2015 Informs Annual Meeting

MA09

INFORMS Philadelphia – 2015

decide when they should trade more aggressively to take advantage of price movements, and when they should trade more conservatively to protect against adverse selection effects. 3 - Bettering Investment Performance using Market Implied Information Duan Li, Professor, The Chinese University of Hong Kong, Dept of Systems Eng. & Eng. Manag., Shatin, Hong Kong - PRC, dli@se.cuhk.edu.hk Financial markets are heavily driven by people’s expectations of the future. Thus portfolio decisions should take into consideration the market implied forward- looking information, in addition to the backward-looking information from historical data. This talk discusses a formal framework in identifying hidden utilities of different representative investor groups by analyzing market implied information using inverse optimization solution schemes. 4 - Optimal Spread Crossing in a Limit Order Book Xuefeng Gao, Assistant Professor, The Chinese University of Hong Kong, xfgao@se.cuhk.edu.hk, Nan Chen, Xiang Ma We study when a precommitted trader converts a limit order to a market order in algorithmic executions of orders. We formulate the problem as an optimal stopping problem. We present structural properties of the optimal strategy and show how it depends on market conditions. We also study the optimal spread crossing problem under a Bayesian learning model for the fundamental value of an asset. Our numerical experiments illustrate how the price-learning affects the optimal spread crossing time. MA07 07-Room 307, Marriott Systemic Risk Measurement: Data and Algorithmic Aspects Cluster: Risk Management Invited Session Chair: Andreea Minca, Cornell University, Ithaca, NY, Somya Singhvi, Cornell University, Ithaca, NY, United States of America, ss989@cornell.edu, Divya Singhvi, Andreea Minca We analyze portfolios of equity funds to understand their impact on other portfolios. Further, we develop an algorithm that calculates the systemic impact of a fund on a network of funds. The algorithm captures the premature liquidation in response to investor outflows for different funds. Finally, we also show that our algorithm converges. 2 - Systemic Impact in Fund Networks Part II Divya Singhvi, Cornell University, 516 University Ave, Apt. B8, Ithaca, NY, 14850, United States of America, ds576@cornell.edu, Andreea Minca, Somya Singhvi Using the holdings data for US equity funds, we implement the systemic risk measure algorithm. We analyze the second order impact of a fund on the other funds. Our analysis suggest that the network structure leads to a significant additional impact on other funds. Further, we show that the funds begin to cluster themselves into groups of high and low impact based on there network properties. 3 - Inhomogeneous Financial Networks and Contagious Links United States of America, acm299@cornell.edu 1 - Systemic Impact in Fund Networks – Part I We propose a framework for testing the possibility of large cascades in financial networks. This framework accommodates a variety of specifications for the probabilities of emergence of `contagious links’, where a contagious link leads to the default of a bank following the default of its counterparty. We give bounds on the size of the first order contagion and testable conditions for it to be small. MA08 08-Room 308, Marriott Topics in Innovative and Entrepreneurial Operations Cluster: Business Model Innovation Invited Session Chair: Onesun Steve Yoo, University College London, Gower Street, London, WC1E 6BT, United Kingdom, o.yoo@ucl.ac.uk 1 - The Time-money Trade-off for Entrepreneurs: When to Hire the First Employee? Onesun Steve Yoo, University College London, Gower Street, London, WC1E 6BT, United Kingdom, o.yoo@ucl.ac.uk, Charles Corbett, Guillaume Roels Andreea Minca, Cornell University, Ithaca, NY, United States of America, acm299@cornell.edu

Hiring the first employee is a major step in a firm’s life cycle, marking the transition from an entrepreneur-dominated firm to a phase of rapid growth. It is also a significant operational problem because how an entrepreneur operates with an employee is fundamentally different than without. We present hiring as a time money tradeoff for entrepreneurs and examine when the entrepreneur should make the hiring decision depending on whether time or money is the chief bottleneck constraint. 2 - Collective Choice in Dynamic Public Good Provision: Real Versus Formal Authority George Georgiadis, Assistant Professor, Northwestern University, 2001 Sheridan Rd, Evanston, IL, 60208, United States of America, g-georgiadis@kellogg.northwestern.edu, Renee Bowen, Nicolas Lambert We study a game in which two heterogeneous agents exert effort over time to bring a project to completion, and the project scope can be determined at any point via collective choice. A larger project scope requires greater cumulative effort and delivers higher benefits on completion. We show that the efficient agent prefers a smaller project scope than the inefficient agent, but their preferences are time-inconsistent. We study the optimal allocation of property rights to minimize disagreement. 3 - Third Party Legal Funding under Asymmetric Information Noam Shamir, Assistant Professor, Tel-Aviv University, Haim Levanon, Tel-Aviv, Israel, nshamir@post.tau.ac.il, Julia Shamir Third party legal funding describes the phenomenon in which a company that has no direct stake in a legal claim, covers the legal costs of this claim in exchange for future share of the monetary outcome of the claim. We study the implications of this phenomenon in terms of its effect on the litigation strategy and court congestion. 4 - Entrepreneurship Company Formation from University Technology Commercialization Vish Krishnan, UCSD, La Jolla, CA, 92037, United States of America, vkrishnan@ucsd.edu, Kanetaka Maki We study how the commercialization of university technologies leads to company formation and collaboration with industrial partners. Specifically, using a mathematical model and empirical testing, we detail the way in which the technology transfer offices both moderate and mediate collaboration. MA09 09-Room 309, Marriott Understanding Knowledge Sources and Politics in Technology Management Sponsor: Technology, Innovation Management & Entrepreneurship Sponsored Session Chair: Zhijian Cui, Assistant Professor of Operations and Technology Management, IE Business School, Calle de Maria de Molina 12, Madrid, 28006, Spain, Zhijian.Cui@ie.edu 1 - The Differential Effect of Knowledge Sources on Innovation Strategy: A Contingency Approach Beatriz Rodriguez-Prado, University of Valladolid, Avda. Valle del Esgueva, Valladolid, 47011, Spain, bprado@eco.uva.es, Elena Revilla, Zhijian Cui We examine how innovation strategy determines the sources of knowledge (own- generated, bought-in and co-developed) and their impact on innovation performance. Data of 9054 firms belonging to fourteen European Countries constitute the empirical base of the study. Results derived from Cluster analysis, ANOVAs and Generalized Linear Models strongly indicate investments in innovation activities may generate differential value depending on key contextual factors. 2 - The Effects of Outsourcing Knowledge on the Dynamics of Outsourcing Modes Qiong Chen, University of Science and Technology of China, School of Management, USTC, 96 Jin Zhai Road, Bao He District, Hefei, 230026, China, qiongc@g.clemson.edu, Shouqiang Wang, Gulru Ozkan-Seely, Aleda Roth We evaluate buyer’s dynamic choice of outsourcing channels: directly through in- house procurement department or indirectly through an intermediary. Using a two-period game theoretic model, we demonstrate the critical yet interesting role of outsourcing knowledge and highlight effects of direct and indirect learning on the change of buyer’s strategies over time.

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