2016 INFORMS Annual Meeting Program

MC40

INFORMS Nashville – 2016

MC41 207C-MCC Option Pricing and Estimation of Greeks Sponsored: Financial Services Sponsored Session Chair: Xuewei Yang, Nanjing University, 22 Hankou Road, Gulou District, Nanjing, 210093, China, xwyang@nju.edu.cn 1 - Optimal Portfolio Deleveraging With Cross Asset Price Pressure Jingnan Chen, Singapore University of Technology and Design, jingnan_chen@sutd.edu.sg, Yufei Yang, Jie Zhang We study an optimal portfolio deleveraging problem, where the objective is to meet specified debt/equity requirements at the minimal execution cost. During the course of trading, permanent and temporary price impact is taken into account. In particular, we include the cross-asset price pressure which measures the impact on an asset caused by the trading of other assets. Mathematically, the optimal deleveraging problem is formulated as a non-convex quadratic program with quadratic and box constraints. We develop a successive convex optimization algorithm to obtain the optimal deleveraging strategy. 2 - A New Smooth Perturbation Analysis Approach To Sensitivity Analysis For Options With Discontinuous Payoffs Yanchu Liu, Sun Yat-sen University, liuych26@mail.sysu.edu.cn, Zhijian He, Guangwu Liu Greeks estimation is one of the most important procedures in financial risk management. Pathwise and likelihood ratio (LR) methods are two classical ways generating unbiased estimates to Greeks. The pathwise method usually has a smaller variance than the LR method. But it typically requires the payoff functions to be (Lipschitz) continuous. This paper proposes a new smooth perturbation analysis (SPA) method that can liberate the Lipschitz continuity requirement on the payoff functions. Our estimator is unbiased and can be easily implemented. Extensive numerical experiments illustrate the advantage of our method. 3 - Catastrophe Option Pricing With Auto-correlated And Catastrophe-dependent Intensity Guanying Wang, Tianjin University, Tianjin, 300072, China, wangguanyingnk@163.com A discrete-time pricing model is proposed to investigate catastrophe equity put options with auto-correlated and catastrophe-dependent intensity. Catastrophic events are assumed to occur according to a Poisson process and the intensity is affected by the numbers of catastrophic events that occurred in the past. Stochastic volatility of the underlying asset is captured by a GARCH process. We derive a pricing formula for catastrophe equity put options and then illustrate effects of the catastrophe intensity on catastrophe equity put option prices. 4 - Option Pricing Under The Price Limits Mechanism: Evidence From China Xuewei Yang, Nanjing University, xwyang@nju.edu.cn Ning Cai We study the effects of the so-called price limits mechnism (PLM) on option pricing. Our setting considers options written on 50-ETF (510050.SH) traded in Shanghai Stock Exchange of China, which is subject to the PLM. Numerical results reveal the implications of PLM on option pricing and hedging. MC42 207D-MCC Revenue Management in the Social Environment Sponsored: Revenue Management & Pricing Sponsored Session Chair: Ming Hu, University of Toronto, Toronto, ON, Canada, ming.hu@rotman.utoronto.ca 1 - Optimal Pricing In Networks With Latent Agents Ozan Candogan, Chicago Booth, Ozan.Candogan@chicagobooth.edu, Baris Ata, Alexandre Belloni We analyze the question of targeted pricing/advertising in social networks, in settings where the platform does not have full information about the underlying network. In particular, we assume that certain agents are latent, and characterize the optimal pricing rule of the platform. We establish that unlike the case with full information, in the presence of latent agents even with symmetric influence structure, using network information can significantly improve the profits of the platform. We then explore how the platform can efficiently learn the optimal prices when the latent component is small when compared to the observable part.

4 - Social Learning In The Presence Of Adversaries Lili Su, University of Illinois at Urbana-Champaign, lilisu3@illinois.edu

We focus on the impact of the adversarial agents on the performance of consensus-based non-Bayesian learning. We propose an update rule wherein each agent updates its local beliefs as (up to normalization) the product of (1) the likelihood of the cumulative private signals and (2) the weighted geometric average of the beliefs of its incoming neighbors and itself (using Byzantine consensus). Under mild assumptions on the underlying network structure and the global identifiability of the network, we show that all the non-faulty agents asymptotically agree on the true state almost surely.

MC40 207B-MCC Target Setting in Efficiency Analysis Invited: Data Envelopment Analysis Invited Session

Chair: Dong Joon Lim, Portland State University, Engineering & Technology Management - Engineering & Computer Science, Maseeh College of (ETM), Portland, OR, 97207, United States, dongjoon@pdx.edu 1 - Study Of Capital Requirement And Bank Operating Efficiency Yang Li, National University of Kaohsiung, Kaohsiung, Taiwan, yangli@nuk.edu.tw Following the 2008 financial tsunami, the Bank of International Settlements proposed Basel III in 2010, in which banks need to raise their capital adequacy ratio in order to make them sound and safe. This study employs the two-stage bootstrapped truncated regression model, proposed by Simar and Wilson (2007), and takes into account undesirable outputs to investigate how the increases in core, tier I, and total capital adequacy ratios influence the efficiency of Chinese commercial banks. The data set is obtained from Bankscope for the period 2012- 2014. Empirical results are consistent with the schedule and intention set by Basel III. 2 - Inverse DEA With Frontier Changes For New Product Target Setting Timothy Anderson, Portland State University, Portland, OR, 97201, United States, tim.anderson@pdx.edu, Dong-Joon Lim Inverse DEA can serve as a useful planning tool by providing information such as how much resources should be invested to achieve a desired level of efficiency. Inverse DEA studies however are based on an assumption that the PPS will not change within the period of interest, which in fact confines the use of inverse DEA to a sensitivity analysis by simply addressing what alternative levels of input/output would have been possible to result in the same efficiency score obtained. In this study, we discuss an inverse DEA problem considering expected changes of the production frontier in the future so that it can be an ex-ante decision support tool for the new product target setting practices. 3 - Evaluating Banker Et Al (2007) Allocative Efficiency Method Paul Rouse, University of Auckland, p.rouse@auckland.ac.nz When price information is unavailable, Banker, Chang, & Natarajan (2007) proposed a method to estimate technical and allocative inefficiency using aggregate cost or revenue data. This research replicates their analysis using the same data but supplemented by simulated data. The results show that when using individual firm prices, the Banker et al. (2007) method produces upwardly biased inefficiency measures and appears to misclassify some allocative inefficiency as technical inefficiency. The method does work, however, if uniform prices are known but in that situation, the quantities can then be derived and allocative efficiency calculated in the usual fashion. 4 - Measuring The Efficiency Of Suffolk County School Districts Diana Hagedorn, Stony Brook University,

14 Orleans Court, Commack, NY, 11725, United States, diana.hagedorn@stonybrook.edu, Herbert F. Lewis, Thomas R Sexton

In this paper, we use an input oriented DEA model to evaluate the performance of 69 school districts in Suffolk County, New York. We then consider merging adjacent school districts to potentially improve efficiency due to economies of scale.

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