Information Content of Bank Credit Rating Changes: Evidence from Europe

This thesis examines the short-term impact of credit rating announcements on daily stock returns of 41 European banks indexed in STOXX Europe 600 Banks. The time period of this study is 2002–2015 and the ratings represent long-term issuer ratings provided by S&P, Moody’s and Fitch. Bank ratings are significant for a bank’s operation costs so it is interesting to investigate how investors react to changes in creditworthiness. The study objective is achieved by conducting an event study. The event study is extended with a cross-sectional linear regression to investigate other potential determinants surrounding rating changes. The research hypotheses and the motivation for additional tests are derived from prior research. The main hypotheses are formed to explore whether rating changes have an effect on stock returns, when this possible reaction occurs and whether it is asymmetric between upgrades and downgrades. The findings provide evidence that rating announcements have an impact on stock returns in the context of European banks. The results also support the existence of an asymmetry in capital market reaction to rating upgrades and downgrades. The rating downgrades are associated with statistically significant negative abnormal returns on the event day although the reaction is rather modest. No statistically significant reaction is found associated with the rating upgrades on the event day. These results hold true with both rating changes and rating watches. No anticipation is observed in the case of rating changes but there is a statistically significant cumulative negative (positive) price reaction occurring before the event day for negative (positive) watch announcements. The regression provides evidence that the stock price reaction is stronger for rating downgrades occurring within below investment grade class compared with investment grade class. This is intuitive as investors are more concerned about their investments in lower-rated companies. Besides, the price reaction of larger banks is more mitigated compared with smaller banks in the case of rating downgrades. The reason for this may be that larger banks are usually more widely followed by the public. However, the study results may also provide evidence of the existence of the so-called “too big to fail” subsidy that dampens the negative returns of larger banks.

Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics

One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.

Project Controlling and Management in IT Consulting Enterprise

Liiketoiminnan organisoiminen projekteiksi on erittäin yleistä nykyisin. Suuri osa projekteista erityisesti IT-alalla epäonnistuu kuitenkin saavuttamaan tavoitteensa. Projektin menestys on tyypillisesti mitattu budjetin, aikataulun, laadun ja sidosryhmien tyytyväisyyden perusteella. Tämän Pro Gradu -tutkielman tarkoituksena on etsiä tyypillisimpiä syitä projektien epäonnistumiseen ja löytää projektien seurannan ja mittaamisen avulla keinoja näiden epäonnistumisten ehkäisemiseen. Tutkimusmenetelmänä on laadullinen tapaustutkimus. Empiirinen aineisto on kerätty haastattelujen, eri materiaalien analysoinnin ja havainnoinnin avulla. Teoriaosuus tarjoaa kattavan yhteenvedon projektiliiketoiminnan ja yksittäisten projektien johtamiseen sekä projektien seurantaan ja mittaamiseen aikaisemman kirjallisuuden perusteella. Empiirisessä osiossa suoritetaan analyysi Case -yrityksen projektien seurantaan ja valittuihin projekteihin. Analyysien, haastattelujen ja havainnoinnin pohjalta tehdään johtopäätökset tyypillisimmistä, ongelmia projekteissa aiheuttavista tekijöistä sekä näiden esiintymisestä projektin elinkaaren eri vaiheissa. Mahdolliset ongelmia ehkäisevät keinot esitetään myös. Ehdotuksia kehityskohteiksi esitetään lopuksi teorian ja empirian pohjalta.