A model of consumer behavior has been formulated by using an additive utility function and the hedonic pricing approach, in a virtual market. Since, there is a time lag between ordering and purchasing products (goods and services) online and receiving them, it means the consumer makes decision under uncertainty. The level of satisfaction with products with distinctive characteristics is describ...

We describe a method to generate statistical models of electricity demand from Commercial and Industrial (C&I) facilities including their response to dynamic pricing signals. Models are built with historical electricity demand data. A facility model is the sum of a baseline demand model and a residual demand model; the latter quantifies deviations from the baseline model due to dynamic pricing ...

The classic Black-Scholes option pricing model assumes that returns follow Brownian motion, but return processes differ from this benchmark in at least three important ways. First, asset prices jump, leading to non-normal return innovations. Second, return volatilities vary stochastically over time. Third, returns and their volatilities are correlated, often negatively for equities. Time-change...

We present efficient approximation algorithms for a number of problems that call for computing the prices that maximize the revenue of the seller on a set of items. Algorithms for such problems enable the design of auctions and related pricing mechanisms [3]. In light of the fact that the problems we address are APX-hard in general [5], we design near-linear and near-cubic time approximation sc...

Non-uniform distribution of customers in a region and variation of their maximum willingness to pay at distinct areas make regional pricing a practical method to maximize the profit of the distribution system. By subtracting the classic objective function, which minimizes operational costs from revenue function, profit maximization is aimed. A distribution network is designed by determining the...

The integration of marketing and demand with logistics and inventories (supply side of companies) may cause multiple improvements; it can revolutionize the management of the revenue of rental companies, hotels, and airlines. In this paper, we develop a multi-objective pricing-inventory model for a retailer. Maximizing the retailer's profit and the service level are the objectives, and shorta...

Electricity Real Time Pricing (RTP) tariffs inter alia have Demand Side Management (DSM) as a main aim. Customers are billed according to hourly fluctuating energy prices. Essentially RTP pricing signals can be seen as control inputs to change customer load usage. It is suggested that optimised pricing signals sent to RTP customers can lead to a much more efficient DSM initiative. This paper de...

We generalize an asset pricing model based on the Arbitrage Pricing Theory (APT) allowing beta to be time-varying. Making beta a random variable adds flexibility to the model because permits a non-linear relation between individual returns and the set of factors, and accounts for the effect of possible omitted variables. We integrate the conditional APT with a general linear stochastic process ...

Most US consumers are charged a near-constant retail price for electricity, despite substantial hourly variation in the wholesale market price. This paper evaluates a randomized experiment that exposed households to hourly real time pricing (RTP) and applies the demand estimates to counterfactual simulations in a structural model of the Pennsylvania-Jersey-Maryland electricity market. The model...

Options are popular financial derivatives that play essential roles in financial markets. How to price them efficiently and accurately is very important both in theory and practice. Options are often priced by the lattice model. Although the prices computed by the lattice converge to the theoretical option value under the continuous-time model, they may converge slowly. Worse, for some options ...