RTB Formulation Using Point Process

TL;DR

This paper introduces a stochastic point process framework for modeling repeated auctions in RTB, enabling analysis of various auction scenarios and optimal strategies, with a focus on joint utility-market distributions.

Contribution

It presents a novel, flexible point process model for RTB auctions, including theoretical approximation results and strategies considering joint distributions.

Findings

Framework can approximate to Poisson processes for analysis

Optimal strategies depend on joint utility and market condition distributions

Provides theoretical basis for modeling and strategy optimization in RTB

Abstract

We propose a general stochastic framework for modelling repeated auctions in the Real Time Bidding (RTB) ecosystem using point processes. The flexibility of the framework allows a variety of auction scenarios including configuration of information provided to player, determination of auction winner and quantification of utility gained from each auctions. We propose theoretical results on how this formulation of process can be approximated to a Poisson point process, which enables the analyzer to take advantage of well-established properties. Under this framework, we specify the player's optimal strategy under various scenarios. We also emphasize that it is critical to consider the joint distribution of utility and market condition instead of estimating the marginal distributions independently.