An expansion in the model space in the context of utility maximization

In the framework of an incomplete financial market where the stock price dynamics are modeled by a continuous semimartingale (not necessarily Markovian), an explicit second-order expansion formula for the power investor’s value function—seen as a function of the underlying market price of risk process—is provided. This allows us to provide first-order approximations of the optimal primal and dual controls. Two specific calibrated numerical examples illustrating the accuracy of the method are also given.     

A risk-neutral equilibrium leading to uncertain volatility pricing

We study the formation of derivative prices in an equilibrium between risk-neutral agents with heterogeneous beliefs about the dynamics of the underlying. Under the condition that short-selling is limited, we prove the existence of a unique equilibrium price and show that it incorporates the speculative value of possibly reselling the derivative. This value typically leads to a bubble; that is, the price exceeds the autonomous valuation of any given agent. Mathematically, the equilibrium price operator is of the same nonlinear form that is obtained in single-agent settings with worst-case aversion against model uncertainty. Thus, our equilibrium leads to a novel interpretation of this price.     

Chebyshev interpolation for parametric option pricing

Recurrent tasks such as pricing, calibration and risk assessment need to be executed accurately and in real time. We concentrate on parametric option pricing (POP) as a generic instance of parametric conditional expectations and show that polynomial interpolation in the parameter space promises to considerably reduce run-times while maintaining accuracy. The attractive properties of Chebyshev interpolation and its tensorized extension enable us to identify broadly applicable criteria for (sub)exponential convergence and explicit error bounds. The method is most promising when the computation of the prices is most challenging. We therefore investigate its combination with Monte Carlo simulation and analyze the effect of (stochastic) approximations of the interpolation. For a wide and important range of problems, the Chebyshev method turns out to be more efficient than parametric multilevel Monte Carlo. We conclude with a numerical efficiency study.     

Explosion in the quasi-Gaussian HJM model

We study the explosion of the solutions of the SDE in the quasi-Gaussian HJM model with a CEV-type volatility. The quasi-Gaussian HJM models are a popular approach for modeling the dynamics of the yield curve. This is due to their low-dimensional Markovian representation which simplifies their numerical implementation and simulation. We show rigorously that the short rate in these models explodes in finite time with positive probability, under certain assumptions for the model parameters, and that the explosion occurs in finite time with probability one under some stronger assumptions. We discuss the implications of these results for the pricing of the zero coupon bonds and Eurodollar futures under this model.     

Stochastic evolution equations in Banach spaces and applications to the Heath–Jarrow–Morton–Musiela equations

The aim of this paper is threefold. Firstly, we study stochastic evolution equations (with the linear part of the drift being a generator of a \(C_{0}\)-semigroup) driven by an infinite-dimensional cylindrical Wiener process. In particular, we prove, under some sufficient conditions on the coefficients, the existence and uniqueness of solutions for these stochastic evolution equations in a class of Banach spaces satisfying the so-called \(H\)-condition. Moreover, we analyse the Markov property of the solutions.Secondly, we apply the abstract results obtained in the first part to prove the existence and uniqueness of solutions to the Heath–Jarrow–Morton–Musiela (HJMM) equations in weighted Lebesgue and Sobolev spaces.Finally, we study the ergodic properties of the solutions to the HJMM equations. In particular, we find a sufficient condition for the existence and uniqueness of invariant measures for the Markov semigroup associated to the HJMM equations (when the coefficients are time-independent) in the weighted Lebesgue spaces.Our paper is a modest contribution to the theory of financial models in which the short rate can be undefined.     

Workload control under continuous order release

Workload control is a production planning and control concept specifically designed for complex manufacturing environments. Past research on Workload control has been essentially focused on discrete order release. This means that release of orders to the shop floor takes places on a periodic basis. Continuous order release has been somehow neglected, in spite of its apparent potential for improving system performance, including the reduction of order flow times. This paper presents a simulation study of this order release approach. The study contributes for improving the basis for setting workload norms, selecting the workload control strategy and deciding upon routing alternatives under continuous order release.     

Public Sector Organizations and Cocreation With Citizens: A Literature Review on Benefits,Drivers, and Barriers

ABSTRACT

Cocreation has captured the attention of public managers and policymakers and yet the literature focusing in the public sector is still relatively dispersed. In this literature review we present a contextualized analysis of the potential reasons that lead public sector organizations to cocreate with citizens and identify potential barriers that may hamper the adoption of cocreation in public settings. The analysis undertaken allowed us to conclude that the topic is increasingly capturing the interest of researchers, although the state of the literature is characterized by a reduced heterogeneity in research methods. We classified cocreation benefits in the public sector as innovation related, improved decision-making, and symbolic related, and we categorized the drivers for cocreation according to three broad categories: external, relation-specific and internal. Finally, we identified potential barriers of cocreation, including structural, organizational, and behavioral barriers.     

To post or not to post: social media sharing and sporting event performance

Social networks are becoming increasingly important for consumers, especially in the context of sport, where the service experience is highly intense. Few studies have combined subjective event performance variables and social network variables to analyze social network content sharing by sports practitioners. This article investigates the use of social networks in relation to sporting events. An empirical study examined the role of social network variables and sporting event performance variables in social media use. The sample consisted of 410 triathletes (72.2% male) aged between 18 and 66 years (mean 37.03 ± 8.62). Four analyses were performed using fuzzy‐set qualitative comparative analysis to examine the causes of sharing comments through social media, sharing photos and videos on social media, participant satisfaction, and word‐of‐mouth (WOM). The event's general image was a necessary condition in all cases. The combination of participants’ satisfaction and positive event image and the combination of social network use and positive event image lead to social network content sharing by athletes. The combination of positive event image and participant satisfaction leads to a positive WOM.