Companies analyse large amounts of sensitive data on clusters of machines, using a framework such as Apache Hadoop to handle inter-process communication, and big data analytic tools such as Apache Spark and Apache Flink to analyse the growing amounts of data. Big data analytic tools are mainly tested on performance and reliability. Security and authentication have not been enough considered and they lack behind. The goal of this research is to improve the authentication and security for data analytic tools.Currently, the aforementioned big data analytic tools are using Kerberos for authentication. Kerberos has difficulties in providing multi factor authentication. Attacks on Kerberos can abuse the authentication. To improve the authentication, an analysis of the authentication in Hadoop and the data analytic tools is performed. The research describes the characteristics to gain an overview of the security of Hadoop and the data analytic tools. One characteristic is that the usage of the transport layer security (TLS) for the security of data transportation. TLS usually establishes connections with certificates. Recently, certificates with a short time to live can be automatically handed out.This thesis develops new authentication mechanism using certificates for data analytic tools on clusters of machines, providing advantages over Kerberos. To evaluate the possibility to replace Kerberos, the mechanism is implemented in Spark. As a result, the new implementation provides several improvements. The certificates used for authentication are made valid with a short time to live and are thus less vulnerable to abuse. Further, the authentication mechanism solves new requirements coming from businesses, such as providing multi-factor authenticationand scalability.In this research a new authentication mechanism is developed, implemented and evaluated, giving better data protection by providing improved authentication.

Introducing more intermittent renewable energy sources in the energy system makes the role of balancing power more important. Furthermore, an increased infeed from intermittent renewable energy sources also has the effect of creating lower and more volatile electricity prices. Hence, investing in balancing power is prone to high risks with respect to expected profits, which is why a good representation of electricity prices is vital in order to motivate future investments. We propose a stochastic multi-factor model to be used for simulating the long-run dynamics of electricity prices as input to investment valuation of power generation assets. In particular, the proposed model is used to assess the impact of electricity price dynamics on investment decisions with respect to balancing power generation, where a combined heat and power plant is studied in detail. Since the main goal of the framework is to create a long-term representation of electricity prices so that the distributional characteristics of electricity prices are maintained, commonly cited as seasonality, mean reversion and spikes, the model is evaluated in terms of yearly duration which describes the distribution of electricity prices over time. The core aspects of the framework are derived from the mean-reverting Pilipovic model of commodity prices, but where we extend the assumptions in a multi-factor framework by adding a functional link to the supply- and demand for power as well as outdoor temperature. On average, using the proposed model as a way to represent future prices yields a maximum 9 percent overand underprediction of duration respectively, a result far better than those obtained by simpler models such as a seasonal profile or mean estimates which do not incorporate the full characteristics of electricity prices. Using the different aspects of the model, we show that variations of electricity prices have a large impact on the investment decision with respect to balancing power. The realized value of the flexibility to produce electricity in a combined heat and power plant is calculated, which yields a valuation close to historical realized values. Compared with simpler models, this is a significant improvement. Finally, we show that by including characteristics such as non-constant volatility and spiky behavior in investment decisions, the expected value of balancing power generators, such as combined heat and power plants, increases. / I takt med att fler intermittenta förnyelsebara energikällor tillför el i dagens energisystem, blir också balanskraftens roll i dessa system allt viktigare. Vidare så har en ökning av andelen intermittenta förnyelsebara energikällor även effekten att de bidrar till lägre men också mer volatila elpriser. Därmed är även investeringar i balanskraft kopplade till stora risker med avseende på förväntade vinster, vilket gör att en god representation av elpriser är central vid investeringsbeslut. Vi föreslår en stokastisk flerfaktormodell för att simulera den långsiktiga dynamiken i elpriser som bas för värdering av generatortillgångar. Mer specifikt används modellen till att utvärdera effekten av elprisers dynamik på investeringsbeslut med avseende på balanskraft, där ett kraftvärmeverk studeras i detalj. Eftersom huvudmålet med ramverket är att skapa en långsiktig representation av elpriser så att deras fördelningsmässiga karakteristika bevaras, vilket i litteraturen citeras som regression mot medelvärde, säsongsvariationer, hög volatilitet och spikar, så utvärderas modellen i termer av årlig prisvaraktighet som beskriver fördelningen av elpriser över tid. Kärnan i ramverket utgår från Pilipovic-modellen av råvarupriser, men där vi utvecklar antaganden i ett flerfaktorramverk genom att lägga till en länkfunktion till tillgång- och efterfrågan på el samt utomhustemperatur. Vid användande av modellen som ett sätt att representera framtida priser, fås en maximal över- och underprediktion av prisvaraktighet om 9 procent, ett resultat som är bättre än det som ges av enklare modellering såsom säsongsprofiler eller enkla medelvärdesestimat som inte tar hänsyn till elprisernas fulla karakteristika. Till sist visar vi med modellens olika komponenter att variationer i elpriser, och därmed antaganden som används i långsiktig modellering, har stor betydelse med avseende på investeringsbeslut i balanskraft. Det realiserade värdet av flexibiliteten att producera el för ett kraftvärmeverk beräknas, vilket ger en värdering nära faktiska realiserade värden baserade på historiska priser och som enklare modeller inte kan konkurrera med. Slutligen visar detta också att inkluderandet av icke-konstant volatilitet och spikkarakteristika i investeringsbeslut ger ett högre förväntat värde av tillgångar som kan producera balanskraft, såsom kraftvärmeverk.

Актуальность исследования обуславливается тем, что банковская сфера в наше время является высоко конкурентной средой и в свете протекающей глобализации и консолидации финансового сектора наблюдается снижение количества частных банков, что вызвано, в свою очередь, процессами слияния, поглощения и неспособностью противостоять крупным агентам рынка, поддерживая необходимые требования, которые выставляются регуляторами. Финансовые институты вынуждены наращивать свой арсенал конкурентных преимуществ, активно использовать нераспределенную прибыль на формирование отличительных конкурентных факторов и заниматься мониторингом существующих предложений на рынке. Как следствие, кредитным организациям необходимо критически подходить к успехам и неудачам иностранных коллег, повышая эффективность банковского бизнеса, формируя собственные уникальные конкурентные преимущества. Целью диссертационной работы является оценка факторов повышения конкурентоспособности международного банка в разрезе сложившегося отечественного финансового сектора. Объектом диссертационного исследования выступает отечественный филиал АО «Райффайзенбанк». Предметом исследования является процесс формирования конкурентных преимуществ АО «Райффайзенбанк», система экономических, организационных и финансовых механизмов повышения эффективности деятельности банка. Результатами выпускной квалификационной работы являются разработка многофакторной модели формирования чистой прибыли, рекомендации по оптимизации существующих процессов и экономическая оценка эффектов от внедрения предлагаемых инструментов. / The relevance of the study stems from the fact that banking is a highly competitive environment and in light of the proceeding of globalization and consolidation of the financial sector, a decrease in the number of private banks, which caused, in turn, processes of mergers, acquisitions, and the failure to counter major market agents, while maintaining the necessary requirements that are set by regulators. Financial institutions are forced to increase their arsenal of competitive advantages, actively use retained earnings to form distinctive competitive factors and monitor existing offers on the market. As a result, credit institutions need to take a critical approach to the successes and failures of foreign colleagues, increasing the efficiency of the banking business, forming their own unique competitive advantages.

本研究考慮市場、規模、淨值市價比及前期累積報酬，這四個影響股票報酬的因子，分別以個股特徵之持股比例變動法與四因子評估模型，對共同基金風險調整後的報酬作績效評比，不但可以評估基金的選股能力與擇時能力，並進一步瞭解報酬之風險來源。最後討論這兩種評比方式的適用性，並藉由基準投資組合將市場股票區分成不同的風險類別，根據基金在各類別股票的持有比例，引伸出對基金持股風格的另一種看法。現將本篇研究結果整理如下： 1. 四因子模型對於資產的解釋能力比資本資產評價模型（CAPM）好；並且透過規模、淨值市價比、前期累積報酬之風險溢酬因子，可以瞭解報酬之不同風險來源。 2. 依照個股特徵為基準之持股比例變動法，計算出實際績效、特徵擇時、特徵選股及平均持股型態的績效。結果顯示共同基金多具有正的選股能力，擇時能力，但經過檢定，並沒有顯著的超額報酬。 3. 以四因子評價模型對共同基金績效做評估。結果發現幾乎不具有顯著的超額報酬；兩種方法的評比結果相類似。但是部份基金在規模、與前期累積報酬項有顯著異於零的結果，顯示基金在規模、量能操作上有穩定的績效表現，因此使得檢定的結果顯著。 4. 而以持股類型風格上來看，顯示部份基金會高度持有大型股、以及過去表現良好的股票，持股風險類群明顯而集中，屬於穩健、偏重長期，並配合量能操作的投資策略。 最後根據本文的實證結果，分別對投資人與基金經理人提出建議。而從持股比例計算的過程，對持股風格分析提供一個更簡易明瞭的看法，並將研究中發現的問題，一併列在建議中，提供給後續研究者作為參考。 第一章 緒論…………………………………………1 第二章 文獻回顧……………………………………4 第一節 風險調整因素……………………………4 第二節 四因子評估模型…………………………7 第三節 依個股特徵之持股比例變動法…………9 第三章 研究設計……………………………………13 第一節 研究假說…………………………………13 第二節 研究架構…………………………………14 第三節 研究範圍與期間…………………………16 第四節 變數定義與資料處理……………………18 第四章 實證結果與分析……………………………22 第一節 四因子評估模型…………………………22 第二節 共同基金績效評估………………………27 第三節 基金之持股類型比例……………………36 第五章 結論與建議…………………………………40 第一節 結論………………………………………40 第二節 建議…………………………………………41 參考文獻……………………………………………45

Investors constantly seek information that provides an edge over the market. One of the conventional methods is to find factors which can predict asset returns. In this study we improve the Fama and French Five-Factor model with Regime-Switches, student's t distributions and copula dependencies. We also add price momentum as a sixth factor and add a one-day lag to the factors. The Regime-Switches are obtained from a Hidden Markov Model with conditional Student's t distributions. For the return process we use factor data as input, Student's t distributed residuals, and Student's t copula dependencies. To fit the copulas, we develop a novel approach based on the Expectation-Maximisation algorithm. The results are promising as the quantiles for most of the portfolios show a good fit to the theoretical quantiles. Using a sophisticated Stochastic Programming model, we back-test the predictive power over a 26 year period out-of-sample. Furthermore we analyse the performance of different factors during different market regimes.

La plupart des études en gestion sur la performance des entreprises sont centréessur l'explication de la relation entre les facteurs internes ou des caractéristiquesintrinsèques de l'entreprise (niveau d'endettement, diversification des produits, lastratégie concurrentielle, etc.) et son performance. Cette thèse vise à déterminerquels sont les facteurs de risque exogènes qui ont un impact sur la performance desentreprises en République Dominicaine? Ces facteurs, affectent-ils différemment lesmicro, petites et moyennes entreprises en fonction de leur secteur d'activité. Quelest le risque pour chacun des plus représentatifs sous-secteurs des entreprisesDominicaines? Nous avons constaté que les facteurs de risque les plusstatistiquement significatifs sont les dépenses de consommation des ménages, letaux d'intérêt des banques commerciales, l'investissement total, le taux de changede DOP à USD et le déficit de la balance commerciale. La composition etl'importance des facteurs varient considérablement en fonction de la taille desentreprises et le sous-secteur auquel ils appartiennent. Les grandes entreprises sonten moyenne moins risqué que des moyennes, petites et micro entreprises, n’importequel que soit le sous-secteur auquel ils appartiennent. / Many of the management studies on the performance of the company are focusedon explaining the relationship between the internal factors or intrinsic characteristicsof the firm (debt level, diversification of products, competitive strategy, etc.) and itsperformance. This thesis seeks to determine, what are the exogenous risk factorsthat impact the performance of all companies in the Dominican Republic? Thesefactors differentially affect the micro, small and medium enterprises according to theirbusiness sector. What is the risk on each of the most representative sub-sectors ofthe Dominican companies? We found that the most statistically significant riskfactors are the household consumption expenditure, the interest rate of commercialbanks, the total investment, the DOP to USD exchange rate and the deficit on thetrade balance. The composition and importance of the factors significantly variesdepending on the size of the company and the sub-sector to which it belongs. Also,large firms are on average less risky than medium, small and micro regardless of thesub-sector they belong. / Muchos de los estudios de gestión sobre el performance de la empresa se enfocanen explicar la relación que existe entre los factores o características intrínsecas de laempresa (nivel de endeudamiento, diversificación de productos, estrategiacompetitiva, etc.) y el performance de la misma. Esta tesis busca determinar¿cuáles son los factores exógenos de riesgo que impactan el performance de lasempresas de la República Dominicana? Si estos factores afectan de forma diferentea la micro, pequeña y mediana empresa según su actividad empresarial. ¿Cuál es elriesgo que tiene cada uno de los sub-sectores más representativos de las empresasdominicanas? Encontramos que los factores de riesgo estadísticamente mássignificativos son el consumo de los hogares, la tasa de interés de los bancoscomerciales, la inversión total, la tasa de cambio de DOP a USD y el déficit en labalanza comercial. La importancia y composición de los factores varíasignificativamente según el tamaño de la empresa y el sub-sector al que pertenece.También, en promedio, las empresas grandes tienen menos riesgos que lasmedianas, pequeñas y micro sin importar al sub-sector que pertenezcan.