An Optimization Approach for Pricing Analysis on a Bank Wealth-Management Equity Structured Product

This paper researches on the pricing and design of a certain stock-type structured product. Firstly, a semi-analytic pricing model is deduced by discounting the payoff function of the product. Secondly, the difference between publishers\u27 and investors\u27 required rate of return is explained with market segmentation theory when estimating the pricing model’s parameters, which defines the cost and sale price of a product. Finally, with sensitivity analysis, it is concluded that publishers can increase their profits by extending the due date of the product or publishing it with relatively large asset volatility. The study aims to help publishers make reasonable product design and pricing decisions

An Optimization Approach for pricing of Discrete European Call options Based on the Preference of Investors

Firstly, a method for measuring the risk aversion of investors was proposed based on the prospect theory. Secondly, under a sole hypothetical condition in which the risk aversion degree for different assets is the same in a market, the pricing of discrete European options was given based on the objective probability. Thirdly, it was proven that the European option price obtained was a non-arbitrate price. And then, both for the binomial tree, which is a complete market, and for the trinomial tree, which is an incomplete market, pricing European options were discussed by implementing the method provided in this paper. Lastly, an illustration is used to demonstrate how to estimate preference parameters from market data and how to calculate options prices. The result states that the method in this paper is the same as the traditional risk-neutral methods in a complete market, but it is different from the traditional risk-neutral methods in an incomplete market, and more, the price obtained in this paper is affected by the objective probability and also contains the risk attitude of the investors

An Optimization Approach for pricing of Discrete European Call options Based on the Preference of Investors

Firstly, a method for measuring the risk aversion of investors was proposed based on the prospect theory. Secondly, under a sole hypothetical condition in which the risk aversion degree for different assets is the same in a market, the pricing of discrete European options was given based on the objective probability. Thirdly, it was proven that the European option price obtained was a non-arbitrate price. And then, both for the binomial tree, which is a complete market, and for the trinomial tree, which is an incomplete market, pricing European options were discussed by implementing the method provided in this paper. Lastly, an illustration is used to demonstrate how to estimate preference parameters from market data and how to calculate options prices. The result states that the method in this paper is the same as the traditional risk-neutral methods in a complete market, but it is different from the traditional risk-neutral methods in an incomplete market, and more, the price obtained in this paper is affected by the objective probability and also contains the risk attitude of the investors

An Optimization Approach for Pricing Analysis on a Bank Wealth-Management Equity Structured Product

This paper researches on the pricing and design of a certain stock-type structured product. Firstly, a semi-analytic pricing model is deduced by discounting the payoff function of the product. Secondly, the difference between publishers' and investors' required rate of return is explained with market segmentation theory when estimating the pricing model’s parameters, which defines the cost and sale price of a product. Finally, with sensitivity analysis, it is concluded that publishers can increase their profits by extending the due date of the product or publishing it with relatively large asset volatility. The study aims to help publishers make reasonable product design and pricing decisions

Industrially Scalable Textile Sensing Interfaces for Extended Artificial Tactile and Human Motion Monitoring without Compromising Comfort

Smart wearables with the capability for continuous monitoring, perceiving, and understanding human tactile and motion signals, while ensuring comfort, are highly sought after for intelligent healthcare and smart life systems. However, concurrently achieving high-performance tactile sensing, long-lasting wearing comfort, and industrialized fabrication by a low-cost strategy remains a great challenge. This is primarily due to critical research gaps in novel textile structure design for seamless integration with sensing elements. Here, an all-in-one biaxial insertion knit architecture is reported to topologically integrate sensing units within double-knit loops for the fabrication of a large-scale tactile sensing textile by using low-cost industrial manufacturing routes. High sensitivity, stability, and low hysteresis of arrayed sensing units are achieved through engineering of fractal structures of hierarchically patterned piezoresistive yarns via blistering and twisting processing. The as-prepared tactile sensing textiles show desirable sensing performance and robust mechanical property, while ensuring excellent conformability, tailorability, breathability (288 mm s ), and moisture permeability (3591 g m per day) for minimizing the effect on wearing comfort. The multifunctional applications of tactile sensing textiles are demonstrated in continuously monitoring human motions, tactile interactions with the environment, and recognizing biometric gait. Moreover, we also demonstrate that machine learning-assisted sensing textiles can accurately predict body postures, which holds great promise in advancing the development of personalized healthcare robotics, prosthetics, and intelligent interaction devices