La contabilizzazione delle operazioni di M&A è radicalmente mutata nel corso degli ultimi dieci anni, nel contesto statunitense come in quello europeo. A seguito di tali cambiamenti l’ammontare di goodwill (avviamento) iscritto nei bilanci di molte società si è incrementato. Questo studio si propone in primo luogo di far luce sulla reliability di tali valori analizzando le cause della svalutazione del goodwill, a partire dall’ipotesi essa sia causata in molti casi dal pagamento di un prezzo eccessivo da parte dell’impresa acquirente, piuttosto che essere la conseguenza di eventi successivi all’operazione. L’analisi, in secondo luogo, ha lo scopo valutare se l’impairment test del goodwill, reso obbligatorio dallo SFAS 142 raggiunga l’obiettivo di individuare in modo tempestivo le perdite durevoli di valore del goodwill acquisito e, dunque, di evitare che rimangano iscritti in bilancio come assets valori che di fatto non lo sono. Lo studio ha considerato un campione di 929 acquisizioni concluse nel periodo 1999-2007 che hanno coinvolto società statunitensi quotate ed è stato condotto sviluppando un modello predittivo basato su alcune misure indicanti potenziale overpayment da parte dell’acquirente alla data di acquisizione. I risultati mostrano in primo luogo come alcuni indicatori di overpayment, come la percentuale del prezzo pagata in azioni dell’impresa acquirente e un ammontare elevato di goodwill rispetto al prezzo di acquisto, diano un contributo significativo nella stima di future svalutazioni del goodwill. Un risultato piuttosto preoccupante, poiché segnala una almeno parziale incapacità da parte degli attuali Principi Contabili (SFAS 141) di garantire che alla data di acquisizione il valore attribuito a tale asset sia effettivamente fondato sulle sinergie e sul valore di “going-concern” del target (“core goodwill”), escludendo elementi ad esso estranei, come l’ overpayment da parte dell’acquirente. Per quanto attiene al secondo obiettivo, i risultati mostrano che il lasso temporale tra la data di acquisizione e il momento della svalutazione è in media di due - tre anni, a differenza di quanto accadeva precedentemente all’entrata in vigore dello SFAS 142, quando tale distanza temporale è stata stimata essere tra i quattro e i cinque anni. Tale risultato pertanto suggerisce che l’impairment test (almeno) annuale ha ottenuto l’effetto di migliorare la tempestività dell’individuazione di eventuali perdite durevoli di valore, contribuendo a bilanciare l’effetto sopra descritto che potenzialmente si ingenera alla data di acquisizione. / The purpose of this study is to shed light on the reliability of accounting goodwill numbers by examining whether the root cause of many goodwill impairment losses is the overpayment for the target at the time of the original acquisition, rather than the deterioration of goodwill values caused by events occurred after acquisition. A second related objective is to assess whether the annual impairment test of the acquired goodwill introduced by SFAS 142 improved the ability of accounting standards to timely capture situations in which the amount of goodwill is overstated and should thus be written down. I tested these hypotheses over a sample of 929 acquisitions completed by US listed companies over the nine-year period from 1999 to 2007. To assess whether the occurrence of a goodwill impairment loss can be predicted based on overpayment indicators, I developed a prediction model of goodwill impairment losses using some indicators measured at the acquisition date that signal potential overpayment by the acquiring firm. First, I found that certain measures, such as the percentage of stock in the consideration and the amount of purchase price assigned to goodwill, in fact represent powerful indicators of the occurrence of a subsequent goodwill impairment. This result is troubling as it suggests that SFAS 141 provisions are at least partially unable to avoid that components other than “core goodwill” being included in the amount recognized as goodwill, casting some doubt on the credibility of prominent goodwill amounts included in the financial statements of many corporations. I also found that the recognition of goodwill impairments lags behind the acquisition time by an average of two to three years. Compared with findings of earlier studies this result indicates that SFAS 142 requirements for annual impairment tests in fact improved the timeliness of recognizing goodwill write-offs, eventually helping to mitigate the failure of SFAS 141.

Diss. (sammanfattning) Stockholm : Karolinska institutet, 2007. / Härtill 4 uppsatser.

Diss. (sammanfattning) Stockholm : Karolinska institutet, 2007. / Härtill 4 uppsatser.

Thesis(M.S.)--Auburn University, 2007. / Abstract. Vita. Includes bibliographic references.

No description available.

Economic agents often face situations, where there are multiple competing fore- casts available. Despite five decades of research on forecast combinations, most of the methods introduced so far fail to outperform the equal weights forecast combination in empirical applications. In this study, we gather a wide spectrum of forecast combination methods and reexamine these findings in two different classical economic times series forecasting applications. These include out-of- sample combining forecasts from the ECB Survey of Professional Forecasters and forecasts of the realized volatility of the U.S. Treasury futures log-returns. We asses the performance of artificial predictions markets, a class of machine learning methods, which has not yet been applied to the problem of combin- ing economic times series forecasts. Furthermore, we propose a new simple method called Market for Kernels, which is designed specifically for combining time series forecasts. We found that equal weights can be significantly out- performed by several forecast combinations, including Bates-Granger methods and artificial prediction markets in the ECB Survey of Professional Forecasters application and by almost all examined forecast combinations in the financial application. We also found that the Market for Kernels forecast...

This master thesis is focused on the analysis of economy efficiency of the European Modular System. This determination is going to proceed from comparison of standard and longer trucks. The sense of this thesis is to find out, if standard or longer trucks are more efficient. The comparison is going to be made with the aid of a calculation of costs, which arise on two chosen independent routes. The conclusion evaluation of the trucks is going to work on these analyses.

Wild animal capture has progressed over the years from trapping or physical capture, which was dangerous to both animal and man, to chemical immobilization. Opioids and butyrophenones are the most common classes of drugs used for ungulate immobilization; however newer drugs and drug combinations are commonly used in an attempt to reduce time to immobilization in wildlife. The enzyme hyaluronidase is often added to drug combinations in the belief that it reduces time to immobilization by improving drug absorption. The primary objective of this study was to ascertain if the addition of hyaluronidase to an etorphine and azaperone drug combination would be of value in reducing time to immobilization in blue wildebeest. The study also tried to ascertain if the added hyaluronidase enabled one to reduce the etorphine and azaperone doses required to immobilize blue wildebeest, without affecting time to immobilization. The study made use of a four-way cross-over study design, with four treatment groups, four sequences and four periods. The four treatment groups were etorphine and azaperone; etorphine, azaperone and 5000 international units (IU) hyaluronidase; etorphine, azaperone and 7500 IU hyaluronidase; and 75 % of the original etorphine dose, 75% of the original azaperone dose and 7500 IU hyaluronidase. Each animal was immobilized with each of the above four drug combinations randomly over an eight week period with a two week interval between each period. The times to first effect, first down and immobilization were recorded. The etorphine and azaperone treatment group was used as the control group. The difference in time to first effect between the control group and the etorphine, azaperone and 7500 IU hyaluronidase treatment group was statistically significant (95 seconds versus 67 seconds; p = 0.007). When compared to the time to immobilization in the control group (323 seconds) the time to immobilization in the etrophine, azaperone and 5000 IU hyaluronidase (228 seconds); etorphine, azaperone and 7500 IU hyaluronidase (210 seconds) and the low dose etorphine, low dose azaperone and 7500 IU hyaluronidase (268 seconds) groups were statistically significantly reduced (p=0.002, p=0.001 and p=0.045 respectively). It is therefore concluded that the addition of 5000 or 7500 IU hyaluronidase to an etorphine and azaperone combination significantly reduced the time to immobilization in blue wildebeest. The unexpected decrease in time to immobilization in the low dose etorphine, low dose azaperone and 7500 IU hyaluronidase treatment group requires further investigation. / Dissertation (MMedVet)--University of Pretoria, 2011. / Production Animal Studies / unrestricted

Combining forecasts have been proven as one of the most successful methods to improve predictive performance. However, while there often is a focus on theoretically optimal methods, this is an ill-posed issue in practice where the problem of robustness is of more empirical relevance. This thesis focuses on the latter issue, where the risk associated with different combination methods is examined. The problem is addressed using Monte Carlo experiments and an application to automated forecasting with data from the M4 competition. Overall, our results indicate that the choice of combining methodology could constitute an important source of risk. While equal weighting of forecasts generally works well in the application, there are also cases where estimating weights improve upon this benchmark. In these cases, many robust and simple alternatives perform the best. While estimating weights can be beneficial, it is important to acknowledge the role of estimation uncertainty as it could outweigh the benefits of combining. For this reason, it could be advantageous to consider methods that effectively acknowledge this source of risk. By doing so, a forecaster can effectively utilize the benefits of combining forecasts while avoiding the risk associated with uncertainty in weights.

The objective of this paper is to retrospectively evaluate forecast models for polling data, to be used prospectively for the Swedish general election in 2022. One of the simplest ways of forecasting an election result is through opinion polls, and using the latest observation as the forecast. This paper considers five different forecasting models on polling data which are evaluated based on different error measures and the results are compared to previous research done on the same topic. The data in this paper consists of time series data of party-preference polls from Statistics Sweden. When forecasting polling data, the naive forecasting model was the most accurate, but forecasting the election in 2018 resulted in the forecast combinations model being the most accurate. Finally, the models are used to make forecasts on the Swedish general election taking place in September of 2022.