2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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4 - Social Learning In The Presence Of Adversaries
Lili Su, University of Illinois at Urbana-Champaign,
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,
1 - Study Of Capital Requirement And Bank Operating Efficiency
Yang Li, National University of Kaohsiung, Kaohsiung, Taiwan,
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, 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,
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,
, 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.
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,
1 - Optimal Portfolio Deleveraging With Cross Asset Price Pressure
Jingnan Chen, Singapore University of Technology and Design,
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,
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,
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,
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 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,
1 - Optimal Pricing In Networks With Latent Agents
Ozan Candogan, Chicago Booth,
, 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.
MC40