The dynamic pricing problem concerns the determination of selling prices over time for a product whose demand is random and whose supply is fixed. We approach this problem in a novel way by formulating a dynamic optimization model in which the demand function is iso-elastic but the random demand process is quite general. Ultimately, what we find is a strong parallel between the dynamic pricing ...

Services vary widely in whether they offer their customers only subscription-based plans, à la carte plans or a mix of both. A priori, it is not obvious which type of plans a retailer should offer and what their optimal prices would be. What makes this analysis complex is that such decisions have to incorporate consumers’ expectation of usage, which may itself be influenced by the offered prici...

Predictive pricing (e.g., Google’s “Smart Pricing” and Yahoo’s “Quality-Based Pricing”) and revenue sharing are two important tools that online advertising networks can use in order to attract content publishers and advertisers. We develop a simple model of the pay-per-click advertising market to study the market effects of these tools. We then present an algorithm, PricingPolicy, for computing...

A monopolist sells informative experiments to heterogeneous buyers who face a decision problem. Buyers differ in their prior information, and hence in their willingness to pay for additional signals. The monopolist can profitably offer a menu of experiments. Even under costless acquisition and degrading of information, the optimal menu is quite coarse. The seller offers at most two experiments,...

Over the past few years, ride-sharing has emerged as an e ective way to relieve tra c congestion. A key problem for these platforms is to come up with a revenue-optimal (or GMV-optimal) pricing scheme and an induced vehicle dispatching policy that incorporate geographic and temporal information. In this paper, we aim to tackle this problem via an economic approach. Modeled naively, the underlyi...

Pricing Asian options based on the arithmetic average, under the Black and Scholes model, involves estimating an integral (a mathematical expectation) for which no analytical solution is available. Pricing their American-style counterparts, which provide early exercise opportunities, poses the additional difficulty of solving a dynamic optimization problem to determine the optimal exercise stra...

Vendor selection decisions are complicated by the fact that various conflicting multi-objective factors must be considered in the decision making process. The problem of vendor selection becomes still more compli-cated with the inclusion of incremental discount pricing schedule. Such hard combinatorial problems when solved using meta heuristics produce near optimal solutions. This paper propose...

Purpose: Simulating markets using agent‐based models must consider pricing. How‐ ever, the strategic nature of prices limits the development of agent‐based models with endogenous price competition. Methods: I propose an agent‐based algorithm based on Game Theory that allows us to simulate the pricing in different markets. I test the algorithm in five theoretical economic models from the industr...

We deal with the pricing of callable Russian options. A callable Russian option is a contract in which both of the seller and the buyer have the rights to cancel and to exercise at any time, respectively. The pricing of such an option can be formulated as an optimal stopping problem between the seller and the buyer, and is analyzed as Dynkin game. We derive the value function of callable Russia...

The optimal geometric mean return is an important property of an asset. As a derivative of the underlying asset, the option also has this property. In this paper, we show that the optimal geometric mean returns of a stock and its option are the same from Kelly criterion. It is proved by using binomial option pricing model and continuous stochastic models with self-financing assumption. A simula...