financial engineering
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10.1142/12725 ◽  
2022 ◽  
Author(s):  
Giuseppe Orlando ◽  
Michele Bufalo ◽  
Henry Penikas ◽  
Concetta Zurlo

2021 ◽  
pp. 299-314
Author(s):  
Andrew C. A. Elliott

The board game backgammon illustrates that we can control the effects of risk by understanding chances, controlling our exposure to risk, and attending to the preparation of our responses. If we understand the risks we face in a financial context, hedging strategies can allow us to shape the overall risk by offsetting some or all of it, but this comes at a price. Financial futures and options are some of the tools that allow financial risks to be shaped in creative ways. Where risks are poorly understood, though, these financial engineering approaches may not always be effective, and have in the past led to financial difficulties.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yongjian Qiu ◽  
Yuming Zhu ◽  
Jingben Yin

This paper presents an efficient branch-and-bound algorithm for globally solving a class of fractional programming problems, which are widely used in communication engineering, financial engineering, portfolio optimization, and other fields. Since the kind of fractional programming problems is nonconvex, in which multiple locally optimal solutions generally exist that are not globally optimal, so there are some vital theoretical and computational difficulties. In this paper, first of all, for constructing this algorithm, we propose a novel linearizing method so that the initial fractional programming problem can be converted into a linear relaxation programming problem by utilizing the linearizing method. Secondly, based on the linear relaxation programming problem, a novel branch-and-bound algorithm is designed for the kind of fractional programming problems, the global convergence of the algorithm is proved, and the computational complexity of the algorithm is analysed. Finally, numerical results are reported to indicate the feasibility and effectiveness of the algorithm.


2021 ◽  
Vol 1 (3) ◽  
pp. 56-88
Author(s):  
Ahmad Muhammad Assa’d ◽  
Alaa Khalid Albusaili

The rooting methodological concepts of Islamic Financial Engineering was not free of being overlapped, especially since there is no mechanism controlling the efforts made in financial transactions. Thus, there was a need to enhance awareness of the most effective fundamentalist tools and to organize their ABCs according to Sharia data. Therefore, through demonstrating the methodology of formulating Islamic financial engineering tools, the current study aims to identify the concepts of Means and Pretexts. In describing and analyzing the concepts, as well as revealing the relationship between their different dimensions, the descriptive deductive approach was used. The researcher recommends Islamic financial engineering scholars to attract their attention towards the importance of developing a clear methodology related to eliciting contemporary financial judgments.


2021 ◽  
Vol 58 (2) ◽  
pp. 347-371
Author(s):  
Yan Qu ◽  
Angelos Dassios ◽  
Hongbiao Zhao

AbstractThere are two types of tempered stable (TS) based Ornstein–Uhlenbeck (OU) processes: (i) the OU-TS process, the OU process driven by a TS subordinator, and (ii) the TS-OU process, the OU process with TS marginal law. They have various applications in financial engineering and econometrics. In the literature, only the second type under the stationary assumption has an exact simulation algorithm. In this paper we develop a unified approach to exactly simulate both types without the stationary assumption. It is mainly based on the distributional decomposition of stochastic processes with the aid of an acceptance–rejection scheme. As the inverse Gaussian distribution is an important special case of TS distribution, we also provide tailored algorithms for the corresponding OU processes. Numerical experiments and tests are reported to demonstrate the accuracy and effectiveness of our algorithms, and some further extensions are also discussed.


2021 ◽  
Vol 39 (4) ◽  
pp. 515-532
Author(s):  
Guangbao Guo & Weidong Zhao

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