Dynamic pricing is a kind of pricing strategy in which the price of products varies based on present demand value. So far, several research works have been reported for using neural network for pricing, such as predicting demand and modeling the customer's choices. However, less work has been performed on using them for optimizing pricing policies. In this project, we try to explain the way of combining neural network and evolutionary algorithms to optimize pricing policies. We create a neural network on the basis of demand model and benefit from evolutionary algorithms for optimizing the resulted model. This has got two privileges: First, necessary flexibilities are created by using neural network to model different demand scenarios that is occurred with different products and services, and second, using evolutionary algorithms provides us with the ability of solving complicated models. Wavelet neural network has been used and the resulted pricing policy has been compared with other demand models that are widely used. The results show that the suggested model match up well under different scenarios and presents a better pricing policy than other suggested models.
Web services have become quite popular over the last few years as they allow easier development and integration of business applications. In this paper, we consider a web service pricing problem where two providers compete through dynamic pricing. Each provider offers access to a web service with different quality classes where users may buy their required web service through a reservation system. They would like to adjust the prices of their web services over a pre-specified time horizon to manage demand and to maximize profit. Users have the right with no obligation to cancel their services as long as they pay a penalty. We consider a dynamic setting where the web service classes share a capacity. We first develop a time continuous model for competitive pricing of a web service and then we provide some insights about the equilibrium condition of the problem using open-loop differential game and propose an algorithm to obtain the optimal pricing policy for providers. Moreover, we conduct numerical analyses to examine the impacts of some parameters on control and state variables.
Risk management plays an important role in banking industry and there are literally many investigations to reduce any risk components in this industry. In this paper, we present a study on relationship between tail risk on earning management in Iranian banking industry. In this survey, we use two series of data. The first set is associated with yearly information of 19 different banks over the period 2005-2011 and it contains 114 observations. The second set of data includes weekly historical data of eight banks over the same period 2005-2011. In this survey, there are four objectives to be investigated. The first hypothesis considers the effects of seven independent variables on loan loss allowance as a fraction of total loans. The second model is associated with the effects of two independent variables on realized gains and losses on securities. The third objective is to study the effects of different independent variables with various interruptions on return of banking sectors. Finally, the last model investigates the effects of revenue management on tail risk. The result of this survey indicates that there is no relationship between tail risk and earning management.
One of the most important issues on revenue management in banking industries is the assignment of loan to customers. In fact, a big portion of banks' revenue is from loan assignment and choosing appropriate customers for loan assignment not only reduces the financial risk but also it can increase the revenue. In this study, we perform an empirical study to find out whether customers' financial statements could provide enough information about customers for loan assignment. The other objective of this study is to find out whether banks' officials could understand about the details of customers' financial statements. Finally, we want to find out whether there is any relationship between unpaid loans and customers' credit rating. The present study is executed on an Iranian bank by distributing a questionnaire analyzing the results. The results indicate that there are some strong evidence that financial statement could help bank official determine customers' credit rating. The survey also concludes that highly education and experienced employees are the best people for devoting best credit rating for customers.