We propose a novel framework to analyze the potentially heterogeneous roles played by different market participants in the fire-sale process during market crash and illustrate the methodology with the 2015–16 Chinese stock market turbulence. Unlike conventional analysis focusing on one...

Online Appendix of “Steering via Algorithmic Recommendations” Chen and Tsai (2019)This paper studies whether self-preferencing affects algorithmic recommendations on dominant platforms. We focus on the dual role of Amazon.com as a platform owner and retailer. We find that products sold by...

We examine the impact of data access within a vertically integrated e-commerce platform. Using a unique daily panel, we find that both the platform owner and third-party sellers base pricing on past sales, but only the owner exploits competitors' sales data. We estimate a price competition model...

Given limited network information, we consider robust risk quantification under the Eisenberg-Noe model for financial networks. To be more specific, motivated by the fact that the structure of the interbank network is not completely known in practice, we propose a robust optimization approach to...

Autonomous vehicles (AVs) are expected to operate on Mobility-on-Demand (MoD) platforms because AV technology enables flexible self-relocation and system-optimal coordination. Unlike the existing studies, which focus on MoD with pure AV fleet or conventional vehicles (CVs) fleet, we aim to...

Electricity power grid operations require information about demand and supply on a variety of timescales and areas. The advent of significant generation contributions by time variable renewable energy sources means that forecasting methods are increasingly required. Some of the earliest...

We derive and analyze Monte Carlo estimators of price sensitivities ("Greeks") for contingent claims priced in a diffusion model. There have traditionally been two categories of methods for estimating sensitivities: methods that differentiate paths and methods that differentiate densities. A...

We study optimal double stopping problems driven by a Brownian bridge. The objective is to maximize the expected spread between the payoffs achieved at the two stopping times. We study several cases where the solutions can be solved explicitly by strategies of threshold type.