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Purpose: The present study aims to test the Quadratic Programming model for Optimal Portfolio selection empirically.

Need for the Study: All the investors who buy financial products are motivated to obtain higher profits or, in other words, to maximise their returns. However, the high returns are often accompanied by higher risks, and avoiding such risks has become the primary concern for all investors. There is a great need for such a model to maximise profits and minimise risk, which can help design an investment portfolio with minimum risk and maximum return. The Quadratic Programming model is one such model which can be applied for selected shares to build an optimised portfolio.

Methodology: This study optimises the stock samples using a two-level screening of correlation coefficient and coefficient of variation. The monthly closing prices of the NSE-listed Indian pharmaceutical stocks from December 2019 to January 2022 have been used as sample data. The Lagrange Multiplier method is used to apply the model to achieve the optimal portfolio solution. Based on the market reality, the transaction costs have also been considered. The Quadratic programming model is further optimised to achieve the optimal portfolio for the select stocks.

Findings: The traditional portfolio theory and the modified quadratic model gives similar and consistent results. In other words, the modified quadratic model asserts the accuracy of the conventional portfolio model. The portfolio constructed in the present study gives a return much higher than the return of the benchmark portfolio of Nifty Fifty, indicating the usefulness of applying the Quadratic Programming model.

Practical Implications: The construction of an optimal portfolio using the traditional or modified Quadratic model can help investors make rational investment decisions for better returns with lower risks.

This contribution discusses a continuum model of large discrete networks in planar domains. For this model, the Kirchhoff law, boundary conditions and capacity constraints lead in a system optimisation approach to a infinite dimensional constrained optimisation problem and to “mixed” variational inequalities. Mixed finite element methods can be formulated for these variational inequalities such that computable discretizations of the continuum problem are obtained.

Since the appearance of Simon Rottenberg's seminal paper on the baseball players' labour market in the Journal of Political Economy (1956), the literature on the economics of professional team sports has increased rapidly, fuelled by major changes in the restrictive rules which had pervaded these sports, themselves a consequence of battles in the courts and the collective bargaining arena. These changes have not been limited to North America, to which most of the literature relates, but also apply to Western Europe and Australia in particular. This monograph surveys this literature covering those various parts of the world in order to draw out both theoretical and empirical aspects. However, to argue that the existence of what is now an extensive literature “justifies” such a survey on professional team sports clearly begs a number of questions. Justification can be found in at least two major aspects.

Self‐consistent electrothermal simulation of modern semiconductor devices is required for the accurate and efficient design and optimization of many semiconductor devices. The need to perform this type analysis in order to predict the behavior of power devices was realized many years ago. It is now clear that nonisothermal analysis can be very important for VLSI devices as well.

Outlines the role of the conservatism inherent in generally accepted accounting principles in Ohlson’s (1995) and Feltham and Ohlson’s (1995) valuation models and compares it with other research findings. Identifies potential sources of conservatism (e.g. expensing advertising costs, providing for deferred tax etc.), develops a mathematical model and applies it to 1980‐1994 US data to examine their relative importance. Finds that intensity of R&D and age of fixed assets are the most significant and goes on to compare the effectiveness of the Feltham/Ohlson conservatism parameter in capturing this information. Shows that their linear information models seems to capture different aspects of the relationship between book and market values and calls for further research.

The purpose of this paper is to present the efficient iterative methods for solving linear complementarity problems (LCP), using a class of pre-conditioners.

By using the concept of solving the fixed-point system of equations associated to the LCP, pre-conditioning techniques and Krylov subspace methods the authors design some projected methods to solve LCP. Furthermore, within the computational framework, some models of pre-conditioners candidates are investigated and evaluated.

The proposed algorithms have a simple and graceful structure and can be applied to other complementarity problems. Asymptotic convergence of the sequence generated by the method to the unique solution of LCP is proved, along with a result regarding the convergence rate of the pre-conditioned methods. Finally, a computational comparison of the standard methods against pre-conditioned methods based on Example 1 is presented which illustrate the merits of simplicity, power and effectiveness of the proposed algorithms.

Comparison between the authors' methods and other similar methods for the studied problem shows a remarkable agreement and reveals that their models are superior in point of view rate of convergence and computing efficiency.

For solving LCP more attention has recently been paid on a class of iterative methods called the matrix-splitting such as AOR, MAOR, GAOR, SSOR, etc. But up to now, no paper has discussed the effect of pre-conditioning technique for matrix-splitting methods in LCP. So, this paper is planning to fill in this gap and the authors use a class of pre-conditioners with iterative methods and analyze the convergence of these methods for LCP.

In 2015, Idris Elba declared ‘I’m probably the most famous Bond actor in the world … and I’ve not even played the role’. Speculation about Elba taking on the role of the world’s most famous spy has circulated for over a decade, fuelled by current Bond Daniel Craig’s assertion that the role has ruined his life. This chapter will examine the role of fans in driving hype about the future of Bond, focusing on the case study of alt-right outrage at the potential casting of Elba. The anti-Elba camp have framed their outrage as informed by authorial intent, and the desire to maintain canon, with claims that Ian Fleming’s Bond was, and should always be white and Scottish. Bond’s expansive narrative universe has remained constant since its inception, enabling fans of the series to form an emotional connection and sense of ownership over the text as a cohesive brand, a form of ‘affective economics’ (Hills, 2015; Jenkins, 2006a). By situating the debate over Elba’s suitability within the timeline of the Bond franchise, the author will posit that the rigid casting and structure of the film series to date enables feelings of fan ownership to flourish. Whilst the influence of vocal fan groups has altered the future direction of numerous popular texts, this chapter will suggest that the sameness of Bond-as-brand provides the justification for fan backlash towards potential change. In sum, this chapter will highlight the Elba-as-Bond rumours as a reflection of the contemporary political moment which seeks to flatten out difference under the auspice of protecting the canon and tradition of ‘brand Bond’.

Everyday conversation has not yet been assigned its full role in public discussion of citizen’s issues, despite the growing number of studies about it. Casual conversations are not usually regarded as a particularly privileged place for political discussions mainly because of its apparent lack of organization following the principles and rules of the deliberative tradition in Political Studies. However, due to its closeness, informality, and personal proximity, it is particularly adequate to rise political aspects of everyday lives that otherwise would not be publicly disclosed. But how to grasp the spontaneity of everyday conversation? This chapter argues that focus groups, as a research method, are fit to observe and understand real-time ordinary conversation on political issues. In what follows, the argument goes threefold: (1) it contrasts “conversation” with “deliberation” from a micro-point of view; (2) all conversation, as a discourse embroiled in power relations, is political in a broad sense (3) as it brings forward personal views and experiences, casual conversations defies the borders between public and private issues.

The authors' objective in this paper is to find the numerical solutions of obstacle, unilateral and contact second‐order boundary‐value problems.

To achieve this, the authors formulate a spatially adaptive grid refinement scheme following Galerkin's finite element method based on a weighted‐residual. A residual based a‐posteriori error estimation scheme has been utilized for checking the approximate solutions for various finite element grids. The local element balance has been considered as an error assessment criterion. The approach utilizes piece‐wise linear approximations utilizing linear Langrange polynomials. Numerical experiments indicate that local errors are large in regions where the gradients are large.

A comparison of the spatially adaptive grid refinement with that of uniform meshing for second order obstacle boundary value problems confirms the superiority of the scheme without increasing the number of unknown coefficients.

The authors believe the work has merit not only in terms of the approach but also of the problem solved in the paper.

This paper aims to improve the radial basis fuction mesh morphing method. During a shape optimization based on computational fluid dynamic (CFD) solvers, the mesh has to be changed. Two possible strategies are re-meshing or morphing. The morphing one is advantageous because it preserves the mesh connectivity, but it must be constrained.

RBF mesh deformation is one of the most robust and accurate morphing method. Using a greedy algorithm, the computational cost of the method is reduced. To evaluate the morphing performances, a rib shape optimization is performed using the NSGA-II algorithm coupled to kriging metamodels based on CFD. The morphing method is then compared to a re-meshing strategy.

The authors propose a method, based on Schur complement, to speed-up the greedy process. By using the information of the previous iteration, smaller linear systems are solved and time is saved. The optimization results highlight the interest of using a morphing-based metamodel regarding the resolution time and the accuracy of the interpolated solutions.

A new method based on Schur complement is addressed to speed-up the greedy algorithm and successfully applied to a shape optimization.