen die sterte van die onderleggende verdelings verontagsaam word.

Financial markets, particularly capital and stock markets, play an important role in mobilizing and canalising the idle savings of individuals and institutions to the investment options where they are really required for productive purposes. The prediction of stock prices and returns is carried out in order to enhance the quality of investment decisions in stock markets, but it is considered to be tricky and complicates tasks as these prices behave in a random fashion and vary with time. Owing to the potential of returns and inherent risk factors in stock market returns. Various stock market prediction models and decision support systems such as Capital asset pricing model, the arbitrage pricing theory of Ross, the inter-temporal capital asset pricing model of Merton ,Fama and French five-factor model, and zero beta model to provide investors with an optimal forecast of stock prices and returns. In this research thesis, a stock market prediction model consisting of two parts is presented and discussed. The first is the three factors of the Fama and French model (FF) at the micro level to forecast the return of the portfolios on the Saudi Arabian Stock Exchange (SASE) and the second is a Value Based Management (VBM) model of decision-making. The latter is based on the expectations of shareholders and portfolio investors about taking investment decisions, and on the behaviour of stock prices using an accurate modern nonlinear technique in forecasting, known as Artificial Neural Networks (ANN). This study examined monthly data relating to common stocks from the listed companies of the Saudi Arabian Stock Exchange from January 2007 to December 2011. The stock returns were predicted using the linear form of asset pricing models (capital asset pricing model as well as Fama and French three factor model). In addition, non-linear models were also estimated by using various artificial neural network techniques, and adaptive neural fuzzy inference systems. Six portfolios of stock predictors are combined using: average, weighted average, and genetic algorithm optimized weighted average. Moreover, value-based management models were applied to the investment decision-making process in combination with stock prediction model results for both the shareholders’ perspective and the share prices’ perspective. The results from this study indicate that the ANN technique can be used to predict stock portfolio returns; the investment decisions and the behaviour of stock prices, optimized by the genetic algorithm weighted average, provided better results in terms of error and prediction accuracy compared to the simple linear form of stock price prediction models. The Fama and French model of stock prediction is better suited to Saudi Arabian Stock Exchange investment activities in comparison to the conventional capital assets pricing model. Moreover, the multi-stage type1 model, which is a combination of Fama and French predicted stock returns and a value-based management model, gives more accurate results for the stock market decision-making process for investment or divestment decisions, as well as for observing variation in and the behaviour of stock prices on the Saudi stock market. Furthermore, the study also designed a graphic user interface in order to simplify the decision-making process based upon Fama and French and value-based management, which might help Saudi investors to make investment decisions quickly and with greater precision. Finally, the study also gives some practical implications for investors and regulators, along with proposing future research in this area.

This dissertation addresses the fundamental question of what factors drive equity prices and investigates the mechanisms through which the drivers influence the price dynamics. The studies are based on the two different frequency levels of financial data. The first part aims to identify what systematic risk factors affect the expected return of stocks based on historical data with frequency being daily or monthly. The second part aims to explain how the hidden supply-demand of a stock affects the stock price dynamics based on market data observed at frequency levels generally between a millisecond and a second. With more and more financial market data becoming available, it greatly facilitates quantitative approaches for analyzing asset price dynamics and market microstructure problems. In the first part, we propose an econometric measure, terms as modularity, for characterizing the cluster structure in a universe of stocks. A high level of modularity implies that the cluster structure of the universe of stocks is highly evident, and low modularity implies a blurred cluster structure. The modularity measure is shown to be related to the cycle of the economy. In addition, individual stock's sensitivity to the modularity measure is shown to be related to its expected return. From 1992 to 2011, the average annual return of stocks with the lowest sensitivity exceeds that of the stocks with highest sensitivities by approximately 7.6%. Considerations of modularity as an asset pricing factor expand the investment opportunity set to passive investors. In the second part, we analyze the effect of hidden demands/supplies in equity trading market on the stock price dynamics. We propose a statistical estimation model for average hidden liquidity based on the limit orderbook data. Not only the estimated hidden liquidity explains the probabilistic property in market microstructure better, it also refines the existing price impact model and achieves higher explanation powers. Our enhanced price impact model offers a base for devising optimal order execution strategies. After we develop an optimal execution strategy based on the price impact function, the advantage of this strategy over benchmark strategies is tested on a simulated stock trading model calibrated by historical data. Simulation tests indicate that our strategy yields significant savings in transaction cost over the benchmark strategies.

Efficient Market Hypothesis (EMH) has been the central assumption of financial modelling in the previous decades. At its core, it is a statement about the efficient incorporation of available information in the prices of assets, rendering each price a 'true' representation of the asset's intrinsic value. The notion of informationally efficient financial markets has been, since its formulation, entrenched in the very core of our understanding of how asset pricing works, yet, with ever so increasing frequency, when subjected to empirical scrutiny, it fails to prove its explanatory and predictive prowess. New academic strands emerged have emerged as a result, attempting to explain those empirical short-comings, with rather mixed results. The new models and theories often either explain a singular anomaly, rather than pro- viding a generalized and consistent theoretical framework, or are exclusive with the general state of financial markets, which tends to be efficient and rational. This thesis shall explore the relationship of information and financial mar- kets, taking into account developments that have occurred since the inception of the EMH. Subsequently it will present a new theoretical model for asset pric- ing and ipso facto the efficiency of financial markets, based on meta-analysis of information, along...

Chapter 1: Intuition suggests that constraint investment strategies will result in losses due to a limited portfolio allocation. Yet prior research has shown that this is not the case for a particular set of constraint mutual funds so-called Socially Responsible Investing, SRI. In this paper I show that such assets do face loses to portfolio efficiency due to their limited asset universe. I contribute to the literature by employing two techniques to estimate asset performance. First, I estimate a DEA based efficiency score that allows for direct comparison between ex-post efficiency rankings and test the ex-ante relevance of such scores by including them into asset pricing models. Second, I further check if these results are consistent when comparing the performance of ethical funds based on the alphas of traditional asset pricing models even after adjusting for coskewness risk. Overall, the results suggest that ethical funds underperform traditional unconstraint investment assets. Chapter 2: Starting after the turn of the millennium, inflation has been persistently higher than the short term T-Bill rate. Following the traditional view, this will imply a negative real rates of return that have become commonplace in the US economy. This paper examines the possibility that if an inflation risk discount contained in nominal rates exist and can explain low or negative real rates, using consumption based asset pricing model. Evidence suggests using the traditional Fisher equation to calculate real rates leads to an overestimate of real rates due to a modest inflation risk premium. To achieve non-negative real rates in a consumption based asset pricing framework the covariance between consumption growth and inflation innovations would have to be at least thirty times larger than empirically found, and in opposite direction, for the Post-Volker era. Still, though the after 2000’s covariance is positive, which suggest a discount on risk free, the magnitude is still too small to explain negativity of real rates. JEL Classification : E21, E31 Key Words : Mutual Funds, Performance, Data Envelop Analysis, Coskewness, Risk Factors, Real Returns, Consumption Bases Asset Pricing Models, Inflation

With background to recent price growth in Swedish real estate and consequently real estate stocks, our aim is to examine the relationship between real estate price development and real estate stock price development. To test our hypothesis, that real estate price development have had an impact on the return of real estate stocks, we built a capital asset pricing model. We divide the return of real estate stocks into two parts, the return in relation to the Swedish market premium and the excess return that is given for the exposure of the real estate market. We found that real estate exposure would treat the investor with an additional return beyond the return given from stock market exposure; hence, real estate price development has contributed to real estate stock returns.

Fads models for stocks under asymmetric information in a purely continuous(GBM) market were first studied by P. Guasoni (2006), where optimal portfolios and maximum expected logarithmic utilities, including asymptotic utilities for the informed and uninformed investors, were presented. We generalized this theory to Lâevy markets, where stock prices and the process modeling the fads are allowed to include a jump component, in addition to the usual continuous component. We employ the methods of stochastic calculus and optimization to obtain analogous results to those obtained in the purely continuous market. We approximate optimal portfolios and utilities using the instantaneous centralized and quasi-centralized moments of the stocks percentage returns. We also link the random portfolios of the investors, under asymmetric information to the purely deterministic optimal portfolio, under symmetric information. / by Winston S. Buckley. / Thesis (Ph.D.)--Florida Atlantic University, 2009. / Bibliography: leaves 268-272.