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INFORMS Philadelphia – 2015

429

4 - Macroprudential Bank Capital Regulation in a Competitive

Financial System

Christian Opp, University of Pennsylvania, The Wharton School,

Philadelphia, United States of America,

opp@wharton.upenn.edu

,

Markus Opp, Milton Harris

We develop a tractable general equilibrium model to analyze the effects of

macroprudential bank capital regulation in an economy where firms of

heterogeneous quality and risk seek financing from competitive banks and public

markets. Our analysis provides an exact characterization of economy-wide capital

allocation and highlights that tighter capital requirements can cause more banks

to engage in value-destroying risk-shifting when banks face external financing

frictions.

WC07

07-Room 307, Marriott

Risk Management and Financial Regulation

Cluster: Risk Management

Invited Session

Chair: Xianhua Peng, Assistant Professor, Hong Kong University of

Science and Technology, Department of Mathematics, Hong Kong,

Hong Kong - PRC,

maxhpeng@ust.hk

1 - The Level of Risk-free Rate in China

Chen Yang, National University of Singapore, Department of

Mathematics, Blk S17, 10 Lower Kent Ridge Road, Singapore,

119076, Singapore,

yang.chen@u.nus.edu

, Min Dai, Steven Kou,

Zhenfei Ye

In terms of the dual fund, an innovative structured fund capable of capturing the

characteristics of both bond market and equity market, we propose an estimation

of the level of China’s risk-free rate under the Black-Scholes framework, and

semi-model-free bounds based on minimal model specification. The level of

estimation is uniformly higher than the commonly used risk-free rate proxies,

which confirms the presence of a downward bias in the level of proxies as

suggested by empirical studies.

2 - Bonus Caps, Deferrals and Bankers’ Risk-taking

Xuchuan Yuan, Risk Management Institute, National University

of Singapore, 21 Heng Mui Keng Terrace I3 Building, #04-03,

Singapore, Singapore,

rmiyuanx@nus.edu.sg

, Jussi Keppo,

Esa Jokivuolle

We model a banker’s future bonuses as a series of call options on profits and show

that bonus caps and deferrals reduce risk-taking. Optimal risk-taking depends on

the cost of risk-taking. We calibrate the model to US banking data and show that

increasing the bonus payment interval has no material impact, whereas capping

the bonus to the base salary substantially reduces risk-taking. Our results suggest

the bonus cap reduces risk-taking whereas bonus clawbacks in Dodd-Frank Act

seem ineffective.

3 - A Dual-curve Market Model for Interest Rate Derivatives

Lixin Wu, Professor, Department of Mathematics, Hong Kong

University of Science and Technology,

malwu@ust.hk

After the 2007 financial crisis, the differences among the forward rates of various

tenors are too significant to ignore, which necessitates multi-curve modeling. We

introduce the term structure of “mean-loss rates,” and adapt the LIBOR market

model to the post-crisis reality of interest-rate markets by jointly modeling a

forward-rate curve and a mean-loss rate curve of the same tenor. We then

demonstrate how the “reshuffle premium” causes the basis spreads, a belief held

by market participants.

WC08

08-Room 308, Marriott

Finance Theory and Empirics

Contributed Session

Chair: Wenqing Zhang, Assistant Professor, University of Minnesota

Duluth, 1318 Kirby Drive, LSBE, UMD, Duluth, MN, 55812,

United States of America,

wqzhang@d.umn.edu

1 - Expected Commodity Returns and Pricing Models

Gonzalo Cortazar, Pontificia Universidad Católica de Chile,

Vicuna Mackenna 4860, Santiago, Chile,

gcortaza@ing.puc.cl,

Ivo Kovacevic, Eduardo Schwartz

Commodity pricing models provide true (in addition to risk neutral) distributions

which are measured with large errors. To increase reliability risk premium

parameters should be obtained from other sources and we show that this can be

done without losing any precision in the pricing of futures contracts. We show

how the risk premium parameters can be obtained from estimations of expected

futures returns and provide alternative procedures for estimating these expected

futures returns.

2 - Sequential Global Sourcing Investment Decision Making under

Extreme Situations

Wenqing Zhang, Assistant Professor, University of Minnesota

Duluth, 1318 Kirby Drive, LSBE, UMD, Duluth, MN, 55812,

United States of America,

wqzhang@d.umn.edu,

Prasad Padmanabhan, Chia-hsing Huang

Uncertainty plays an important role in determining a decision maker’s choice

when making sequential global sourcing investment decisions. This paper

presents evidence that firms hiring adventurous managers may be able to

generally reap dividends when faced with negative cash flows (extreme or

normal) when the cost ratios are small, the investment horizons are high, and the

discount rates are small.

WC09

09-Room 309, Marriott

Innovation and Entrepreneurship I

Contributed Session

Chair: Magali Delmas, UCLA, Anderson School of Management, Los

Angeles, United States of America,

delmas@ioes.ucla.edu

1 - Optimal Product Launch Times for a Small Firm in a

Competitive Environment

Jacqueline Ng, Northwestern University, 2145 Sheridan Road,

Evanston, Il, 60208, United States of America,

jacquelineng2018@u.northwestern.edu

, Izak Duenyas,

Seyed Iravani

We consider the optimal production introduction policy for a small firm that

produces a single base product that progresses through a series of product

generations over time against a large rival firm. We develop a dynamic

programming model to analyze the small firm’s new product introduction

strategy, and prove the optimality of a threshold policy. We then compare and

contrast the optimal policy with the common time-pacing and event-pacing

product introduction policies used in practice.

2 - A Case Study - Problem Based Learning Works to Foster the

Entrepreneurial Minded Engineer

Don Reimer, College Professor, LTU, 21000 West Ten Mile Road,

Southfield, United States of America,

dreimer@ltu.edu,

Ahad Ali

This abstract focuses tools that have successfully engaged engineering students in

actively participating in learning the skills. Through the use of Problem Bases

Learning (PBL) as an interactive tool, engineering students are engaged.

Examples of engineering students engaged in PBL will be used in case studies of a

class currently being offered at LTU. The case study – Tires, Tires, Tires

Everywhere will be used to demonstrate the use of PBL in the classroom.

3 - The Dynamics of Energy Conservation: Novelty and

Framing Effects

Omar I. Asensio, UCLA, Institute of the Environment, Los

Angeles, United States of America,

omar.asensio@ucla.edu,

Magali Delmas

Using a field experiment with high frequency data, we investigate dynamic

consumer responses to information-based interventions designed to encourage

conservation behavior in the residential electricity sector. We discuss novelty and

framing effects as temporal mechanisms resulting from new consumer

innovations in appliance level metering and information technologies. Our results

on dynamic decision-making are based on 52 million observations at 1/30Hz for

118 residences over 8 months.

WC10

10-Room 310, Marriott

E-Business/Commerce I

Contributed Session

Chair: Wei Zhang, Assistant Professor, University of Hong Kong,

University of Hong Kong, Hong Kong, China,

zhangw.03@gmail.com

1 - How Many Crowd Workers should a Requester Hire on Amazon

Mechanical Turk?

Arthur Carvalho, Assistant Professor, Rotterdam School of

Management, Erasmus University, Burgemeester Oudlaan 50,

J Building, Room 35-5th Floor, Rotterdam, NA, 3038BG,

Netherlands,

carvalho@rsm.nl

, Stanko Dimitrov, Kate Larson

We investigate the optimal number of workers a requester should hire on the

crowdsourcing platform Amazon Mechanical Turk. In particular, we report the

results of three studies involving different tasks and payment schemes.

Surprisingly, we find that the optimal number of workers a requester should hire

is around 10 to 11, no matter the underlying task and payment scheme. To derive

such a result, we employ a principled analysis based on segmented linear

regression.

WC10