Informs 2015

INFORMS Philadelphia – 2015

260

TA07

07-Room 307, Marriott

Pricing and Risk Modeling in Financial Engineering,

Operations Research

Cluster: Risk Management

Invited Session

Chair: Hongzhong Zhang, Assistant Professor, Columbia University,

1255 Amsterdam Ave, New York, NY, 10027, United States of America,

hz2244@columbia.edu

1 - Counterparty Risk in a Heterogenous Random Network Model

Stephan Sturm, Worchester Polytechnic Institute,

ssturm@wpi.edu

, Eric Schaanning

We discuss the consequences of the central clearing mandate for OTC derivatives.

Analysing the expected total and potential future counterparty exposure in a

heterogeneous random graph network allows us to analyse the consequences of

central clearing in a realistic model calibrated to actual market data.

2 - On Minimizing Drawdown Risks of Lifetime Investments

Bin Li, University of Waterloo, 200 University Avenue West, M3

Building, Waterloo, Canada,

b226li@uwaterloo.ca

David Landriault, Dongchen Li, Xinfu Chen

We study a lifetime investment problem to minimize the risk of occurrence of

significant drawdowns. We examine two financial market models and closed-form

optimal strategies are obtained. Our results show that it is optimal to minimize

the portfolio variance when the fund value is at its historic high-water mark.

When the fund value drops, the fund manager should increase the proportion

invested in the asset with a higher instantaneous rate of return.

3 - Beating the Omega Clock: An Optimal Stopping Problem with

Random Time-horizon

Hongzhong Zhang, Assistant Professor, Columbia University, 1255

Amsterdam Ave, New York, NY, 10027, United States of America,

hz2244@columbia.edu,

Neofytos Rodosthenous

We study the optimal stopping of a perpetual call option in a random time-

horizon under exponential spectrally negative Levy models. The time-horizon is

modeled as the so-called Omega default clock, which is the first time the

occupation time of the underlying process below a level exceeds an independent

exponential random variable. We show that the shape of the value function

varies qualitatively with model parameters. In particular, we show the possibility

of two disjoint continuation regions.

4 - Impact of Bayesian Learning and Externalities on

Strategic Investment

Wenxin Xu,

University of Illinois, Urbana IL 61801, United States of

America,

wxu9@illinois.edu

We investigate the interplay between learning effects and externalities in the

problem of competitive investments with uncertain returns. We find a region of a

war of attrition between the two firms in which the interplay between

externalities and learning gives rise to counterintuitive effects on investment

strategies and payoffs.

TA08

08-Room 308, Marriott

e-Business Models

Cluster: Business Model Innovation

Invited Session

Chair: Simone Marinesi, Wharton, 562 Jon M. Huntsman Hall,

3730 Walnut St, Philadelphia, PA, 19104, United States of America,

marinesi@wharton.upenn.edu

1 - Online Grocery Retailing

Elena Belavina, University of Chicago Booth School of Business,

5807 S Woodlawn Ave, Chicago, United States of America,

elena.belavina@chicagobooth.edu

Grocery delivery is a market that many try to conquer. Appropriate pricing is key

for success. There is little consensus among different players (at times even within

one firm operating in different locations) on what is the best pricing scheme. For

example, Amazon Fresh in Seattle is using per order pricing while in San

Francisco - subscription fee. We provide recommendation for the preferred

pricing scheme based on various characteristics (delivery logistics, demand

variability etc.).

2 - “If at First You Don’t Succeed”: Understanding Serial

Entrepreneurs on Kickstarter

Hallie Cho, INSEAD, 1 Ayer Rajah Avenue, Singapore, Singapore,

hallie.cho@insead.edu,

David Clough

From the crowdfunding platform Kickstarter, we have data on 27,399 technology

and design projects created by 6960 entrepreneurs—1376 of whom are serial

entrepreneurs. We examine characteristics of the projects and the entrepreneurs

to understand what distinguishes a serial entrepreneur from a one timer. For 779

of the serial entrepreneurs, their first projects were failures. We investigate how

serial entrepreneurs respond to setbacks and how their resource gathering

strategy changes over time.

3 - Wisdom or Madness? Comparing Crowds with Expert Evaluation

in Funding the Arts

Ethan Mollick, Assistant Professor, U. Penn, 2000 Steinberg Hall-

Dietrich Hall, 3620 Locust Walk, Philadelphia, PA, 19004, United

States of America,

emollick@wharton.upenn.edu

, Ramana Nanda

Drawing on a panel of experts and data from the largest crowdfunding site, we

examine funding decisions for proposed theater projects. We find significant

agreement between the funding decisions of crowds and experts. Our findings

suggest that crowdfunding can play a role in complementing expert decisions by

allowing projects the option to receive multiple evaluations and thereby lowering

the incidence of false negatives.

4 - Crowdsourcing Exploration

Yiangos Papanastasiou, Haas School of Business, UC Berkeley,

Berkeley, CA, 94720, United States of America,

yiangos@haas.berkeley.edu,

Nicos Savva, Kostas Bimpikis

In an online review platform, information on the quality of alternative service

providers is both generated and utilized by the consumer population.

Inefficiencies arise from the fact that information is generated as a byproduct of

self-interested consumer choices, rather than with the benefit of future

consumers in mind. Within a multi-armed bandit framework, we study how such

inefficiencies relate to alternative policies of information-disclosure to the

platform’s users.

TA09

09-Room 309, Marriott

Using Big Data Analytics for Technology Intelligence:

Methods and Cases to Gather Intelligence on

Technological Innovations

Sponsor: Technology, Innovation Management & Entrepreneurship