Existing leadership theories and applied resources contain bountiful lists of recommended behaviors for leaders to employ, yet an integrated model that produces the most efficient set of leader behaviors does not currently exist. A standard, quantitative method to compare and contrast leader behaviors is needed to siphon utility from each resource, leading to an integrated and diversified set of optimal behaviors for leaders to consider. Leaders have limited time and need a reliable method to make informed behavioral decisions that consistently produce the most positive effects on the desired outcome. Unfortunately, leaders do not have the time to sift through the plethora of literary resources to uncover an optimal list of behavioral options. Leaders need to know what behavior to employ, when to employ it, the expected outcome, and the potential risk. Interestingly, these behavioral variables are also common to investors in the financial arena, where the principles of Modern Portfolio Theory (MPT) are often used to decipher the most optimal portfolio from a daunting list of investment options. The primary purpose of this study was to adopt some of the basic principles behind MPT in order to propose a similar quantitative Leader Behavior Portfolio Model, which determines an integrated and optimal set of effective leader behaviors. During this research, the proposed model was populated with archival performance data on over 5,000 cadets at the United States Military Academy. The outputs were then used to construct and administer surveys to 255 ROTC cadets in order to validate the model. The results of the survey response data were consistent with the outputs from the Leader Behavior Portfolio Model, showing strong support for adopting the principles of MPT to create an optimal set of leader behaviors.

Magister Commercii - MCom / The notion of market efficiency posits that stock prices fully reflect all available information in a timely manner. The efficient market hypothesis (EMH) proposed by Fama (1970) systematically rules out the profitability of information driven investing, and implicitly promulgates a passive market capitalisation weighted investment strategy such as indexing. The appeal of passive strategies has largely been driven by the growth of passive tracking instruments, which allow investors to earn underlying index performance by purchasing a single security such as an exchange traded fund (ETF). On the contrary, proponents of behavioural finance suggest that investors are irrational and subject to psychological biases. Furthermore, the noisy market hypothesis of Siegel (2006) asserts that the deviations from the economic ideal of rationality proposed by the EMH, introduces noise in the market which could lead prices to deviate from their intrinsic values. The resultant drag in performance of market capitalisation weighted indices suggests that the optimal cap-weighted market portfolio promulgated by the modern portfolio theory (MPT) of Markowitz (1952), ceases to be the most mean-variance approach to asset allocation. With the goal of testing the applications of ETF’s, this study first evaluates the performance of passive sector ETF’s in the global equity market. In addition, motivated by the potential inefficiencies of capweighted portfolios, the study tests optimisation based asset allocation techniques, and technical analysis based market timing strategies. The study employs the S&P Global 1200 sector indices and their respective sector ETF’s to test their performances and applications in passive and active investment strategies, over the period from July 5th, 2002 to February 6th, 2015. The ETF’s are evaluated based on their tracking ability and price efficiency. All 10 sector ETF’s possess insignificant tracking errors and successfully replicate the performance of their underlying indices. In addition, the globalsector ETF’s are not price efficient over the study period, as they possess persistent price deviations from their net asset values (NAV’s). Furthermore, the ETF trading strategy based on the relationship between ETF returns and price deviations, proves to be effective in outperforming the passive buy and hold strategy in the majority of the sectors. The sector decomposition of the cap-weighted S&P Global 1200 index which is employed as the market proxy, reveals that its sector allocation remains fairly stable throughout the study period. In contrast, the optimal historical sector composition incurs large changes in sector exposure from year to year and provides substantially superior performance relative to the cap-weighted market portfolio. The cap-weighted portfolio tends to overweight cyclical sectors and underweight resilient sectors during major economic downturns. The long-only, long-short and market neutral strategies developed from the S&P Global 1200 index and its constituent sector indices provide exceptional risk-adjusted performance, and more meanvariance efficient portfolios than the cap-weighted market proxy. The relaxation of the longonly constraint also improves the optimised portfolios risk-adjusted performance, mainly through risk reduction benefits. The performance of the optimised global sector based portfolios also resembles the performances of the global style based optimised portfolios developed by Hsieh (2010), thereby suggesting that the two approaches are analogous. The 3 technical market timing strategies tested in this research provide varying results. The sector momentum portfolios experience significant positive returns during bull markets, however the portfolios incur significant drawdowns during periods of economic turmoil such as the 2008 global financial crisis. As a result, all sector momentum portfolios provide inferior risk-adjusted returns relative to the passive cap-weighted buy and hold strategy. The exponential moving average (EMA) trend timing strategy promulgated by Hsieh (2010) provides impressive risk-management attributes and superior risk-adjusted performance relative to passive buy and hold benchmarks. Similarly, the alternative technical charting heuristics trend timing strategy helps reduce drawdowns during market crashes, however the charting strategy provides inferior cost and risk-adjusted performance relative to the capweighted buy and hold approach due to larger timing errors and longer hedging periods in comparison to the EMA strategy. In addition, the global tactical sector allocation (GTSA) model tests the EMA and technical charting trend timing tools in the context of a global sector portfolio, and the model provides outstanding cost and risk-adjusted performances relative to the passive investing alternatives. The portfolio based GTSA model highlights the benefits of portfolio diversification and successfully hedges market exposure during economic downturns.

The objective of this thesis is to apply alternative multi-objective optimization techniques to the portfolio selection problem. Theoretical part starts with detailed analysis of the classical Markowitz model and its assumptions. Following that, introduction of multi-criterion optimization techniques available for finding non-dominated portfolios is given. One of these techniques, the genetic algorithm, is presented in great detail. Some of the basic methods useful for predicting stock prices and its risks are presented at the end of the theoretical part. Practical part presents an application of the theory to the problem of constructing efficient portfolios of 11 selected stocks traded on Prague Stock Exchange. Results achieved by different approaches are compared and interpreted.

To add to the tools currently available to combat income inequality in the United States an investment fund type is proposed, justified, described, and created using historical asset returns from 1960 to 2015. By focusing on two socio-economic indicators of poverty, inflation and unemployment rates, this fund, when marketed to investors who live near, at, or below the poverty line, seeks to increase returns during times of increased strain on the economies of the poor. Multiple hurdles are proposed and affirmatively answered to this end and a fund type and corresponding four factor model that realized hypothetical excess returns fitting the requirements of a successful investment strategy was developed and evaluated. With the increasing importance of socially responsible investment practices an investment bank who maintains a fund of this type could potentially see financial and reputational benefits.

Pengar har under en lång tid spelat en central roll i människans samhälle och dagens samhälle präglas av allt mer handel. Utifrån detta har nya betalningsmetoder utvecklats. En förändring i konsumentbeteendet har bidragit till att allt fler individer väljer elektroniska betalningstjänster. En relativt ny innovation är kryptovalutan bitcoin som erbjuder betalning mellan köpare och säljare utan inblandning av en tredje part. Ett flertal studier har gjorts med syftet att fastställa om bitcoin är en valuta eller en tillgång, något som visat sig vara svårt. Något som varit tydligare är att bitcoins värdeförändringar inte tycks vara korrelerad med andra investeringsalternativ. I en studie av Brière et al. (2015) drogs slutsatsen att bitcoin är en intressant tillgång för en investerare tack vare bitcoins låga korrelationskoefficient med andra tillgångar. Denna studie grundar sig i de teoretiska utgångspunkterna om Famas (1970) hypotes om den effektiva marknaden, Markowitz (1952) moderna portföljteori och Rogers (2003) teori om spridning av innovationer. Med detta som utgångspunkt är syftet med denna studie att undersöka hur korrelationskoefficienten mellan bitcoin och traditionella investeringstillgångar som aktier, valutor och råvaror ser ut idag samt hur dessa har förändrats över tid. Med hjälp av Famas (1970) teori om effektiva marknader och Rogers (2003) teori om spridning av innovationer kommer en diskussion om huruvida bitcoins egenskaper som investering i den moderna portföljen har förändrats i takt med att bitcoin blivit mer använd, både som betalningsmedel och investeringsalternativ. För att besvara dessa frågor undersöks korrelationskoefficienterna mellan bitcoin och elva andra tillgångar i kombination med en analys av en deskriptiv statistik. Med en undersökningsperiod som sträcker sig från 18 augusti 2011 till 17 mars 2017. Denna period har även delats upp i mindre tidsperioder för att utifrån detta analysera om det skett några förändringar i korrelationen mellan bitcoin och de traditionella tillgångarna i studien. Resultatet visade att bitcoin inte är korrelerad med andra traditionella tillgångar, oavsett vilken tidsperiod som undersöks. Det visade sig att bitcoin i förhållande till andra tillgångar är en riskfylld investering på grund av bland annat en hög volatilitet. Dock kompenseras detta av bitcoins höga årlig avkastning. Av resultatet framgår det även att volatiliteten för bitcoin har minskat med tiden och att kryptovalutan inte är lika riskfylld idag jämfört med tidigare.

Increasing awareness of sustainable issues is just one of the ways how modern society has evolved. Due to the growing challenges faced by climate change and societal issues, our world has grown to be more innovative in the fight and support towards initiatives that will contribute to the long-term of the world we live in. Capitalists have exploited the resources, and as such, it is the economy where we can make the most significant changes to reverse the negative consequences. Responsible investment has incorporated various financial tools oriented towards the support of environmental, societal, and governance practices to revert the adverse effects brought on by capitalism. Sustainable bonds are a type of fixed income financial tool to support responsible investment practices. Their motive is to drive the financing of projects oriented towards positively contributing to the environment, society, and governance.   Previous studies on the field of responsible investment have covered the topic of green bonds and, most recently, social bonds. Although this field is relatively new, much of the literature developed has focused on the financial returns of such fixed-income assets. This thesis is the first to attempt the study of a self-created Swedish Sustainable Bond index consisting of 156 sustainable bonds issued in the Swedish market in correlation to three other asset classes. General interests and a lack of research due to its contemporary issuance in this context brought us to study such relation of return characteristics with its conventional bond counterpart, the equity market, and the energy stock section all within the Swedish market. The objective, as such, was to determine whether such an instrument could be used as a diversification tool.   For us to be able to conduct this study, we utilized the returns of each category’s indices. We applied different statistical models and tests, including correlation, univariate, and multivariate GARCH models, to be able to ensure robust results that could yield thought-provoking results for us to analyze. In conjunction with the Modern Portfolio Theory, we were able to determine that sustainable bonds provide investors with some diversification benefit by a positive correlation with the conventional bond and negative correlations with the equity and energy stock market. Volatility clustering and spillover effects within the Swedish sustainable bonds and the identified markets were also present.   We went a step ahead and curious to explore whether the conventional bond market was better off than the sustainable bond market. Such results indicate that the conventional bond is still a better tool for diversification purposes with the other two asset classes selected in comparison to the Swedish Sustainable Bond. As such, we are still wishful that sustainable bonds could potentially change their behavior in the future as a diversification tool, as more regulations and standardization of such asset classes are implemented.

This diploma thesis deals with optimization models of financial risks. The first part, which is devoted to the theoretical background, introduces the basic concepts of optimization, modern portfolio theory, fundamental and technical analysis and statistical background. The basic principles of operation of modern portfolio theory are presented. The methods for analysis and selection of assets called Growth at A Reasonable Price and portfolio optimization approach according to Harry Markowitz were used with selected methods. The practical part is focused on the data analysis, selection of assets and design of a portfolio optimization model according to selected conditions with an emphasis on minimizing investment risk. The used models examine the selected data and are solved using the MS Excel add-in Solver version.

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.

This thesis is focused on security portfolio optimalization using the value of stock screener. The theoretical section discusses the basic theory of markets, modern portfolio theory, diversification and the types of risks associated with financial activities, the basic steps to become an investor. The practical part is designed to build optimized stocks portfolio using the value of screening, its feigned purchase on New York Stock Exchange (NYSE), followed by monitoring the evolution rate of the portfolio thus created.

This thesis deals with design and implementation of an investment model, which applies methods of Post-modern portfolio theory. Particle swarm optimization (PSO) metaheuristic was used for portfolio optimization and the parameters were analyzed with several experiments. Johnsons SU distribution was used for estimation of future returns as it proved to be the best of analyzed distributions. The result is software application written in Python, which is tested for stability and performance of model in extreme situations.