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

De novo Drug Design using Reinforcement Learning with Multiple GPT Agents

De novo drug design is a pivotal issue in pharmacology and a new area of focus in AI for science research. A central challenge in this field is to generate molecules with specific properties while also producing a wide range of diverse candidates. Although advanced technologies such as transformer models and reinforcement learning have been applied in drug design, their potential has not been fully realized. Therefore, we propose MolRL-MGPT, a reinforcement learning algorithm with multiple GPT agents for drug molecular generation. To promote molecular diversity, we encourage the agents to collaborate in searching for desirable molecules in diverse directions. Our algorithm has shown promising results on the GuacaMol benchmark and exhibits efficacy in designing inhibitors against SARS-CoV-2 protein targets. The codes are available at: https://github.com/HXYfighter/MolRL-MGPT.Comment: Accepted by NeurIPS 202

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