Table of Contents

Split-second Decision-Making in the Field: Response Times in Mobile Advertising

Khai Chiong, University of Texas at Dallas - Naveen Jindal School of Management
Matthew Shum, California Institute of Technology
Ryan Webb, University of Toronto
Richard Chen, Happy Elements, Inc.

Neural Network for CVA: Learning Future Values

Jian-Huang She, Wells Fargo Bank
Dan Grecu, Wells Fargo Bank


"Split-second Decision-Making in the Field: Response Times in Mobile Advertising" Free Download

KHAI CHIONG, University of Texas at Dallas - Naveen Jindal School of Management
MATTHEW SHUM, California Institute of Technology
RYAN WEBB, University of Toronto
RICHARD CHEN, Happy Elements, Inc.

In this paper we take the class of drift-diffusion models from psychology and neuroeconomics, which were developed to jointly explain subjects’ choices and decision times in quick, split-second decision tasks in laboratory experiments, to a field setting -- app users’ response to video advertisements on their mobile devices. We specify a two-stage drift-diffusion model to accommodate features of mobile advertisements. In most mobile advertising platforms, including our application, ads are “non-skippable? -- that is, users are forced to watch the ad in its entirety. We use our estimates to simulate the counterfactual of “skippable? ads, and we find that permitting users to take an action while the ad is still playing would lead to lower click-through rates. While this finding rationalizes industry practice, the effects are very heterogeneous across users.

"Neural Network for CVA: Learning Future Values" Free Download

JIAN-HUANG SHE, Wells Fargo Bank
DAN GRECU, Wells Fargo Bank

A new challenge to quantitative finance after the recent financial crisis is the study of credit valuation adjustment (CVA), which requires modeling of the future values of a portfolio. In this paper, following recent work in [Weinan E(2017), Han(2017)], we apply deep learning to attack this problem. The future values are parameterized by neural networks, and the parameters are then determined through optimization. Two concrete products are studied: Bermudan swaption and Mark-to-Market cross-currency swap. We obtain their expected positive/negative exposures, and further study the resulting functional form of future values. Such an approach represents a new framework for modeling XVA, and it also sheds new lights on other methods like American Monte Carlo.


About this eJournal

This eJournal distributes working and accepted paper abstracts focused on research where economic outcomes are the product of many individual decisions, constrained by scarcity, and equilibrium forces that simultaneously shape a person's social networks and the institutionally defined rules of the game. Decisions are made by computations in the brain which produce action-choices that directly affect the homeostatic wellbeing of the individual and choices that indirectly change wellbeing by changing an individual's future constraints, the scope of their social networks, and their message sending rights within the institutions they participate. Neuroeconomics broadly speaking is interested in the study of these computations and the resulting choices they produce. This includes experiments that attempt to understand the mechanisms of neuronal computations that produce action-choices, theories which predict how neuronal computations in socio-economic environments produce decisions, outcomes and wellbeing, and policy which use our understanding of neuoroeconomic behavior to either build or defend better solutions to societal problems.

Editors: Michael C. Jensen, Harvard University, and Kevin A. McCabe, George Mason University


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Advisory Board

Neuroeconomics eJournal

Harris & Harris Group Professor, Massachusetts Institute of Technology (MIT) - Sloan School of Management, National Bureau of Economic Research (NBER), Principal Investigator, Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Professor, Baylor University - Department of Neuroscience

Professor of Economics and Law, Chapman University - Economic Science Institute, Chapman University School of Law