The aim of this thesis is to examine an empirical relationship between multifrac- tality of financial time series and its returns. We approach the multifractality of a given time series as a measure of its complexity. Multifractal financial time series exhibit repeating self-similar patterns. Multifractality could be a good predictor of stock returns or a factor which can be used in asset pricing. We expected that capturing the complexity of a given time series by a model, a positive or a negative risk premia for investing into "more multifractal assets" could be found. Daily prices of 31 stock indices and daily returns of 10-years US government bonds were downloaded. All the data were recorded between 2012 and 2021. After estimation the multifractal spectra, applying MF-DFA method, of all stock indices, we ordered all stock indices from the lowest to the most multifractal. Then, we constructed a "multifractal portfolio" holding a long position in the 7 most multifractal and holding a short position in the 7 least multifractal stock indices. Fama-MacBeth regression with market risk premia and multifractal variable as independent variables was applied. Multi- fractality in all examined financial time series was found. We also found a very low negative risk premia for holding "a multifractal...

The doctoral thesis is thematically focused to human operator systems significantly contributing to this system reliability and safety. The theoretical part of the thesis is concerned with human activities and communications in MMS system, valuation and estimation of human reliability probability in MSS. The important part of the thesis is also a description of human operator neuromuscular system as an executive powerful system on MMS system regulating activities and the summary of human driver models in compensative lateral car control. The practical part of the doctoral thesis is based on analyses created by experimental data of drives. Experimental drives were done on drivers set following different backgrounds and different sleep deprivation at whole day. All experimental data was realized from the cooperation and following the agreement of Faculty of Transportation Science research centre on Prague ČVUT. Another part of thesis includes driver simulation model proposals with nonlinear components for lateral car control. Simulation model drives are compared with real drives or drivers on drive-simulator and there are monitored identical and different dynamic movement characteristics. The main target of doctoral thesis is to detect and obtain significant dynamical drive experience characteristics based on experimental data analyses. As well to found drive characters variability owing to driver’s fatigue and determinated evaluated characteristics changes. Acquired results of thesis should help in assistant systems that in cooperation with other components alert to micro-sleep and run off drive possibility.

<p>Social engineering attacks, especially trust exploitation, have become a focus of attention</p> <p>for cybercriminals attempting to manipulate or deceive users to take actions that further</p> <p>expose their vulnerabilities. This has also become a budding field for researchers as these</p> <p>interactions are based on complex social equations that are constantly taken advantage of.</p> <p>Identifying the "weakest link" is a popular method of identifying how these exploits take</p> <p>place, generally by observing when individuals fall for a social engineering attack. However,</p> <p>valuable insights may be used to harden security by observing patterns in users resistant</p> <p>or vigilant to these attacks. Primarily, this trend may be discovered in resistant users’</p> <p>personality traits. This has been found to be a more accurate indicator of behavior than</p> <p>self-reported intentions. Survey responses (n=120) indicate correlations between high test</p> <p>scores in trust exploitation exercises and Conscientiousness in the Big 5 Personality Model</p> <p>(p<0.001). No significant correlation was seen between self-reported cybersecurity habits</p> <p>and actual security behavior.</p>

Factor models attribute stock returns to a linear combination of factors. A model with great explanatory power (R2) can be used to estimate the systematic risk of an investment. One of the most important factors is the industry which the company of the stock operates in. In commercial risk models this factor is often determined with a manually constructed stock classification scheme such as GICS. We present Natural Language Industry Scheme (NLIS), an automatic and multivalued classification scheme based on topic modeling. The topic modeling is performed on transcripts of company earnings calls and identifies a number of topics analogous to industries. We use non-negative matrix factorization (NMF) on a term-document matrix of the transcripts to perform the topic modeling. When set to explain returns of the MSCI USA index we find that NLIS consistently outperforms GICS, often by several hundred basis points. We attribute this to NLIS’ ability to assign a stock to multiple industries. We also suggest that the proportions of industry assignments for a given stock could correspond to expected future revenue sources rather than current revenue sources. This property could explain some of NLIS’ success since it closely relates to theoretical stock pricing. / Faktormodeller förklarar aktieprisrörelser med en linjär kombination av faktorer. En modell med hög förklaringsgrad (R2) kan användas föratt skatta en investerings systematiska risk. En av de viktigaste faktorerna är aktiebolagets industritillhörighet. I kommersiella risksystem bestäms industri oftast med ett aktieklassifikationsschema som GICS, publicerat av ett finansiellt institut. Vi presenterar Natural Language Industry Scheme (NLIS), ett automatiskt klassifikationsschema baserat på topic modeling. Vi utför topic modeling på transkript av aktiebolags investerarsamtal. Detta identifierar ämnen, eller topics, som är jämförbara med industrier. Topic modeling sker genom icke-negativmatrisfaktorisering (NMF) på en ord-dokumentmatris av transkripten. När NLIS används för att förklara prisrörelser hos MSCI USA-indexet finner vi att NLIS överträffar GICS, ofta med 2-3 procent. Detta tillskriver vi NLIS förmåga att ge flera industritillhörigheter åt samma aktie. Vi föreslår också att proportionerna hos industritillhörigheterna för en aktie kan motsvara förväntade inkomstkällor snarare än nuvarande inkomstkällor. Denna egenskap kan också vara en anledning till NLIS framgång då den nära relaterar till teoretisk aktieprissättning.

Robust portfolio optimization models attempt to address the standard optimization method's high sensitivity to noise in the parameter estimates, by taking an investor's uncertainty about the estimates into account when finding an optimal portfolio. In this thesis, we study robust variations of an extension of the mean-variance problem, where an additional term penalizing the portfolio's correlation with an exogenous return sequence is included in the objective. Using a normalized risk factor model of the asset returns, estimations are done using EMA filtering as well as exponentially weighted linear regression. We show that portfolio performance can significantly improve with respect to a range of metrics, such as Sharpe ratio, expected shortfall and skewness, when using appropriate robust models and hyperparameters. We further show that extending the optimization problem with a correlation penalty can notably reduce portfolio correlation with an arbitrary return sequence, with only a small impact on other performance metrics. / Robust portföljoptimering är en metod för att reducera vanliga portföljmodellers höga känslighet för brus i parameterskattningar, genom att ta en investerares osäkerhet kring skattningarna i åtanke när en optimal portfölj tas fram. I denna rapport studeras robusta varianter av ett utökat mean-variance-problem, där en straffterm för portföljens korrelation med en exogen avkastningsserie lagts till. Skattningarna bygger på en riskfaktor-modell för avkastningarna, och använder EMA-filter kombinerat med exponentiellt viktad linjär regression. Vi visar att en portföljs prestanda kan förbättras avsevärt med avseende på ett flertal prestandamått, till exempel Sharpe-kvot, expected shortfall och skevhet, vid användning av lämpliga robusta modeller och hyperparametrar. Vi visar också att inkludering av ett korrelationsstraff i optimeringsproblemet kan ge noterbara reduceringar i portföljens korrelation med en godtycklig avkastningsserie, med liten effekt på andra prestandamått.

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Sustainability has become a major societal trend and interest in sustainable investments has increased among investors. The purpose of this study is to investigate how sustainability affects Swedish funds' returns and risk. Since research on the impact of sustainability on funds focuses mostly on investments outside Sweden, this study has limited itself to Swedish funds to fill the gap in research. The study analyzes 67 Swedish funds during 2015-2019 using various models such as CAPM, Fama-French three-factor model and Sharpe ratio. Furthermore, the funds' sustainability is measured using Morningstar's sustainability rating. Results show no signs of linear regression between sustainability and results from different models and the results of the study are not statistically significant. Thus, the study concludes that it is not sustainability that affects risk and return among the Swedish funds, but there may be other factors that have not been taken into account in this study. However, previous research shows that sustainable funds perform better and are more stable during times of crisis. This study has not examined the Swedish funds during times of crisis, but this may be an interesting topic for future research. / Hållbarhet har blivit en stor samhällstrend och intresset för hållbara investeringar har ökat bland investerare. Syftet med denna studie är att undersöka hur hållbarhet påverkar Sverigefonders avkastning och risk. Eftersom forskning kring hållbarhetens påverkan på fonder fokuserar mestadels på investeringar utanför Sverige har denna studie avgränsat sig till Sverigefonder för att fylla luckan i forskningen. Studien analyserar 67 Sverigefonder under 2015-2019 med hjälp av olika modeller såsom CAPM, Fama-French trefaktormodell och Sharpekvot. Vidare mäts fondernas hållbarhet med hjälp av Morningstar hållbarhetsbetyg. Resultat visar inga tecken på linjär regression mellan hållbarhet och resultat från olika modeller samt studiens resultat är inte statistiskt signifikanta. Därmed är studiens slutsats att det inte är hållbarhet som påverkar på risk och avkastning bland Sverigefonderna utan det kan vara andra faktorer som inte tagits hänsyn till i denna studie. Däremot visar tidigare forskning att hållbara fonder presterar bättre och är mer stabila under kristider. Denna studie har inte undersökt Sverigefonderna under kristider men detta kan vara ett intressant ämne för framtida forskning.

[pt] Este trabalho busca analisar a divergência observada, quanto à aplicabilidade do prêmio de risco por tamanho, entre a proposta apresentada pela TBG – Transportadora Gasoduto Bolívia-Brasil e a resposta da ANP - Agência Nacional de Petróleo para estimação do custo de capital próprio que balizará a tarifa máxima de transporte de gás natural para a empresa regulada. Tanto a TBG quanto a ANP adotaram o Capital Asset Price Model – CAPM como modelo para estimação do custo de capital próprio, no entanto, a proposta da TBG considerou o prêmio de risco por tamanho, ao passo que a resposta da Agência Reguladora não acatou a inclusão desse prêmio, conforme consta na nota técnica nº 007/2018-SIM de 16 de julho de 2018. Para analisar a divergência em relação ao prêmio de risco por tamanho, foi o utilizado modelo de três fatores de Fama e French (1993), que considera, além do risco sistemático adotado no CAPM, os fatores tamanho e índice B/M (book-to-market) para mensuração do custo de capital próprio. Os resultados encontrados, com base no modelo de três fatores de Fama e French (1993), não indicam aplicabilidade do prêmio de risco por tamanho para estimação do custo de capital próprio no mercado regulado de transporte de gás natural, pois os coeficientes dos fatores small minus big (SMB) e high minus low (HML) não apresentaram resultados com significância estatística para diversas das carteiras analisadas. Adicionalmente, as empresas de menor porte (small) e de alto índice B/M (high) apresentaram, entre julho de 2009 e junho de 2018, retornos médios inferiores às empresas maiores (big) e de baixo índice B/M (low), não evidenciando a existência de prêmios de risco por tamanho e por valor. / [en] The purpose of this study is to analyze the divergence observed regarding the applicability of the size risk premium, between the proposal presented by TBG - Brazilian Transporter Gasoduto Bolívia-Brasil and the response of ANP - National Petroleum Agency, in the estimation of the cost of equity that will define the maximum rate for the transport of natural gas to the regulated company. Both TBG and ANP adopted the Capital Asset Price Model (CAPM) model, however, TBG proposal considered the size risk premium while ANP response did not accept the inclusion of this premium as stated in technical note no. 007/2018-SIM of July 16, 2018. To analyze this divergence was used the Fama and French three factor model (1993) that considers, besides the systematic risk adopted in the CAPM, the factors size and B/M (book-to-market) index for measuring the cost of equity. The results obtained, based on Fama and French three factors model (1993), do not indicate the applicability of the size risk premium for estimative of the cost of equity in the regulated natural gas transportation market, since the small minus big (SMB) and high minus low (HML) factor s coefficients did not present statistical significant results for some of the analyzed portfolios. In addition, smaller and high B/M companies presented, between July 2009 and June 2018, lower average returns than bigger and low B/M companies, not evidencing the existence of size and value risk premiums.

Det ökade fokuset på hållbarhet har gjort miljö-, social- och styrningsfaktorer (ESG) till kritiska faktorer när man fattar investeringsbeslut. Denna studie beskriver och analyserar sambandet mellan ESG-screening och finansiella prestandan hos portföljer inom STOXX Europe 600-indexet mellan 2019 och 2023. Studien tillämpar en kvantitativ ram för att analysera tre portföljer, var och en med olika tröskelvärden för ESG-screening, och undersöker om högre ESG-rating korrelerar med högre avkastning. Genom att tillämpa CAPM tillsammans med Fama Frenchs trefaktormodell samt prestationsmått som Sharpekvoten, Beta och Jensens Alfa, syftar studien till att ge en fördjupad jämförelse av portföljer med olika ESG-kriterier mot det europeiska aktieindexet. Resultaten visar att ESG-screenade portföljer inom STOXX Europe 600 inte överträffade indexet i hänsyn till deras riskjusterade avkastning. Denna studie bidrar till diskussionen om de ekonomiska fördelarna med hållbara investeringar, genom att visa att även om ESG-screenade portföljerna har högre hållbarhetsgrad, leder de inte nödvändigtvis till förbättrade finansiella resultat på de europeiska marknaderna. / The increasing focus on sustainability has made Environmental, Social and Governance (ESG) factors critical elements when making investment decisions. This study evaluates the relationship of ESG screening and the financial performance of portfolios within the STOXX Europe 600 index between 2019 and 2023. Using a quantitative framework, this study analyzed three portfolios – each with different ESG-screening thresholds – to investigate whether higher ESG-rating correlates with higher financial returns. By applying CAPM and the Fama-French three-factor model along with performance metrics such as the Sharpe ratio, Beta and Jensen’s Alpha, the study aims to provide an in-depth comparison of portfolios with ESG-criteria against the European stock index. The results indicate that ESG-screened portfolios within STOXX Europe 600 did not outperform the unscreened index, in terms of risk-adjusted returns.  This study adds to the ongoing discussion about the financial benefits of sustainable investing by showing that whilst ESG-screened portfolios have higher sustainability measures, they do not necessarily lead to improved financial results in the European markets.