Cognitive User Interface for Portfolio Optimization

This paper describes the development of a chatbot as a cognitive user interface for portfolio optimization. The financial portfolio optimization chatbot is proposed to provide an easy-to-use interface for portfolio optimization, including a wide range of investment objectives and flexibility to include a variety of constraints representing investment preferences when compared to existing online automated portfolio advisory services. Additionally, the use of a chatbot interface allows investors lacking a background in quantitative finance and optimization to utilize optimization services. The chatbot is capable of extracting investment preferences from natural text inputs, handling these inputs with a backend financial optimization solver, analyzing the results, and communicating the characteristics of the optimized portfolio back to the user. The architecture and design of the chatbot are presented, along with an implementation using the IBM Cloud, SS&C Algorithmics Portfolio Optimizer, and Slack as an example of this approach. The design and implementation using cloud applications provides scalability, potential performance improvements, and could inspire future applications for financial optimization services.

Impact of dust events on the optimization of photovoltaic-wind hybrid system in desert

Reliable optimization of renewable energy systems has to be adapted to the installation site and its environmental factors. In dust event sources, the impact of dust on solar irradiance or on system’s production is not usually taken into consideration during optimization of photovoltaic (PV) or PV-wind hybrid systems. The first objective of this paper was to make observatory studies on wind velocity and lifting of Saharan dust that characterize Algerian desert which allowed us to extract a wind threshold for each event in our desert site. The second objective was to quantify this dust suspension and its negative impact, up to 47.46% on global solar irradiance (GSI) and 48.95% on photovoltaic yield effects were observed. The third and main objective of this paper was evaluating changes in optimized system when the dust impact was taken into account. To achieve that we adjusted GSI satellite data on HOMER software to dust presence, and then we run an optimization on HOMER with its GSI database and the new data, this data adjustment leads to a significant expansion of 13.70% on the size of PV generator, also 7.66% and 7.68% increase on the investment expenses and cost of energy respectively. Results obtained on this paper can be used to make PV-hybrid system’s technical and financial optimization in the main Algerian dust source trustworthy.

Financial Optimization of the Resource-Constrained Project Scheduling Problem with Milestones Payments

This article presents the resource-constrained project scheduling problem with the discounted cash flow maximization criterion from the perspective of a contractor. Cash flows are considered as the contractor’s expenses related to the execution of activities and client’s payments (revenue to the contractor) after the completion of contractual stages. To solve the problem, dedicated techniques to generate solutions and a simulated annealing algorithm are proposed. Finally, the proposed procedures are examined using the test library, Project Scheduling Library (PSPLIB). An experimental analysis identified the efficient moves and techniques for creating solutions, that is backward scheduling with optimization of completion times of project stages and triple justification.

Research on the Innovation of Supply Chain Financial Operation mode in the Pharmaceutical Circulation Field---Taking the Accounts Receivable Securitization as an Example

In recent years, the scale of China’s pharmaceutical circulation market has continued to expand, and the government has issued relevant policies to regulate the market. For example, the implementation of two-vote system has led to the increase of accounts receivable of pharmaceutical circulation enterprises year by year with a decrease of accounts receivable turnover rate and an increasing pressure of capital turnover. The enterprise accounts receivable securitization is an important way for enterprises to broaden financing channels, reduce financing costs, revitalize existing assets and improve the efficiency of asset use, while the securitization of statement type assets is the only standardized financial tool to reduce the leverage ratio of enterprises and realize financial optimization. Asset securitization can relieve the pressure of capital turnover and reduce the cost of financing. The case analysis part of this paper analyzes the factors that promote the financial innovation of enterprise’s supply chain from the macro and micro perspectives. And also from the perspective of the capital demand of upstream and downstream enterprises, this part analyzes the motivation of developing supply chain financial innovation. the innovation of supply chain financial operation mode.

Financial Optimization of a Solar-Driven Organic Rankine Cycle

The objective of this work is the financial optimization of a solar-driven organic Rankine cycle. Parabolic trough solar collectors are used as the most mature solar concentrating system and also there is a sensible storage system. The unit is examined for the location of Athens in Greece for operation during the year. The analysis is conducted with a developed dynamic model in the program language FORTRAN. Moreover, a developed thermodynamic model in Engineering Equation Solver has been used in order to determine the nominal efficiency of the cycle. The system is optimized with various financial criteria, as well as with energy criteria. The optimization variables are the collecting area and the storage tank volume, while the nominal power production is selected at 10 kW. According to the final results, the minimum payback period is 8.37 years and it is found for a 160 m2 collecting area and a 14 m3 storage tank, while for the same design point the levelized cost of electricity is minimized at 0.0969 € kWh−1. The maximum net present value is 123 k€ and it is found for a 220-m2 collecting area and a 14-m3 storage tank volume. Moreover, the maximum system energy efficiency is found at 15.38%, and, in this case, the collecting area is 140 m2 and the storage tank volume 12 m3. Lastly, a multi-objective optimization proved that the overall optimum case is for a 160-m2 collecting area and a 14-m3 storage tank.

New Safe Approximation of Ambiguous Probabilistic Constraints for Financial Optimization Problem

In financial optimization problem, the optimal portfolios usually depend heavily on the distributions of uncertain return rates. When the distributional information about uncertain return rates is partially available, it is important for investors to find a robust solution for immunization against the distribution uncertainty. The main contribution of this paper is to develop an ambiguous value-at-risk (VaR) optimization framework for portfolio selection problems, where the distributions of uncertain return rates are partially available. For tractability consideration, we deal with new safe approximations of ambiguous probabilistic constraints under two types of random perturbation sets and obtain two equivalent tractable formulations of the ambiguous probabilistic constraints. Finally, to demonstrate the potential for solving portfolio optimization problems, we provide a practical example about the Chinese stock market. The advantage of the proposed robust optimization method is also illustrated by comparing it with the existing optimization approach via numerical experiments.