The thesis focuses on the analysis of various extensions of the classical multi-period single-item stochastic inventory problem. Specifically, we investigate two particular approaches of modeling risk in the context of inventory management: risk-averse models and robust formulations. We analyze the classical newsvendor problem utilizing a coherent risk measure as the objective function. Properties of coherent risk measures allow us to offer a unifying treatment of risk averse and min-max type formulations. We show that the structure of the optimal policy of the risk-averse model is similar to that of the classical expected value problem for both single and multi-period cases. The result carries over even when there is a fixed ordering cost. We expand our analysis to robust formulations of multi-period inventory problems. We consider both independent and dependent uncertainty sets and prove the optimality of base-stock policies for the general problem formulation. We focus on budget of uncertainty approach and develop a heuristic that can also be employed for a class of parametric dependency structures. We compare our proposed heuristic against alternative solution techniques.

Denna studie bidrar till området behavioral finance och ger en ökad förståelse om hur kvinnliga aktieägare påverkas av stereotyper och igenkänning. Diskussionen kring att en könsdiversifierad styrelse och företagsledning kan bidra till en stabilare och ökad tillväxt uppmärksammas i allt fler länder, däribland Sverige vars jämställhet mellan kvinnor och män är hög. På dagens marknad är kvinnor underrepresenterade på högre företagsposter, vilket även gäller kvinnliga aktieägare jämfört med manliga. Detta beror på att män tenderar att ha en överdriven tilltro till sina egna uppfattningar och värderingar samt är mer riskbenägna och optimistiska än kvinnor. Beteendet hos aktieägarna påverkas av de stereotyper som förkommer. I jämförelse med andra är den demografiska egenskapen kön en central del i beslutsprocessen. Med utgångspunkt i teorier som prospektteorin, signalteorin och agentteorin kan kvinnliga aktieägares påverkan av stereotyper förklaras. Två fundamentala faktorer i studien är representativitet och konservatism eftersom människor har en tendens att kategorisera och hålla fast vid tidigare uppfattningar och stereotyper om andra individer och grupper. I enlighet med signalteorin bidrar kvinnor till minskad informationsasymmetri, på grund av ökade kommunikativa förmågor, vilket bidrar till stabilitet i företaget och intresserar enligt resultatet de kvinnliga aktieägarna. Ökad kommunikation till aktieägare minskar risken för att intressekonflikter uppstår mellan aktieägare och företagsledning. Teorierna hjälper till att undersöka det resultat som framställts av de analysmetoder som använts för att pröva hur aktieägare påverkas av en ökad könsdiversifiering. För att undersöka om en kvinnlig verkställande direktör påverkar kvinnliga aktieägare har en eventstudie genomförts. Vidare har en multivariat regressionsanalys gjorts för att kunna ta hänsyn till fler variablers påverkan, exempelvis könsdiversifiering i styrelse och ledning, samt företagsstorlek. Studiens resultat visar att en ökad könsdiversifiering intresserar kvinnliga aktieägare. Detta beror på att kvinnor är mindre riskbenägna än män och att igenkänning till individer med liknande demografiska egenskaper skapar en trygghetskänsla. Företag med en kvinnlig verkställande direktör har inte direkt påverkan på de kvinnliga aktieägarna, något som beror på den långsamma förmågan att ändra på tidigare övertygelser och stereotyper om kvinnors ledarskapsförmåga. Däremot sker en indirekt påverkan eftersom ledningen, vilken den kvinnliga verkställande direktören ingår i, har en påverkan på andelen kvinnligt ägda aktier. / The purpose of the study is to provide an increased understanding of how female shareholders are affected by stereotypes and comparison with other women. The discussion of gender-diversified boards and management is highlighted in several countries, including Sweden. Women are underrepresented as CEOs, board members and management. Likewise, women are underrepresented in the stock market, this because men tend to have excessive confidence in their own perceptions and values and are more risk taking and optimistic than women. Shareholders are affected by the stereotypes that occur. In comparison with others, the demographic characteristics are a key part of the decision-making process. The result of the study shows that increased gender diversification is interesting for female shareholders. This is because women are less risk-intensive than men and that recognition to individuals with similar demographic characteristics creates a sense of security. Female shareholders find similar characteristics in female board-members and management, this does not match comparison with female CEOs, due to the slow ability to change the perception of female leadership.

No description available.

Background: Since the emergence of Covid-19 has it reaped and created havoc within every segment of society on a national and global scale. The financial market experienced significant declines and losses but some asset items handled the fluctuations better than others. Moreover, since some asset items are associated with different risk levels will various investors with contrasting risk attitude allocate dissimilar proportion of their disposable capital between these alternatives. Especially during low and high levels of economic uncertainty which is related to the volatile market of Covid-19. Although, little to no research has been conducted aimed at understanding how Covid-19 impacted Swedish students asset allocation prior and post the pandemic with different risk profiles.   Purpose: The purpose of this study is to investigate if students with different risk attitudes (risk-preference, risk-neutral and risk-averse) conduct statistically different asset allocation prior and post the Covid-19 pandemic. Furthermore, investigate shifts in asset holdings prior and post the pandemic. Moreover, in order to fill the identified literature gap and add to the current body of knowledge regarding asset allocation and variability concerning risk attitudes since its exclusion of Swedish student’s risk attitudes and impact of Covid-19 on preferable asset items.                                    Method: This investigative study concerns a quantitative survey of 81 different students attending Jönköping University. The survey was structured in a way to uncover whether students with different risk attitudes conduct asset allocation statistically different prior and post the Covid-19 pandemic. Moreover, incorporate sociodemographic factors of students in order to measure its relation to risk attitudes and uncertainty changes. This will be done through non-parametric tests (distribution free) such as the Chi-square, Kruskal-Wallis and Bonferroni adjusted p-value approach. The data is later discussed and interpreted through various academic sources and in the context of the frame of reference (expected utility theory).                              Conclusion: The impact of Covid-19 resulted into increased asset allocation of less risky and “safe” asset in order to deal with the declining stock market and future economic uncertainty. The study also suggest that students liquidated some of their current/fixed deposits and re-invested their disposable capital into a more conservative money management strategy, which was a continuous identified pattern.  Furthermore, the results indicate that students with different risk attitudes conduct significantly different asset allocation concerning commercial insurance, stocks/funds and various bond types prior to Covid-19. However, post the eruption has the statistical identified differences in bonds asset allocation reduced which refers to that the statistical power and dissimilar allocated proportion amongst asset items has diminished. Further multiple comparison reinsures this conclusion. Thusly, the study implies that the differences between asset allocation and student risk profiles are diminished post Covid-19 and therefore students perceived and allocated more similar capital proportions into various asset items. Hence answer the initial stated research question and empirically state that risk attitude of students impact how they conduct asset allocation prior to and to a lesser extent post Covid-19

Os processos de decisão de Markov (Markov Decision Process - MDP) têm sido usados para resolução de problemas de tomada de decisão sequencial. Existem problemas em que lidar com os riscos do ambiente para obter um resultado confiável é mais importante do que maximizar o retorno médio esperado. MDPs que lidam com esse tipo de problemas são chamados de processos de decisão de Markov sensíveis a risco (Risk-Sensitive Markov Decision Process - RSMDP). Dentre as diversas variações de RSMDP, estão os trabalhos baseados em utilidade exponencial que utilizam um fator de risco, o qual modela a atitude a risco do agente e que pode ser propensa ou aversa. Os algoritmos existentes na literatura para resolver esse tipo de RSMDPs são ineficientes se comparados a outros algoritmos de MDP. Neste projeto, é apresentada uma solução que pode ser usada em problemas maiores, tanto por executar cálculos apenas em estados relevantes para atingir um conjunto de estados meta partindo de um estado inicial, quanto por permitir processamento de números com expoentes muito elevados para os ambientes computacionais atuais. Os experimentos realizados evidenciam que (i) o algoritmo proposto é mais eficiente, se comparado aos algoritmos estado-da-arte para RSMDPs; e (ii) o uso da técnica LogSumExp permite resolver o problema de trabalhar com expoentes muito elevados em RSMDPs. / Markov Decision Process (MDP) has been used very efficiently to solve sequential decision-making problems. There are problems where dealing with environmental risks to get a reliable result is more important than maximizing the expected average return. MDPs that deal with this type of problem are called risk-sensitive Markov decision processes (RSMDP). Among the several variations of RSMDP are the works based on exponential utility that use a risk factor, which models the agent\'s risk attitude that can be prone or averse. The algorithms in the literature to solve this type of RSMDPs are inefficient when compared to other MDP algorithms. In this project, a solution is presented that can be used in larger problems, either by performing calculations only in relevant states to reach a set of meta states starting from an initial state, or by allowing the processing of numbers with very high exponents for the current computational environments. The experiments show that (i) the proposed algorithm is more efficient when compared to state-of-the-art algorithms for RSMDPs; and (ii) the LogSumExp technique solves the problem of working with very large exponents in RSMDPs

Os processos de decisão de Markov (Markov Decision Process - MDP) têm sido usados para resolução de problemas de tomada de decisão sequencial. Existem problemas em que lidar com os riscos do ambiente para obter um resultado confiável é mais importante do que maximizar o retorno médio esperado. MDPs que lidam com esse tipo de problemas são chamados de processos de decisão de Markov sensíveis a risco (Risk-Sensitive Markov Decision Process - RSMDP). Dentre as diversas variações de RSMDP, estão os trabalhos baseados em utilidade exponencial que utilizam um fator de risco, o qual modela a atitude a risco do agente e que pode ser propensa ou aversa. Os algoritmos existentes na literatura para resolver esse tipo de RSMDPs são ineficientes se comparados a outros algoritmos de MDP. Neste projeto, é apresentada uma solução que pode ser usada em problemas maiores, tanto por executar cálculos apenas em estados relevantes para atingir um conjunto de estados meta partindo de um estado inicial, quanto por permitir processamento de números com expoentes muito elevados para os ambientes computacionais atuais. Os experimentos realizados evidenciam que (i) o algoritmo proposto é mais eficiente, se comparado aos algoritmos estado-da-arte para RSMDPs; e (ii) o uso da técnica LogSumExp permite resolver o problema de trabalhar com expoentes muito elevados em RSMDPs. / Markov Decision Process (MDP) has been used very efficiently to solve sequential decision-making problems. There are problems where dealing with environmental risks to get a reliable result is more important than maximizing the expected average return. MDPs that deal with this type of problem are called risk-sensitive Markov decision processes (RSMDP). Among the several variations of RSMDP are the works based on exponential utility that use a risk factor, which models the agent\'s risk attitude that can be prone or averse. The algorithms in the literature to solve this type of RSMDPs are inefficient when compared to other MDP algorithms. In this project, a solution is presented that can be used in larger problems, either by performing calculations only in relevant states to reach a set of meta states starting from an initial state, or by allowing the processing of numbers with very high exponents for the current computational environments. The experiments show that (i) the proposed algorithm is more efficient when compared to state-of-the-art algorithms for RSMDPs; and (ii) the LogSumExp technique solves the problem of working with very large exponents in RSMDPs

In the field of VLSI circuit optimization, the scaling of semiconductor devices has led to the miniaturization of the feature sizes resulting in a significant increase in the integration density and size of the circuits. At the nanometer level, due to the effects of manufacturing process variations, the design optimization process has transitioned from the deterministic domain to the stochastic domain, and the inter-relationships among the specification parameters like delay, power, reliability, noise and area have become more intricate. New methods are required to examine these metrics in a unified manner, thus necessitating the need for multi-metric optimization. The optimization algorithms need to be accurate and efficient enough to handle large circuits. As the size of an optimization problem increases significantly, the ability to cluster the design metrics or the parameters of the problem for computational efficiency as well as better analysis of possible trade-offs becomes critical. In this dissertation research, several utilitarian methods are investigated for variation aware multi-metric optimization in VLSI circuit design and spatial pattern clustering. A novel algorithm based on the concepts of utility theory and risk minimization is developed for variation aware multi-metric optimization of delay, power and crosstalk noise, through gate sizing. The algorithm can model device and interconnect variations independent of the underlying distributions and works by identifying a deterministic linear equivalent model from a fundamentally stochastic optimization problem. Furthermore, a multi-metric gate sizing optimization framework is developed that is independent of the optimization methodology, and can be implemented using any mathematical programming approach. It is generalized and reconfigurable such that the metrics can be selected, removed, or prioritized for relative importance depending upon the design requirements. In multi-objective optimization, the existence of multiple conflicting objectives makes the clustering problem challenging. Since game theory provides a natural framework for examining conflicting situations, a game theoretic algorithm for multi-objective clustering is introduced in this dissertation research. The problem of multi-metric clustering is formulated as a normal form multi-step game and solved using Nash equilibrium theory. This algorithm has useful applications in several engineering and multi-disciplinary domains which is illustrated by its mapping to the problem of robot team formation in the field in multi-emergency search and rescue. The various algorithms developed in this dissertation achieve significantly better optimization and run times as compared to other methods, ensure high utility levels, are deterministic in nature and hence can be applied to very large designs. The algorithms have been rigorously tested on the appropriate benchmarks and data sets to establish their efficacy as feasible solution methods. Various quantitative sensitivity analysis have been performed to identify the inter-relationships between the various design parameters.

現實社會中，由於人並非如傳統學派所聲稱完全理性制定決策，自1980年以來即產生諸多傳統學派無法說明的現象，因此行為財務學派興起。本篇導入行為財務學的模型，探討當經理人具過度自信與過度樂觀特質時，經理人的特性會如何影響公司價值。研究假設當經理人為風險中立者，可達到公司價值極大化first-best value。若經理人為風險趨避，產生的效用成本將使其無法達成此目標，但此時經理人若具過度自信，則可抵消風險趨避帶來的公司價值減損，而達成股東所希望達到的公司價值極大。除此之外，根據Heaton(2003)模型所聲稱，過度樂觀的經理人無法達成公司價值極大，而本篇修改其模型，得出當公司經理人具過度樂觀特性，是有可能符合股東利益，而達到公司價值極大化的目標。 / In real world, people don’t make decisions depend on rationality. Therefore, there exists many facts that traditional researchers can’t explain since 1980’s and that’s why behavioral finance school arises. In this paper, we use behavioral finance models to discuss when managers are overconfident or optimistic, how their personality will affect the value of company. We find that when a manager is risk-neutral, he can maximize the firm value that we called “first-best value.” However, when a manager is risk-averse, the utility cost will be the huge obstacle to attain the goal. However, if the manager is overconfident, this characteristic will counterbalance the drawback that risk-averse will decrease company value. In addition, according to Heaton’s (2003) model, an optimistic manager can’t maximize firm value. This paper modifies Heaton’s model and finds that when managers are optimistic, it is likely that a manager can meet shareholder’s needs and maximize the firm value.

Nous nous intéressons dans ce travail au guidage optimal des usagers dans un réseau routier. Plus précisément, nous nous focalisons sur les stratégies adaptatives de guidage avec des garanties en termes de fiabilité des temps de parcours, et en termes de robustesse de ces stratégies. Nous nous basons sur une approche stochastique où des distributions de probabilités sont associées aux temps de parcours sur les liens du réseau. Le guidage est adaptatif et individuel. L'objectif de ce travail de recherche est le développement de stratégies « robustes » de guidage des usagers dans un réseau de transport routier. Une stratégie de guidage d’un nœud origine vers un nœud destination est dite robuste, ici, si elle minimise la détérioration de sa valeur maximale calculée au départ de l’origine, contre d’éventuelles reconfigurations du réseau dues à des coupures de liens (accidents, travaux, etc.) La valeur de la stratégie de guidage est maximisée par rapport à la moyenne et à la fiabilité des temps de parcours associées à la stratégie. Deux principales parties sont distinguées dans ce travail. Nous commençons par l’aspect statique du guidage, où la dynamique du trafic n’est pas prise en compte. Nous proposons une extension d’une approche existante de guidage, pour tenir compte de la robustesse des itinéraires calculés. Dans une deuxième étape, nous combinons notre nouvel algorithme avec un modèle microscopique du trafic pour avoir l’effet de la dynamique du trafic sur le calcul d’itinéraires robustes / In this work, we are interested in the optimal guidance of users on road networks. More precisely, we are focused on the adaptive strategies of guidance with guarantees in terms of the travel time reliability and in terms of the robustness of the strategies. We base here on a stochastic approach, where probability distributions are associated to travel times on the links of the network. The guidance is adaptive and user-based. The objective of this work is the development of "robust" strategies for user guidance in a road network. A guidance strategy is said to be robust, here, if it minimizes the deterioration of its maximum value calculated at the origin, against eventual reconfigurations of the network due to link failures (accidents, works, etc.) The value of a guidance strategy is maximized with respect to the mean travel time and its reliability. Two main parts are distinguished in this work. We start with the static aspect of the guidance, where the traffic dynamics are not taken into account. We propose an extension of an existing guidance approach, to take into account the robustness of the calculated itineraries. In a second step, we combine our new guidance algorithm with a microscopic traffic model in order to have the effect of the traffic dynamics on the robust route calculation

Retirement is one part of life that everybody will sooner or later come too. It is very important to prepare and plan for it by looking for the best possible alternative(s) to save and invest money in order to get enough capital to live on when it is time to retire. In Sweden like in many other countries women tend to have lower wages than men and the maternity leave is a life event that can affect the income of women during their labour time. This can then result in women having less disposable income during the retirement period. In general, women are living longer than men therefore they should get more money to live on but this is not the case in most of the time. In finance taking high risk can be rewarded by high return. Several researches that have been conducted in different fields came to the same conclusion that women are more risk averse than men. This risk averse can be explained by physiological, psychological, social and intellectual aspects. In this thesis I study the investment behaviour of both genders in Premium Pension Funds managed by the Swedish Pension Authority (PPM). In contrary to what many researches in several fields have come to, I found that men tend to invest less than women when the risk level involved in investing in Premium Pension Funds increases. This observation can be seen as an attempt of the women to increase their pension capital in a shorter of time by investing in riskier pension funds. A further study on this subject will be suitable in order to confirm if the women’s attempt to increase their pension capital by engaging in riskier pension funds is rewarded by a higher return by including annually returns as an additional independent variable / Pensionering är en del av livet som alla förr eller senare kommer också. Det är mycket viktigt att förbereda och planera för det genom att leta efter bästa möjliga alternativ (s) för att spara och investera pengar i för att få tillräckligt med kapital för att leva på när det är dags att gå i pension. I Sverige liksom i många andra länder kvinnor tenderar att ha lägre löner än män och moderskapsledigheten är en händelse i livet som kan påverka inkomster kvinnor under sin arbetstid. Detta kan sedan leda till att kvinnor har mindre disponibel inkomst under pensionstiden. I allmänhet, kvinnor lever längre än män och därför bör de få mer pengar att leva på, men detta är inte fallet i större delen av tiden. I finans ta hög risk kan belönas med hög avkastning. Flera undersökningar som har genomförts inom olika områden kom till samma slutsats att kvinnor är mindre riskbenägna än män. Denna riskaversion kan förklaras av fysiologiska, psykologiska, sociala och intellektuella aspekter. I denna avhandling studerar jag investeringsbeteende båda könen i Premiepensionsfonder som förvaltas av Svenska Pensionsmyndigheten (PPM). I motsats till vad många forskare inom flera områden har kommit till, fann jag att män tenderar att investera mindre än kvinnor när risknivån med att investera i Premiepensionsfonderna ökar. Denna observation kan ses som ett försök av kvinnor att öka sitt pensionskapital i en kortare tid genom att investera i mer riskfyllda pensionsfonder. En påbyggande studie i detta ämne kommer att vara lämplig för att bekräfta om kvinnornas försök att öka sitt pensionskapital genom att delta i riskfyllda pensionsfonder belönas med en högre avkastning genom att inkludera avkastning som en ytterligare oberoende variabel.