>Magister Scientiae - MSc / In this thesis, we discuss methods for optimising the expected rate of return of a portfolio with minimal risk. As part of the work we look at the Modern Portfolio Theory which tries to maximise the portfolio's expected rate of return for a cer- tain amount of risk. We also use Quadratic Programming to optimise portfolios. Generally it is recognised that portfolios with a high expected return, carry higher risk. The Modern Portfolio Theory assists when choosing portfolios with the lowest possible risk. There is a nite number of assets in a portfolio and we therefore want to allocate them in such a way that we're able to optimise the expected rate of return with minimal risk. We also use the Markowian approach to allocate these assets. The Capital Asset Pricing Model is also used, which will help us to reduce our e cient portfolio to a single portfolio. Furthermore we use the Black-Litterman model to try and optimise our portfolio with a view to understanding the current market conditions, as well as considering how the market will perform in the future. An additional tool we'll use is Value at Risk. This enables us to manage the market risk. To this end, we follow the three basic approaches from Jorion [Value at Risk. USA: McGraw-Hills, 2001]. The Value at Risk tool has become essential in calcu- lating a portfolio's risk over the last decade. It works by monitoring algorithms in order to nd the worst possible scenarios within the portfolio. We perform several numerical experiments in MATLAB and Microsoft Excel and these are presented in the thesis with the relevant descriptions.

This thesis deals with the issue of investment decision. The goal of thesis is to evaluate for the company owners optimal investment variant of predetermined investment opportunities. Thesis is divided into theoretical-methodological part, which summarizes all the methods and procedures and practical part. The practical part consists mainly of net present value calculations, which chosen input data will be afterwards analyzed by sensitivity test. Application of these apparatuses will reveal the best investment opportunity, respectively their combination

The Black-Scholes model quickly been used in practice for pricing options in spite of its restrictive assumptions it is based on. Its robustness and especially its simplicity in calculating the option price has speeded this development. During the following years the main focus of scientific work has been empirical testing and analysing consequences of hurting model assumptions. The real functionality of the model - especially the practical execution of arbitrage process that shall guaranty Black-Scholes price - has never been questioned in scientific literature. The Arbitrage process is analysed in this work, resulting in serious doubts about the practical application of the Black-Scholes model. In the case of option mispricing not only the option price itself yet its partial deriviation have to be known in order to realise the arbitrage process. Furthermore arbitrage profits are very small compared with the deviation from Black-Scholes price, thus under the consideration of the transaction costs predicted intervals of arbitrage free option prices may be as high as the Black-Scholes model seems insuitable to value exchange traded options. A CAPM-based option pricing model is developed as an alternative to the Black-Scholes model. The Black-Scholes assumptions have been used almost unchanged and only one additional assumption regarding the utility function of market participients has been made to develop the model. The created model is a generalization of the Black-Scholes model as the Black-Scholes model is one special case of the created model. The CAPM-based approach proves its superiority to the Black-Scholes model in an empirical test of Eurex-traded DAX-calls and moreover the model can explain theoretically Black-Scholes anomalies such as Volatility Smile. / Das Black-Scholes-Optionsbewertungsmodell wurde trotz seiner sehr restriktiven Modellannahmen schnell in der Praxis eingesetzt - seine Robustheit und vor allem die Einfachheit der Berechnung stellten dabei die Haupttriebfeder dar. Das Hauptaugenmerk der wissenschaftlichen Diskussion der folgenden Jahre lag neben der empirischen Überprüfung vor allem in der Untersuchung der Auswirkung der Verletzung seiner Modellannahmen. Die eigentliche Funktionsweise des Modells - insbesondere die praktische Umsetzbarkeit des Arbitrageprozesses, der den Black-Scholes-Preis garantieren soll - wurde hingegen in der Literatur nie in Frage gestellt. In der vorliegenden Arbeit wird dieser Arbitrageprozesses analysiert, mit dem Ergebnis, daß erhebliche Zweifel an der Praxistauglichkeit des Black-Scholes-Modells angebracht sind. So muß z.B. bei einer Fehlbewertung der Option nicht nur der Optionspreis selbst, sondern auch die Ableitungen des fehlbewerteten Optionspreises bekannt sein, um die Arbitrage auch tatsächlich durchführen zu können. Darüber hinaus sind die bei einer Fehlbewertung zu realisierenden Arbitragegewinne im Verhältnis zur Abweichung vom Black-Scholes-Preis sehr gering, so daß die unter Berücksichtigung von Transaktionskosten ermittelten arbitragefreien Intervalle für den Optionspreis so groß werden können, daß das Black-Scholes-Modell für die Anwendung zur Optionsbewertung an den Börsen ungeeignet erscheint. Als Alternative zum Black-Scholes-Modell wird ein CAPM-basiertes Optionsbewertungsmodell hergeleitet. Dabei werden die Annahmen des Black-Scholes-Modells fast unverändert über-nommen und es wird nur eine zusätzliche Annahme an die Nutzenfunktion der Wirtschaftssubjekte gestellt. Das hergeleitete Modell stellt dabei eine Verallgemeinerung des Black-Scholes-Modells dar, da es dieses immer noch als Spezialfall beinhaltet. In der empirischen Untersuchung anhand der DAX-Calls an der Eurex erweist sich das CAPM-basierte Optionspreismodell dem Black-Scholes-Modell als eindeutig überlegen und kann darüber hinaus noch dessen Anomalien wie das Volatility Smile modelltheoretisch erklären.

<div>In the first chapter, our empirical tests use data from three sources. First, we obtain the Loughran and McDonald’s (hereafter LM wordlist) positive/negative wordlist and from the authors’ website. Second, we obtain the monthly Fama and French (1993 and 2015) factors (i.e. SMB, HML, Rm-Rf, CMA, and RMW) and momentum factor (MOM) from Kenneth French’s website for the sample period January 1994 through December 2016. Third, we obtain the monthly stock returns, monthly index returns, month end market value from the Center for Research in Security Prices (CRSP) as well as accounting information such as annual book</div><div>I the second chapter, we utilize five main datasets in this study. The first dataset is the stock market transaction level data for S&P 500 stocks, obtained from Trades and Quote (TAQ). The second dataset is the corporate bond transaction data from Trade Reporting and Compliance Engine (TRACE) through Wharton Research Data Services (WRDS) for the S&P 500 firms. The TRACE data provides over the counter (OTC) corporate bond market real-time prices.To examine the price discovery of bonds in equity prices we use a sample period of over 1,000 trading days from January 2004 through December 2008.</div><div>Our third data source is the institutional level transaction data from ANcerno, which provides transactional level trade data for corporate bonds and stocks for the first quarter of 2006 through the third quarter of 2010. Several studies have used equity transaction dataset to examine the ANcerno institutional trading behavior. See for example Puckett and Yan (2011), Bethel, Hu and Wang (2009), Chemmanur, He and Hu (2009), Goldstein, Irvine, Kandel and Wiener (2009). Additionally, Hu, Jo, Wang and Xie (2018) provide a comprehensive review of ANcerno dataset. The fourth source of data comes from Mergent Fixed Income Security Database (FISD), which provides details of bond characteristics and credit ratings from standard and poor’s (S&P) and Moody’s. Finally, we obtain the daily stock returns data from center for security prices (CRSP) database and match it with the daily bond returns to examine the lead-lag relationships.</div><div><br></div>

Companiesissuing insurance cover, in return for insurance premiums, face the payments ofclaims occurring according to a loss distribution. Hence, capital must be heldby the companies so that they can guarantee the fulfilment of the claims ofeach line of insurance. The increased incidence of insurance insolvencymotivates the birth of new legislations as the European Solvency II Directive.Companies have to determine the required amount of capital and the optimalcapital allocation across the different lines of insurance in order to keep therisk of insolvency at an adequate level. The capital allocation problem may betreated in different ways, starting from the insurance company balance sheet.Here, the running process and efficiency of four methods are evaluated andcompared so as to point out the characteristics of each of the methods. TheValue-at-Risk technique is straightforward and can be easily generated for anyloss distribution. The insolvency put option principle is easily implementableand is sensitive to the degree of default. The capital asset pricing model isone of the oldest reliable methods and still provides very helpful intermediateresults. The Myers and Read marginal capital allocation approach encouragesdiversification and introduces the concept of default value. Applications ofthe four methods to some fictive and real insurance companies are provided. Thethesis further analyses the sensitivity of those methods to changes in the economiccontext and comments how insurance companies can anticipate those changes.

If more people are starting to invest, then the focus on the effective markethypothesis will increase. The hypothesis's basic idea is that stock pricesalready reflect all available information and outperforming the marketthrough investment strategies is not possible. This study presents how twoinvestment strategies, CAN SLIM and Peter Lynch, has performed on andagainst the S&amp;P 500 under a 10 year period. The result of the study showsthat the efficient market hypothesis does not hold and that an excess returncompared to the market is possible. Between the investment strategies therewas a comparison and analysis regarding the Sharpe ratio and the CapitalAsset Pricing Model. Conclusively, the study shows that CAN SLIM is thestrategy that has performed the best under the period that the study is basedon.

Denna studie undersöker om periodiseringskvalitet är en prissatt riskfaktor för nordiska företag som är noterade på en reglerad marknad under perioden 2010–2019. Tidigare studier menar att periodiseringskvalitet utgör en proxy för informationsrisk, men olika författare framställer olika slutsatser i frågan huruvida periodiserings­kvalitet är en prissatt riskfaktor eller inte. Med den av McNichols (2002) modifierade Dechow &amp; Dichev modellen (2002) mäter vi periodiseringskvalitet som standard­avvikelsen av residualer från regressioner som kopplar periodiseringar till kassaflöden. Vi mäter riskpremien genom att dela in företagen i kvintiler baserad på periodiseringskvalitet och tillämpar en likaviktad portfölj som säljer företagen i de två kvintilerna med högst periodiseringskvalitet och köper företagen i kvintilerna med lägst periodiseringskvalitet. Vi finner en signifikant negativ koefficient i en två-stegs tvärsnittsregressionen som visar att periodiseringskvalitet inte utgör en prissatt riskfaktor för nordiska företag. / This study investigates if accruals quality is a priced risk factor for Nordic countries being traded on a regulated market in the Nordic countries during 2010–2019. Earlier studies argue that accruals quality is a proxy for information risk, but different authors find different results regarding whether accruals quality is a priced risk factor or not. By using the Dechow &amp; Dichev model (2002), modified by McNichols (2002), we measure accruals quality as the standard deviation of regressions that match accruals to cash flow. We measure the risk premium by dividing the entities into quintiles and use an equal-weighted portfolio that sells the stocks in the two quintiles with the highest accruals quality and buys the two quintiles with the lowest accruals quality. We find a significant negative coefficient in a two-stage cross-sectional regression which shows that accruals quality is not a priced risk factor in the Nordic countries.

During the recent years, the Swedish housing market has developed into a topic of major interest, both domestically and internationally. The sky-rocketing prices, the uprising demand together with the housing shortage, and the market bubble ongoing debate, have resulted in the discussion of risk being more relevant than ever before. Literature is vast and knowledge is still gained, as recent research is seeking for answers about where the market is headed towards. This study intends to provide a new perspective regarding risk as a factor in the housing market. Based on the classical portfolio theory, an asset pricing approach in the Swedish housing market is presented. By applying modern quantitative methods, this thesis analyses the results of several models in the Swedish housing market and tries to establish a relationship between different market segments and the overall market. The goal is to determine: (1) the risk factor reflected by the market segments towards the overall market, (2) the evolution of the risk factor through time, (3) the way the market segments affect and cause each other, and finally (4) the response of the market segments against market shocks. The results provide a new insight on the risk factor and the mechanics defining the Swedish housing market. This could work as a useful tool in a new approach regarding the real estate market analysis, from a developer’s perspective. / Under de senaste åren har den svenska bostadsmarknaden utvecklats till ett ämne av stort intresse, både nationellt och internationellt. Skyhöga prisökningar, en ökande efterfrågan i relation till bostadsbrist, till den pågående debatten om marknadsbubblor har resulterat i diskussioner om att risken är högre än någonsin tidigare. Litteraturen är stor på området men mer kunskap inhämtas hela tiden eftersom aktuell forskning fortfarande söker svar på frågan om vart marknaden är på väg. Denna studie avser att ge ett nytt perspektiv av riskfaktorn på bostadsmarknaden. Baserat på den klassiska portföljteorin presenteras en prissättningsstrategi för den svenska bostadsmarknaden. Genom att tillämpa moderna kvantitativa metoder analyserar denna avhandling resultaten från flera modeller på den svenska bostadsmarknaden och försöker upprätta en relation mellan olika marknadssegment och den övergripande marknaden. Målet är att bestämma: (1) riskfaktorn reflekterad av marknadssegmenten gentemot den övergripande marknaden, (2) riskfaktorns utveckling över tid, (3) hur marknadssegmenten påverkar varandra och slutligen (4) marknadssegmentens reaktion mot marknadschocker. Resultaten ger en ny inblick i riskfaktorn och mekaniken som definierar den svenska bostadsmarknaden. Detta kan fungera som ett användbart verktyg i en ny metod för fastighetsmarknadsanalys från en fastighetsutvecklares perspektiv.

Value creation in any stock market is a highly discussed topic with an abundant amount of generalized models aiming to predict future returns. Although no such tool exists yet there are, however, acknowledged models from peer-reviewed journals that have received a lot of attention over the years in examining company performance. This thesis is therefore built on the well-known Fama-French three-factor model. The original Fama-French three-factor model is extended by adding a new size premium and a new value premium, both based upon the spread between the return on invested capital (ROIC) – the weighted average cost of capital (WACC). The purpose of this is to make the returns of a portfolio account for cash flow and debt on top of risk, size, and value premium for a company. This thesis finds that the ROIC-WACC spread adds explanatory power to the existing Fama and French three-factor model on the Swedish stock market. The research method of this study is quantitative and deductive. The considered period is six years between the years 2014 and 2020.

We derive and test a series of profitability factors for cross-section of expected returns on Japanese and Chinese equity markets. We find gross profitability predicts returns and significant both on Japanese and Chinese equity markets. We test these factors using Fama-MacBeth regression and find gross profitability and value portfolios perform better in Japan, size and gross profitability portfolios perform better in China. Then we create new three-factor model based on the result of 5*5 portfolios, which capture value and gross profitability premium in Japan, and, size and gross profitability premium in China. And the new models' GRS test performs better than Fama-French-three-factor model at the 5% significance level. / 博士(文化情報学) / Doctor of Culture and Information Science / 同志社大学 / Doshisha University