Investeringar i aktier eller aktiefonder kan få ens pengar att växa genom den kumulativa avkastning som genereras. Genom ränta-på-ränta-effekten kan en liten ökning i avkastning från dessa investeringar få en stor effekt över en lång tidsperiod. På grund av detta etablerar många investerare strategier för att försöka uppnå en högre avkastning än den generella aktiemarknaden. Att slå marknaden har historiskt sett varit svårt vilket går i linje med det rådande paradigmet om att marknader är effektiva. Empirisk forskning har dock visat på återupprepande prismönster, som inneburit att det funnits möjligheter att strategiskt och systematiskt investera för att generera en högre riskjusterad avkastning än marknaden. Dessa prismönster kallas för anomalier och när de är tidsbaserade benämns de vanligtvis som kalendereffekter. Syftet med studien var att undersöka huruvida kalendereffekter även varit förekommande på marknader med mindre utvecklade institutioner och begränsad tidigare forskning. Studien är avgränsad till aktiemarknader i Afrika och har ställts i relation till motsvarande marknader i några av västvärldens mest välutvecklade ekonomier. En jämförelse har gjorts för att undersöka vart och vilka kalendereffekter som funnits samt hur resultatet skiljer sig mellan Afrika och västvärlden. Studien omfattar en tidsperiod från år 2000 fram till 2020. Resultatet visar något vanligare och mer signifikanta kalendereffekter på de afrikanska marknaderna men inte någon annan tydlig övergripande skillnad vid jämförelse med de västerländska marknaderna. Långa positioner vid månadsskiftet och efterföljande dagar alternativt vid slutet av handelsveckan har kunnat ge en högre riskjusterad avkastning än den generella marknaden i flera länder. Under tidsperioden finns det således belägg för att överavkastning kunnat uppnåtts på ett flertal afrikanska aktiemarknader genom systematiskt planerade investeringar. / Investments in equities or equity funds can help to make your money grow through the cumulative returns generated. Through compound interest, a small increase in return on these investments can have a large effect over a long period of time, resulting in many investors establishing strategies to achieve a higher return than the general stock market. Beating the market has historically been difficult which supports the prevailing paradigm that markets are efficient. However, empirical research has shown recurring price patterns, implying that there have been opportunities to strategically and systematically invest to generate a higher risk-adjusted return than the market. These price patterns are called anomalies and when time-based, are usually referred to as calendar effects. The purpose of this study was to examine whether calendar effects were also present in markets with less developed institutions and limited previous research. The study is focused on stock markets in Africa, which have been compared to corresponding markets in some of the most developed economies in the Western world. A comparison has been made to examine where and what calendar effects existed and how the results differ between Africa and the Western world. The study covers a period from 2000 to 2020. The results show slightly more common and significant calendar effects in the African markets, but no other clear overall difference was observed when compared with the Western markets. Long positions at the end of the month and subsequent days, alternatively at the end of the trading week, have been able to produce a higher risk-adjusted return than the general market in several countries. Thus, during this time period, there is evidence that excess returns could have been achieved in a number of African stock markets through systematically planned investments.

The purpose of this investigation was to test the theoretical possibility of an investor earning a positive cash return from the activities of the stock market despite effectively holding no position at all in said market. The sample data were the daily returns for the shares of the 780 companies listed on the NASDAQ and the New York Stock Exchange (“NYSE”), which fell within the top 500 listed companies by market capitalisation between 1 January 2005 and 31 December 2017. The reversal strategy’s performance was evaluated using portfolios constructed as quantiles of 100 or 500 shares, respectively, where the investor had the option of implementing the reversal strategy immediately after an information-gathering period closed or a day thereafter. The time intervals used were 1 January 2005 to 29 September 2008 (the day the Dow Jones Industrial Average crashed by 777.68 points), 29 September 2008 to 31 December 2017 and 1 January 2005 to 31 December 2017. Of the 1000 portfolios tested in each time interval, at least 416 had positive average returns in every time interval. Of the portfolios that had positive average returns over the time intervals, at least 66 had statistically significant average returns in every time interval. The best-performing portfolio for the entire sample period was a combination of the best-performing pre-crash and post-crash portfolios - an investor who held that portfolio realised a cumulative return of approximately $61.39 for every $1 invested. The conclusion was that it was theoretically possible for an investor to earn a positive cash return from the market’s activities despite effectively holding no position at all in the market. Consequently, it was concluded that the strong form of Fama’s (1970) Efficient Market Hypothesis was disproved. Future research should include out-of-sample tests, tests that include restrictions on short selling and tests that consider the impact of trading costs on portfolio performance, to render the conclusions of this investigation more practically applicable to investors.

Aujourd’hui, il y a une demande croissante de fournir les informations d'environnement en temps réel tels que la qualité de l'air, le niveau de bruit, état du trafic, etc. pour les citoyens dans les zones urbaines a des fins diverses. La prolifération des capteurs de smartphones et la mobilité de la population font des Mobile Crowdsensing (MCS) un moyen efficace de détecter et de recueillir des informations a un coût faible de déploiement. En MCS, au lieu de déployer capteurs statiques dans les zones urbaines, les utilisateurs avec des périphériques mobiles jouent le rôle des capteurs de mobiles à capturer les informations de leurs environnements, et le réseau de communication (3G, WiFi, etc.) pour le transfert des données pour MCS applications. En général, l'application MCS (ou tâche) non seulement exige que chaque participant de périphérique mobile de posséder la capacité de réception missions de télédétection, de télédétection et de renvoi détecte résultats vers un serveur central, il exige également de recruter des participants, attribuer de télédétection tâches aux participants, et collecter les résultats obtenues par télédétection ainsi que représente les caractéristiques de la cible zone de détection. Afin de recruter un nombre suffisant de participants, l'organisateur d'une MCS tâche devrait considérer la consommation énergétique causée par MCS applications pour chaque participant et les questions de protection dans la vie privée, l'organisateur doit donner a chaque participant un certain montant des incitations comme un encouragement. En outre, afin de recueillir les résultats obtenues par télédétection et représentant la région cible, l'organisateur doit s'assurer que les données de télédétection qualité des résultats obtenues par télédétection, p. ex., la précision et la spatio-temporelle la couverture des résultats obtenus par télédétection. Avec la consommation d'énergie, la protection de la vie privée, les mesures d'incitation, de télédétection et qualité des données à l'esprit, dans cette thèse nous avons étudié quatre problèmes d'optimisation de mobile crowdsensing et mené après quatre travaux de recherche [...] / Nowadays, there is an increasing demand to provide real-time environment information such as air quality, noise level, traffic condition, etc. to citizens in urban areas for various purposes. The proliferation of sensor-equipped smartphones and the mobility of people are making Mobile Crowdsensing (MCS) an effective way to sense and collect information at a low deployment cost. In MCS, instead of deploying static sensors in urban areas, people with mobile devices play the role of mobile sensors to sense the information of their surroundings and the communication network (3G, WiFi, etc.) is used to transfer data for MCS applications. Typically, an MCS application (or task) not only requires each participant's mobile device to possess the capability of receiving sensing tasks, performing sensing and returning sensed results to a central server, it also requires to recruit participants, assign sensing tasks to participants, and collect sensed results that well represents the characteristics of the target sensing region. In order to recruit sufficient participants, the organizer of the MCS task should consider energy consumption caused by MCS applications for each individual participant and the privacy issues, further the organizer should give each participant a certain amount of incentives as encouragement. Further, in order to collect sensed results well representing the target region, the organizer needs to ensure the sensing data quality of the sensed results, e.g., the accuracy and the spatial-temporal coverage of the sensed results. With the energy consumption, privacy, incentives, and sensing data quality in mind, in this thesis we have studied four optimization problems of mobile crowdsensing and conducted following four research works: • EEMC - In this work, the MCS task is splitted into a sequence of sensing cycles, we assume each participant is given an equal amount of incentive for joining in each sensing cycle; further, given the target region of the MCS task, the MCS task aims at collecting an expected number of sensed results from the target region in each sensing cycle.Thus, in order to minimize the total incentive payments and the total energy consumption of the MCS task while meeting the predefined data collection goal, we propose EEMC which intends to select a minimal number of anonymous participants to join in each sensing cycle of the MCS task while ensuring an minimum number of participants returning sensed results. • EMC3 - In this work, we follow the same sensing cycles and incentives assumptions/settings from EEMC; however, given a target region consisting of a set of subareas, the MCS task in this work aims at collecting sensed results covering each subarea of the target region in each sensing cycle (namely full coverage constraint).Thus, in order to minimize the total incentive payments and the total energy consumption of the MCS task under the full coverage constraint, we propose EMC3 which intends to select a minimal number of anonymous participaNts to join in each sensing cycle of the MCS task while ensuring at least one participant returning sensed results from each subarea. • CrowdRecruiter - In this work, we assume each participant is given an equal amount of incentive for joining in all sensing cycles of the MCS task; further, given a target region consisting of a set of subareas, the MCS task aims at collecting sensed results from a predefined percentage of subareas in each sensing cycle (namely probabilistic coverage constraint).Thus, in order to minimize the total incentive payments the probabilistic coverage constraint, we propose CrowdRecruiter which intends to recruit a minimal number of participants for the whole MCS task while ensuring the selected participants returning sensed results from at least a predefined percentage of subareas in each sensing cycle. • CrowdTasker - In this work, we assume each participant is given a varied amount of incentives according to [...]

Background: The National Institute Mental Health (2015) estimated there were about 44.7 million people diagnosed with a serious mental illness and 62.9% of those diagnosed were without mental health services. The loss of services was due to unemployment, reoccurring hospitalization, inabilities to care for themselves, and lack of participation in societal norms (World Health Organization [WHO], 2014). According to Insel (2011/2015), the U.S. cost of mental healthcare was an estimated $57.5 billion in 2006. This cost was not due to actual care but associated with the economic burden of job loss and the excessive use of community resources. The Affordable Care Act (ACA) and the Mental Health Equality and Parity Act (MHEPA) has positively influenced access to mental healthcare, but healthcare coverage continues to be deficient. Insufficient clinical documentation practices decrease insurance reimbursement potential. Purpose: The purpose of this quality improvement project was to enhance the current clinical documentation practices and policies and increase insurance reimbursement in an adult psychiatric inpatient unit in a private, non-profit mental and behavioral health organization. Theoretical Framework: The Kurt Lewin’s 3 Step Change Management Theory Methods: A quantitative design guided this project utilized an investigator-developed tool modeled from the CMS Inpatient Unit Worksheet as a data collection tool from the clinical chart documentation reviews. Results: Fisher’s Exact and Chi square tests measured the cross tabulation of pre and post comparison sample frequency of staff’s integration of an evidence-based descriptive documentation method into practice. The results presented with statistical significance of the progress narrative notes. The declined chart claims a p <0.001, and the numbers related to case scenario utilization of the documentation method was p = 1.00. Conclusion: The relationship between descriptive clinical documentation and insurance reimbursement was evident in the usage of the Data, Assessment/Action, Response, and Plan (DARP) method in the clinical documentation progress narratives notes. There was a 24% improvement in insurance reimbursement claims and a 17% decrease in charts declined for the study period.

In spite of the well-accepted belief of the relationship between cash flow and stock price, there are some controversies about whether cash flow is a good value driver in terms of explaining the volatility of stock prices, when compared with other value drivers, such as earnings or dividends. Most of the previous studies that have focused on the relationship between stock price and cash flow have used cross-industries data, primarily S&P 500 index. These studies do not distinguish service industry from manufacturing industry. However, the service industry is different from manufacturing in many ways. These differences make cash play different roles in the daily operation between the service industry and the manufacturing industry. Given these factors, whether the relationship between stock price and cash flow identified in previous studies will hold in the casual theme restaurant industry is the question this study tries to answer. Therefore, a set of 20 casual theme restaurant companies are selected through the COMPUSTAT database as the sample of this study. In this study, the performance of cash flow, earnings and dividends helping to explain the stock price move will be compared and ranked under the setting of casual theme restaurants. This result will provide the management of casual theme restaurants a guideline, which explains how to maintain the stock price increase and minimize the volatility by monitoring the most important value driver of the industry. The methodology of this study will follow the traditional multiple valuation model. The logic of this model is to compare the pricing error of different value drivers and determine which one is the best. The results of this study show that operating cash flow outperformed earnings and dividends in the multiple valuation tests. This is different from the results of previous studies that earnings has the strongest explanatory power in the variance of share price. / Master of Science

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The main objective of this research is to build an interest based peer – to – peer network which is structured yet non-DHT. Maintaining DHTs is a complex task and needs substantial amount of effort to handle the problem of churn. So, the major challenge facing such architectures is how to reduce this amount of effort while still providing an efficient data query service. The rationale behind choosing non- DHT based interest based network is that users sharing common interests are likely to share similar contents, and therefore searches for a particular type of content is more efficient if peers likely to store that content type are neighbors. We have used a mathematical model based on modular arithmetic, specifically residue class (RC), to design a two-level structured architecture. To the best of my knowledge, there does not exist any such work that has used this mathematical model.

This thesis investigates how ESG ratings for Nordic companies vary between two ESG providers, and how the risk and expected return differs between two highly rated ESG portfolios according to the two providers. In doing so, we aim to contribute to research on the topic of ESG divergence as it is of great importance for investors that this subject is studied further. To achieve the purpose of this thesis, secondary data was gathered in terms of ESG ratings from two chosen providers, S&amp;P Global and Refinitiv. Based on the collected data, a Spearman correlation analysis was performed as well as statistical investigations in Excel in order to examine the rating divergence between the two providers. Additionally, efficient frontier values of the two provider dependent portfolios were calculated using R Studio. The results found suggests that there is an evident ESG rating divergence amongst all companies examined, regardless of origin and industry. Furthermore, it was concluded that Refinitiv consistently rated companies higher than S&amp;P Global. The comparison between the two provider dependent portfolios illustrates that relying on ESG ratings from different providers will result in different portfolio composition. In turn, this has an impact on investors seeking to implement ESG as a part of their investment strategy. The results indicate that the composition differences affects portfolio performance. This led to the conclusion that it is of great importance for investors to be aware of the existing divergence in order to make accurate investment decisions.