Approximate Solution for Barrier Option Pricing Using Adaptive Differential Evolution With Learning Parameter

Febrianti, Werry; Sidarto, Kuntjoro Adji; Sumarti, Novriana

doi:10.13164/mendel.2022.2.076

Cited by 3 publications

(3 citation statements)

References 19 publications

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“…Although there has been an explosion of "novel" evolutionary methods that draw on these principles [38][39][40], many of which were found to hide their lack of novelty behind a flawed experimental analysis [41][42][43][44] or a metaphor-rich jargon [45,46], these techniques are still among the most-utilized methods for diverse and complex applications, where the use of standard optimization methods is either found to be inadequate or overly computationally demanding [47,48]. Among these applications are for instance the design of mechanical components [49], quantum operators [50] or airfoil geometry [51], landslide displacement prediction [52], inverse kinematics control of a robot [53], or barrier option pricing in economics [54].…”

Section: Evolutionary Algorithmsmentioning

confidence: 99%

Evolutionary Computation Techniques for Path Planning Problems in Industrial Robotics: A State-of-the-Art Review

Juříček,

Parák,

Kůdela

2023

Computation

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The significance of robot manipulators in engineering applications and scientific research has increased substantially in recent years. The utilization of robot manipulators to save labor and increase production accuracy is becoming a common practice in industry. Evolutionary computation (EC) techniques are optimization methods that have found their use in diverse engineering fields. This state-of-the-art review focuses on recent developments and progress in their applications for industrial robotics, especially for path planning problems that need to satisfy various constraints that are implied by both the geometry of the robot and its surroundings. We discuss the most-used EC method and the modifications that suit this particular purpose, as well as the different simulation environments that are used for their development. Lastly, we outline the possible research gaps and the expected directions future research in this area will entail.

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Section: Evolutionary Algorithmsmentioning

confidence: 99%

Evolutionary Computation Techniques for Path Planning Problems in Industrial Robotics: A State-of-the-Art Review

Juříček,

Parák,

Kůdela

2023

Computation

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“…Although options and structured warrants are quite different, the pricing method could be similar due to their properties. Some research about option pricing using adaptive differential evolution and option portfolio construction are [7] and [20].…”

Section: Introductionmentioning

confidence: 99%

Stock and Structured Warrant Portfolio Optimization Using Black-Litterman Model and Binomial Method

Jayadi,

Sumarti

2023

mendel

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In recent years, the number of Indonesian investors has rapidly increased during the COVID-19 pandemic which happened all around the world. There have been a massive number of influencers in social media who were promoting investment. Although stocks and warrants are interesting choices, mutual funds still become the main ones for beginners. Therefore, this research focuses on the development of a stock portfolio model using the Black-Litterman method which involves the investor’s views towards the stock returns. The research refers to one of the largest equity funds in Indonesia, that is Sucorinvest Equity Fund, by using the top ten of its stocks that are majority in the fund (as of April 28, 2023). Furthermore, this research also constructs a structured warrant portfolio, but it is separated from the initially constructed stock portfolio. Structured warrants could be an appropriate choice for low-budget investors. It was newly introduced in Indonesia in September 2022 so it is interesting to be observed. Based on the results and the implemented assumptions, the return obtained from the stock portfolio is superior to the observed fund’s return. Meanwhile, call structured warrant portfolio using the existing product in the market yields a negative return, because the exercise price and warrant offered price were too high. Thus, structured warrants could be considered overpriced at the moment, so the chance of obtaining profit is extremely small. Due to its similar properties to call and put options, we propose the warrant pricing and use it in simulations, so in the future, structured warrants may become an attractive instrument for the investors.

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“…Among them are classical techniques such as the genetic algorithm (GA), the evolutionary strategy (ES), differential evolution (DE), or particle swarm optimization (PSO). Many of these methods found their use in diverse and complex applications, where the utilization of exact optimization algorithms was either found to be inadequate or computationally too expensive [9], such as the design of mechanical components [10] and quantum operators [11], feature selection [12,13], landslide displacement prediction [14], airfoil geometry design [15], or barrier option pricing in economics [16]. Another class of methods that is popular for such complex optimization problems is the class of the deterministic DIRECT (which is an acronym of DIviding RECTangles) algorithms [17].…”

Section: Introductionmentioning

confidence: 99%

Chance-Constrained Optimization Formulation for Ship Conceptual Design: A Comparison of Metaheuristic Algorithms

Kudela

2023

Computers

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This paper presents a new chance-constrained optimization (CCO) formulation for the bulk carrier conceptual design. The CCO problem is modeled through the scenario design approach. We conducted extensive numerical experiments comparing the convergence of both canonical and state-of-the-art metaheuristic algorithms on the original and CCO formulations and showed that the CCO formulation is substantially more difficult to solve. The two best-performing methods were both found to be differential evolution-based algorithms. We then provide an analysis of the resulting solutions in terms of the dependence of the distribution functions of the unit transportation costs and annual cargo capacity of the ship design on the probability of violating the chance constraints.

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Approximate Solution for Barrier Option Pricing Using Adaptive Differential Evolution With Learning Parameter

Cited by 3 publications

References 19 publications

Evolutionary Computation Techniques for Path Planning Problems in Industrial Robotics: A State-of-the-Art Review

Evolutionary Computation Techniques for Path Planning Problems in Industrial Robotics: A State-of-the-Art Review

Stock and Structured Warrant Portfolio Optimization Using Black-Litterman Model and Binomial Method

Chance-Constrained Optimization Formulation for Ship Conceptual Design: A Comparison of Metaheuristic Algorithms

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