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INFORMS Nashville – 2016
347
TD39
207A-MCC
Applied Probability and Optimization III
Sponsored: Applied Probability
Sponsored Session
Chair: Chaitanya Bandi,
c-bandi@kellogg.northwestern.edu1 - Adaptive Control Of Flexible Queueing Networks
Yuan Zhong, Columbia University, New York, NY, 10027, United
States,
yz2561@columbia.edu,Ramtin Pedarsani, Jean Walrand
We consider the problem of designing adaptive control policies for queueing
networks with flexible servers of overlapping capabilities. We show that a simple,
adaptive version of the classical maxweight policy can lead to system instability.
We then provide tight characterizations for systems that are stable under the
simple, adaptive maxweight policy. Finally, we propose class of adaptive control
policies that are throughput optimal for general parallel server systems.
2 - Delay Performance Of Scheduling Algorithms For Data Center
Networks And Input Queued Switches
Sivateja Maguluri, IBM,
siva.theja@gmail.comToday’s era of cloud computing is powered by massive data centers hosting
servers that are connected by high speed networks. It is therefore desirable to
design scheduling algorithms for data packets that have low computational
complexity and result in small average packet delays. We consider the scheduling
problem in an input-queued switch, which is a good abstraction for a data center
network. We present low complexity scheduling algorithms that have optimal
queue length (equivalently, delay) behavior in the heavy traffic regime. We also
present bounds on the queue length in light traffic. These results are obtained
using drift based arguments.
3 - Characterizing Global Stability Of Queueing Networks Via Robust
Optimization
Chaithanya Bandi, Northwestern University, Evanston, IL, United
States,
c-bandi@kellogg.northwestern.edu,Itai Gurvich
We study the conditions of global stability in open multi-class queueing networks,
that is stability under any work conserving policy. We propose a new approach,
where rather than aiming at the full characterization of global stability, we seek
toidentify assembly (LEGO) operations, such as pooling of networks, and
assembly rules-of-thumb that, when followed, crate a globally stable network
from globally stable building blocks. We also use robust optimization as a key
methodology that brings a new perspective to known results on global stability,
state space collapse and the network Skorohod problem.
4 - Using Robust Queueing To Expose The Impact Of Dependence In
Single Server Queues
Wei You, PhD Student, Columbia University, 500 W. 120th St.,
Mudd 323, New York, NY, 10027, United States,
wy2225@columbia.edu,Ward Whitt
Queueing applications often exhibit dependence among interarrival times and
service times, e.g., when there are multiple customer classes with class-dependent
service-time distributions, or when arrivals are departures or overflows from
other queues or superpositions of such complicated processes. In this talk, we
show that the robust queueing approach proposed by Bandi et al. can be
extended to describe the impact of dependence structure on customer waiting
times and the remaining workload in service time as a function of the traffic
intensity. Thus, robust queueing can be useful to develop performance
approximations for queueing networks and other complex queueing systems.
TD40
207B-MCC
Applications in Applied Probability
Sponsored: Applied Probability
Sponsored Session
Chair: Kevin Leder, University of Minnesota, 111 Church St,
Minneapolis, MN, 55455, United States,
kevinleder@gmail.com1 - A Stochastic Model Of Order Book Dynamics Using Bouncing
Geometric Brownian Motions
Xin Liu, Clemson University,
xliu9@clemson.eduIn a limit order book, market ask price is always greater than market bid price,
and these prices move upwards and downwards due to new arrivals, market
trades, and cancellations. We model the two price processes as “bouncing
geometric Brownian motions (GBMs)”, which are defined as exponentials of two
mutually reflected Brownian motions (BM). We then modify these bouncing
GBMs to construct a discrete time stochastic process of trading times and trading
prices, which is parameterized by a parameter c > 0. It is shown that the
logarithmic trading price process, under a suitable scaling, converges to a standard
BM, and the modified ask and bid price processes approach the original bouncing
GBMs, as c goes to 0.
2 - Synchronization Of Discrete Pulse-coupled Oscillators
David Sivakoff, Ohio State University,
dsivakoff@stat.osu.eduWe introduce a discrete state, discrete time model of inhibitory oscillators, and
analyze the long time behavior of a system of oscillators located on the integer
lattice. We show that, when started from random initial condition, the system
clusters (weakly synchronizes), and give upper and lower bounds on the
clustering rate.
3 - Sample Path Large Deviations For Heavy Tailed Levy Processes
And Their Applications
Chang-Han Rhee, CWI,
C.Rhee@cwi.nlWhile the theory of large deviations has been wildly successful in providing
systematic tools for studying rare events, the central ideas behind the classical
large deviations theory critically hinge on the assumption that the underlying
uncertainties are light-tailed. As a result, the heavy-tailed counterparts have
remained significantly less mature. In this talk, we introduce a new large
deviations result for heavy-tailed Levy processes, which enables systematic study
of the rare events associated with multiple big jumps, beyond the celebrated
“principle of one big jump.” We illustrate the implications of the new theory in
applications in computational finance and stochastic networks.
TD41
207C-MCC
Quantitative Methods in Finance
Sponsored: Financial Services
Sponsored Session
Chair: Qi Wu, Chinese University of Hong Kong, Hong Kong, Shatin,
NT, 12345, Hong Kong,
qwu@se.cuhk.edu.hk1 - Option Pricing In The Presence Of Market Microstructure
Nan Chen, Chinese University of Hong Kong,
nchen@se.cuhk.edu.hkNo-arbitrage prices of vanilla options becomes nontrivial when the underlying
dynamic is modeled at the order book level. By taking into account the market
microstructure such as market depth and resilience, we formulate the traditional
option pricing problem as a singular-impulsive control problem. Our analysis
demonstrates that the liquidity-related microstructure has a profound impact on
the resulting prices.
2 - On The Measurement Of Economic Tail Risk
Xianhua Peng, Hong Kong University of Science & Technology,
maxhpeng@ust.hk,Steven Kou
This paper attempts to provide a decision-theoretic foundation for the
measurement of economic tail risk, which is not only closely related to utility
theory but also relevant to statistical model uncertainty. The main result is that
the only risk measures that satisfy a set of economic axioms for the Choquet
expected utility and the statistical property of general elicitability (i.e. there exists
an objective function such that minimizing the expected objective function yields
the risk measure) are the mean functional and Value-at-Risk (VaR), in particular
the median shortfall, which is the median of tail loss distribution and is also the
VaR at a higher confidence level.
3 - Persistence And Procyclicality In Margin Requirements
Qi Wu, Chinese University of Hong Kong,
qwu@se.cuhk.edu.hkDerivatives central counterparties (CCP) impose margin requirements on their
clearing members to protect the CCP from the default of a member firm. A spike
in volatility leads to margin calls in times of market stress. Risk-sensitive margin
requirements are procyclical in the sense that they amplify shocks. We analyze
how much higher margin levels need to be to avoid procyclicality. Our analysis
compares the tail decay of conditional and unconditional loss distributions to
compare stable and risk-sensitive margin requirements. Greater persistence in
volatility leads to a slower decay in the tail of the unconditional distribution and a
higher bu er needed to avoid procyclicality.
4 - Over-the Counter Markets andCounterparty Risk
Agostino Capponi, Columbia University,
ac3827@columbia.eduWe develop a parsimonious model to study how counterparty risk influences the
structure of OTC markets. A unit continuum of traders, who are risk-averse
agents with exponential utility, are organized into banks. Traders of a bank
strategically engage in bilateral transactions with traders of another bank taking
into account the terms of deal and counterparty risk. We show that the rise of
counterparty risk leads to a higher concentration of dealers.
TD41