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Senast publicerade

Microstructural Investigation of Solder Joint Failure in Heavy Duty Trucks
(2026) Sudhakar, Bhushan
The reliability of electronic control units (ECUs) used in heavy-duty vehicles is strongly influenced by the thermo-mechanical behaviour of Ball Grid Array (BGA) solder joints. This study investigates the microstructural evolution of SAC305 BGA solder joints subjected to accelerated environmental loading and compares laboratory-aged samples with a field-returned component. SAC305 solder joints were investigated after thermal shock testing for 1000 and 2000 cycles, vibration testing, combined thermal cycling and vibration, and field service. The samples were characterized using polarized optical microscopy (POM), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), and quantitative Image analysis. The investigation focused on Ag3Sn particle evolution and interfacial intermetallic compound (IMC) layers. The results showed measurable microstructural evolution, including changes in Ag3Sn particle morphology and distribution and variations in IMC thickness. The PCB-side IMC was generally thicker than the package-side IMC. No visible fatigue cracks or interfacial delamination were observed after 1000 or 2000 thermal cycles, indicating an early stage of solder degradation. The vibration and combined loading samples also exhibited microstructural changes, although the individual effects of thermal and mechanical loading could not be separated conclusively. Comparison with the field-returned component showed differences in Ag3Sn morphol ogy and IMC characteristics, demonstrating that laboratory thermal shock alone cannot fully reproduce the complexity of field ageing
Systems and Methods for Resource Allocation in Late-Stage Drug Development
(2026) Bergstrand, Linus; Ernberg, Ollie; Sandstedt, Emmie; Blomgren, Ludvig; Gradinarska, Boiana; Zhu, Steven
Problem: The pharmaceutical industry is characterised by high uncertainty, resource scarcities and strict time and quality constraints, making resource allocation in multi-project environments particularly complex. This is distinctly critical in late-stage drug development, where heightened regulatory requirements and unpredictable results intensify coordination challenges. Aim: This study aims to investigate how effective resource allocation is conducted under the constraints of late-stage drug development in the pharmaceutical industry and how its effectiveness can be improved. Theoretical Framework: A theoretical framework was established for the study and was based on previous literature related to the characteristics of late-stage drug development, decision levels, governance, organisational alignment, and allocation methods. Method: A qualitative single-case study was applied to the thesis, consisting of a literature study and an interview study. This was done in order to examine how theoretical approaches are applied in practice and which decision parameters shape allocation behaviour within AstraZeneca, a global pharmaceutical company. The literature study was conducted to establish a theoretical base for the analysis of resource allocation in late-stage drug development. The interview study provided empirical data from employees at AstraZeneca working in various roles related to the focus area of the study. Results and Implications: The findings confirm that resource allocation in multi-project environments and late-stage development are shaped by high uncertainty, structural constraints, and reliance on managerial judgement. Uncertainty limits optimisation at operational and tactical levels, causing decision-making to rely on heuristic and experience-based judgement under time constraints and incomplete information. Consequently, resource allocation becomes reactive and requires continuous re-prioritisation across projects. The study also identifies a gap between formal systems and enacted practices, where informal coordination compensates for limited local flexibility and fragmented decision-support systems. This suggests that, rather than attempting to eliminate uncertainty and reactivity, organisations within late-stage drug development should enable more integrated decision-making tools, implement information-sharing structures for managerial knowledge, and balance governance structures with local flexibility.
ECB:s klimattilt och greenium på företagsobligationsmarknaden
(2026) Ekman, Lukas; Eurén, Gustav; Karlsson, David; Lagergren, Tilda; Lundgren, Max
Problem Marknaden för gröna obligationer har vuxit kraftigt, men existensen av och drivkrafterna bakom ett så kallat greenium är fortfarande omdebatterade. Även om centralbanker som Europeiska centralbanken (ECB) har infört klimatviktad penningpolitik för att stödja den gröna omställningen, är det oklart i vilken utsträckning en sådan klimatinriktad penningpolitik faktiskt påverkar företags finansieringsvillkor och prissättningen av gröna företagsobligationer på primärmarknaden. Syfte Denna studie undersöker huruvida ECB:s klimattilt 2022 har påverkat greenium, definierat som skillnaden i kreditspread mellan jämförbara gröna och konventionella obligationer, på primärmarknaden för EUR-denominerade företagsobligationer. Teoretiskt ramverk Studien kontrasterar den effektiva marknadshypotesen (EMH) mot teorier om preferensdriven prissättning, preferred habitat och institutionell signalering, för att förklara de mekanismer genom vilka centralbankers interventioner kan förväntas påverka greenium. Metod Med en datamängd bestående av 3 279 observationer av företagsobligationer över perioden 2015 2026 tillämpas difference-in-differences (DiD) och triple difference-in-differences (DDD). Den svenska företagsobligationsmarknaden (SEK) används som kontrollgrupp i DDD-modellen för att isolera den specifika policyeffekten på den behandlade marknaden. Resultat och implikationer DiD-modellen visar att gröna EUR-obligationer emitterades till en cirka 13 räntepunkter lägre kreditspread relativt konventionella obligationer efter policyskiftet, vilket är ett statistiskt signifikant resultat. DDD-modellen ger en koefficient av liknande storlek (-14 räntepunkter) men saknar statistisk signifikans. Denna diskrepans drivs troligtvis av spridningseffekter till följd av en överlappande institutionell investerarbas mellan EUR- och SEK-marknaderna, vilket kontaminerar kontrollgruppen. Resultaten indikerar att greenium förstärktes på den europeiska marknaden efter ECB:s klimattilt, men ger inte tillräcklig statistisk evidens för att fastställa ett direkt kausalt samband enbart till policyn.
Comparing Empirical Minimum Variance Hedging with Delta-Vega Hedging and Model-Based Delta hedging (Black-Scholes, GARCH, and SABR) Under Normal and Extreme Market Conditions
(2026) Hashemi, Simon; Wegfors, Albin; Dahlgren, Hugo; Halvarson, Markus; Jönsson, Arvid; Larsson, Erik
Options are one of the most used instruments in risk management and are used by corporations and investors manage their risk exposure. For the issuer of an option, there is an exposure to the underlying asset. This is usually managed through whats called hedging. The most well-known hedging method is the delta hedge, from the Black-Scholes framework. In the Black-Scholes framework, the position in the underlying asset is continuously adjusted to counter changes in the option value, while assuming constant volatility. In practice, however, the assumption of constant volatility doesn’t hold. The relationship between the underlying price and its implied volatility leads to hedging errors that become more pronounced during periods of market stress. The approaches proposed to handle these limitations include, stochastic volatility models such as SABR, time-varying volatility models such as GARCH, the empirical minimum variance hedge developed by Hull and White, and combined delta vega strategies that aim to neutralise both price and volatility exposure at the same time. Each approach captures a different part of the relationship between price and volatility, and each has its own strengths and weaknesses. This thesis aims to evaluate and compare these hedging strategies under both normal and more stressed market conditions. The goal is to provide insight into which strategies remain robust during both normal and extreme market regimes. The thesis is conducted as a quantitative replication and extension of the work by Hull and White from 2017. The dataset is sourced from OptionMetrics and covers the period 2015 to 2025. The dataset includes index options, equity options, and ETF options, and each trading day is classified into a normal, elevated, or extreme regime based on the VIX index level. Each methods performance is measured through the sum of squared hedging errors relative to the Black-Scholes benchmark, with Newey-West corrections applied to account for autocorrelation in the daily loss differentials. The theoretical literature is reviewed in order to motivate the construction of each hedge and to interpret the difference in hedging performance. The hedging strategies discussed are the standard Black-Scholes delta hedge, the GARCH plug-in delta hedge, the GJR-GARCH minimum variance correction, the SABR model-based delta hedge, the empirical minimum variance hedge, the model-free delta-vega hedge, and the GARCH-scaled delta-vega overlay. The thesis shows that it is highly uncertain whether any hedging method dominates across market conditions. The investigated approaches share strengths and weaknesses, and their relative performance depends on the option type, the moneyness, and the volatility regime. The model-free delta-vega hedge delivers the largest and most consistent improvement over Black-Scholes, while the empirical minimum variance hedge also improves on the benchmark, although by a smaller margin than originally reported. The SABR approach yields modest gains and exhibits a clear difference between calls and puts. The GARCH based delta hedges perform poorly because they discard the smile information embedded in implied volatility. The broader analysis is that effective hedging depends less on forecasting volatility itself and more on capturing the relationship between the underlying price and its implied volatility. Practitioners should therefore prioritise hedging strategies that target volatility exposure directly rather than those that rely on historical return-based forecasts.
Systemperspektiv som hjälpmedel vid planering av infrastrukturella megaprojekt
(2026) Forssmed, Elsa; Linghoff, Tess; Tanderud, Elvira; Lindner, Hanna; Sterky, Elvira; Vestman, Andréa
Large-scale infrastructure projects, so called megaprojects, are characterized by a high degree of complexity where technical solutions interact with social, environmen tal, and economic factors. Previous research indicates that a traditional fragmented perspective fails to capture the holistic planning of megaprojects, leading to subopti mal outcomes and significant cost overruns. To meet this need, a system perspective may offer the insight needed to handle the complexity. This study aims to investigate how a system perspective can be implemented and applied to the planning process of infrastructure megaprojects, using the project Norrbotniabanan carried out by Trafikverket, as a case study. First, an analytical framework was developed, with strategic, organizational, and operational levels, based on system theory and the insight of experts. Second, a qualitative case study approach, using semi-structured interviews, was held with 21 professionals, including strategic planners and project managers working with the project. The main findings indicate that a system per spective was present at the organisation, however it remained largely implicit and inconsistently applied, due to reliance on the working experience and expertise of individual team members. The study further discusses the benefits, obstacles, and responsibilities of implementing a system perspective in the planning process. In conclusion, the study suggests standardization of systems perspective use, as well as internal education and improved communication, to enable the explicit application of a system perspective for an optimal planning process.