Inequalities for the De Pril approximation to the distribution of the number of policies with claims

In the present paper, we give sufficient conditions for an ordering of De Pril approximations of the distribution of the number of claims in an insurance portfolio of independent policies. Possible extensions are discussed, both for the De Pril approximation and the Kornya approximation. A numerical example is given.     

Target ratcheting and effort reduction

In this paper, we examine how retail store managers reduce their sales activity in response to target ratcheting. We find that managers with favorable sales performance in the first three quarters reduce their sales activity in the final quarter. We also document that managers who engage in sales reducing activities enhance their likelihood of meeting their next-year sales target, which is based on their current sales. That is, managers who reduce their sales activity in the final quarter are more likely to beat their next-year sales targets than managers who refrain from reducing their final-quarter sales.     

A Bibliometric Review of Open Innovation: Setting a Research Agenda

Through an objective, systematic, and comprehensive review of the literature on open innovation (OI), this article identifies gaps in existing research, and provides recommendations on how hitherto unused or underused organizational, management, and marketing theories can be applied to advance the field. This study adopts a novel approach by combining two complementary bibliometric methods of co‐citation analysis and text mining of 321 journal articles on OI that enables a robust empirical analysis of the intellectual streams and key concepts underpinning OI. Results reveal that researchers do not sufficiently draw on theoretical perspectives external to the field to examine multiple facets of OI. Research also seems confined to innovation‐specific journals with its focus restricted to a select few OI issues, thereby exerting limited influence on the wider business community. This study reveals three distinct areas within OI research: (1) firm‐centric aspects of OI, (2) management of OI networks, and (3) role of users and communities in OI. Thus far, studies have predominantly investigated the firm‐centric aspects of OI, with a particular focus on the role of knowledge, technology, and R&D from the innovating firm's perspective, while the other two areas remain relatively under‐researched. Further gaps in the literature emerge that present avenues for future research, namely to: (1) develop a more comprehensive understanding of OI by including diverse perspectives (users, networks, and communities), (2) direct increased attention to OI strategy formulation and implementation, and (3) enhance focus on customer co‐creation and conceptualize “open service innovation.” Marketing (e.g., service‐dominant logic), organizational behavior (e.g., communities of practice), and management (e.g., dynamic capabilities) offer suitable theoretical lenses and/or concepts to address these gaps.     

Multidimensionales Verfahren zur Bestimmung des Regelleistungsbedarfes unter Berücksichtigung von Unsicherheiten

One of the most crucial constraints in operation of electrical power supply systems is the permanent balance between generation and load. Reserve power is held ready to be able to keep this balance also in case of the occurrence of unpredictable events like power plant outages or inevitable deviations of power injections from their predicted values. At this, the allocation of operating reserves is in the field of conflict between level of reliability and cost effectiveness. The amount of reserve generation capacity required in a control area heavily depends on prediction quality which constitutes the need for high quality predictions. This article is about the influence of prediction quality on the amount of reserve generation capacity required in a control area. The algorithms for the assessment of required reserve generation capacity known from literature use the variation calculus technique to account for the aforementioned unpredictable events and prediction errors. In this article, an extension to a convolution-based method is presented in which the uncertainties of the predictions are expressed using intervals. Each parameter is represented by an independent dimension, assuming statistical independence among them. This allows the distinct analysis of each parameter’s influence on the amount of required reserve generation capacity. In addition, two methods for the visualization of the multi-dimensional results are presented, allowing a comprehensive analysis of the parameters’ influences. Standard distribution functions are used to represent the parameters for the simulation and the results are shown as probability density functions of possible imbalances. Based on forecasts of the development of conventional power plants and regenerative generation in the years 2020, 2030 and 2040, the required control power of the future German transmission system is calculated. Influences and dependencies are identified with the extended convolution-based method.     

Forecasting the US term structure of interest rates using a macroeconomic smooth dynamic factor model

We extend the class of dynamic factor yield curve models in order to include macroeconomic factors. Our work benefits from recent developments in the dynamic factor literature related to the extraction of the common factors from a large panel of macroeconomic series and the estimation of the parameters in the model. We include these factors in a dynamic factor model for the yield curve, in which we model the salient structure of the yield curve by imposing smoothness restrictions on the yield factor loadings via cubic spline functions. We carry out a likelihood-based analysis in which we jointly consider a factor model for the yield curve, a factor model for the macroeconomic series, and their dynamic interactions with the latent dynamic factors. We illustrate the methodology by forecasting the U.S. term structure of interest rates. For this empirical study, we use a monthly time series panel of unsmoothed Fama–Bliss zero yields for treasuries of different maturities between 1970 and 2009, which we combine with a macro panel of 110 series over the same sample period. We show that the relationship between the macroeconomic factors and the yield curve data has an intuitive interpretation, and that there is interdependence between the yield and macroeconomic factors. Finally, we perform an extensive out-of-sample forecasting study. Our main conclusion is that macroeconomic variables can lead to more accurate yield curve forecasts.     

BLACK–SCHOLES REPRESENTATION FOR ASIAN OPTIONS

Asian options are securities with a payoff that depends on the average of the underlying stock price over a certain time interval. We identify three natural assets that appear in pricing of the Asian options, namely a stock S, a zero coupon bond B^T with maturity T, and an abstract asset A (an “average asset”) that pays off a weighted average of the stock price number of units of a dollar at time T. It turns out that each of these assets has its own martingale measure, allowing us to obtain Black–Scholes type formulas for the fixed strike and the floating strike Asian options. The model independent formulas are analogous to the Black–Scholes formula for the plain vanilla options; they are expressed in terms of probabilities under the corresponding martingale measures that the Asian option will end up in the money. Computation of these probabilities is relevant for hedging. In contrast to the plain vanilla options, the probabilities for the Asian options do not admit a simple closed form solution. However, we show that it is possible to obtain the numerical values in the geometric Brownian motion model efficiently, either by solving a partial differential equation numerically, or by computing the Laplace transform. Models with stochastic volatility or pure jump models can be also priced within the Black–Scholes framework for the Asian options.