The solvability of dynamic decision problems suffers from the curse of dimensionality, which limits the planning horizon one can afford for mapping the real problem into a numerically solvable dynamic optimization model. In this note, stochastic multistage programming is applied to dynamic fixed-income portfolio selection. We report how well some fixed income portfolio problems are currently solved with barycentric approximation. In particular, we illustrate how the planning horizon affects the numerical effort required to solve the programs. The computational results serve as a benchmark for decomposition methods of mathematical programming.
We examine the impact of corporate lifecycle on the likelihood of becoming a voluntary going private firm. We apply the firm’s capital mix as a measure for the stage in a firm’s lifecycle. In doing so, we provide a framework and evidence on firm characteristics of going private firms. We find that the decision to go private depends on the firm’s lifecycle. Young firms, with low retained earnings are more likely to go private than mature or old firms. We also find that relative firm characteristics of going private and non-going private firms are consistent with the findings on relative firm characteristics in M & A activity research for acquirers (bidders, non-targets) vs. non-acquirer (non-bidders, and targets) and that these relative firm characteristics of going private and non-going private firms stay constant throughout all stages of the corporate lifecycle.
The Swiss capital market is an extraordinary liquid and efficient market with increasing importance in times of financial instability in Europe and the world. However, there is no study that provides current evidence on IPO-pricing in Switzerland. Therefore, we analyze in this study the short- and long-run performance of Swiss IPO's from 2000 to 2014. The observed first-day underpricing is 8.4% on average, which we explain with high IPO activity and with a lack of competition between the Swiss investment banks. On the long-run, the IPO seem to be fairly priced.
The ongoing deregulation of electricity markets worldwide has a major impact on the power industry. New price risks require new risk management tools and new methods for the valuation of generation and transmission assets as well as existing (physical) electricity contracts. As far as risk management is concerned, many derivative instruments have been designed to hedge against spot price risk or different types of liability risk exposure. For instance one observes the emergence of markets for simple financial and physical derivative contracts such as futures, forwards, call and put options, etc. In addition, there is an immense variety of derivative contracts with American style and path dependent payoff structure. Such options are much more widespread in the energy business then in finance. Probably the most important examples are swing options which have been traded in electricity over-the-counter markets for a long time. Swing options are sometimes referred to as virtual power plants. In fact the problem of finding an optimal exercise strategy for a swing option is basically equivalent to the problem of finding an optimal generation schedule for a real power plant. The well known methods of finance (such as stochastic processes, option theory, and stochastic dynamic programming) can essentially be applied to forecasting, scheduling and pricing problems in the energy business, as well. However the special peculiarities of electric power lead to complications. In fact electric energy is not storable. Thus, contingent claims must be hedged by trading in forward contracts and a risk free asset, whereas the spot price of electric energy has to be considered as a non tradable state variable driving the market. Moreover electricity prices are mean-reverting and exhibit jumps and spikes, which significantly complicates the valuation of European-style derivatives. Finally, the most wide-spread derivative contracts (as well as the physical generation assets) in the energy business have an American-style and path-dependent payoff structure. The valuation of such contracts requires solution of involved stochastic programming problems.
Six hundred and twenty-four centers from 43 countries reported a total of 31?322 hematopoietic SCT (HSCT) to this 2009 European Group for Blood and Marrow Transplantation (EBMT) survey with 28?033 first transplants (41% allogeneic, 59% autologous). The main indications were leukemias (31%; 92% allogeneic), lymphomas (58%; 12% allogeneic), solid tumors (5%; 6% allogeneic) and non-malignant disorders (6%; 88% allogeneic). There were more unrelated than HLA-identical sibling donors (51 vs 43%) for allogeneic HSCT; the proportion of peripheral blood as stem cell source was 99% for autologous and 71% for allogeneic HSCT. Allogeneic and autologous HSCT continued to increase by about 1000 HSCT per year since 2004. Patterns of increase were distinct and different. In a trend analysis, allogeneic HSCT increased in all World Bank Categories (P=0.01, two sided; all categories), autologous HSCT increased in middle- (P=0.01, two sided) and low-income (P=0.01, two sided) countries. EBMT practice guidelines appeared to have an impact on trend, with a clear increase in absolute numbers within the categories ‘standard' and ‘clinical option' for both allogeneic and autologous HSCT (P=0.01, two sided; for both allogeneic and autologous HSCT) and a clear decrease in autologous HSCT for the ‘developmental' and ‘generally not recommended' indications (P=0.01, two sided). These data illustrate the status and trends of HST in Europe.
Die im Elektrizitätsmarkt als Swing-Optionen bekannten Derivate sind hinsichtlich ihres Charakters und ihrer Einsatzgebiete klassischen Call- und Put-Optionen aus der Finanzwelt ähnlich. So geben Swing-Optionen dem Optionshalter das Recht, während der vereinbarten Ausübungsperiode Energie zu einem vertraglich festgelegten Preis zu kaufen (Call) oder zu verkaufen (Put). Analog den klassischen Finanzoptionen eignen sich Swing-Optionen daher einerseits als Absicherungsinstrumente, andererseits lassen sich spekulative Interessen verfolgen. Die Bewertung von Swing-Optionen erweist sich jedoch als ungleich schwerer, denn oft ist eine solche Option nicht nur durch Rechte, sondern auch durch Verpflichtungen gekennzeichnet. Der hohen Komplexität dieser Derivate kann man mit numerischen Bewertungsmethoden begegnen.
