
Brief
bio and directory entry 
Last updated April 2014. 
Contingent Capital, Tail Risk, and DebtInduced Collapse
N. Chen, P. Glasserman, B. Nouri, and M. Pelger, working paper.
How Likely is Contagion in Financial Networks?
P. Glasserman and H. P. Young, forthcoming in the Journal of Banking and Finance.
Design of Risk Weights
P. Glasserman and W. Kang, working paper.
Stress Scenario Selection by Empirical Likelihood
P. Glasserman, C. Kang, and W. Kang, Quantitative Finance, to appear.
Robust Portfolio Control with Stochastic Factor Dynamics
P. Glasserman and X. Xu, Operations Research, 120, 2013.
Robust Risk Measurement and Model Risk
P. Glasserman and X. Xu, Quantitative Finance, to appear.
MarketTriggered Contingent Capital: Equilibrium Price Dynamics
P. Glasserman and B. Nouri, working paper.
Contingent
Capital with a CapitalRatio Trigger
P. Glasserman and B. Nouri, Management Science 2012 (with typos
corrected).
Forward
and Future Implied Volatility
P. Glasserman and Q. Wu, IJTAF vol. 14, 407432, 2011.
Valuing
the Treasury's Capital Assistance Program
P. Glasserman and Z. Wang, Management Science vol. 57, 11951211,
2011.
Risk
Horizon and Rebalancing Horizon in Portfolio Risk Measurement
P. Glasserman, Mathematical Finance vol
22, 215249, 2012.
Gamma
Expansion of the Heston Stochastic Volatility Model
P. Glasserman and K. Kim, Finance and
Stochastics 130, 2009.
Sensitivity
Estimates for Portfolio Credit Derivatives Using Monte Carlo
Z. Chen and P. Glasserman, Finance
and Stochastics vol 12, 507540, 2008.
Moment
Explosions and Stationary Distributions in Affine Diffusion Models
P. Glasserman and K. Kim, Mathematical
Finance vol 20, 133, 2010.
Saddlepoint
Approximations for Affine JumpDiffusion Models
P. Glasserman and K. Kim, Journal of
Economic Dynamics and Control, vol 33, 3752, 2009.
Beta
Approximations for Bridge Sampling
P. Glasserman and K. Kim, Proceedings
of the Winter Simulation Conference, 569577, 2008.
Sensitivity
Estimates from Characteristic Functions
P. Glasserman and Z. Liu, Operations Research, vol. 58, 16111623, 2010.
Estimating
Greeks in Simulating LevyDriven Models
P. Glasserman and Z. Liu, Journal of Computational Finance, vol. 14, 356, 2010/2011.
Malliavin
Greeks without Malliavin Calculus
N. Chen and P. Glasserman, Stochastic
Processes and Their Applications, vol. 117, 16891723, 2007.
Correlation
Expansions for CDO Pricing
P. Glasserman and S.
Suchintabandid, Journal of Banking and
Finance, vol. 31, 13751398, 2007.
Fast
Pricing of Basket Default Swaps
Z. Chen and P. Glasserman, Operations
Research, vol. 56, 286303, 2008.
Uniformly
Efficient Importance Sampling for the Tail Distribution of Sums of Random
Variables
P. Glasserman and S. Juneja, Mathematics of Operations Research, vol.
33, 3650, 2008.
Additive
and Multiplicative Duals for American Option Pricing
N. Chen and P. Glasserman, Finance
and Stochastics, 11, 153179, 2007.
Large
Deviations of Multifactor Portfolio Credit Risk
P. Glasserman, W. Kang, and P. Shahabuddin, Mathematical Finance, vol. 17, 345379, 2007.
Fast
Simulation of Multifactor Portfolio Credit Risk
P. Glasserman, W. Kang, and P. Shahabuddin, Operations Research, to appear.
Perwez
Shahabuddin, 19622005: A Professional
Appreciation
S. Androdottir, P. Glasserman, P.W. Glynn, P. Heidelberger and
A
Conversation with Chris Heyde
P. Glasserman and S. G. Kou, Statistical Science, vol. 21, 286298,
2006.
Smoking
Adjoints: Fast Monte Carlo Greeks
M. Giles and P. Glasserman, Risk, vol. 19, 8892, 2006.
Importance
Sampling for Portfolio Credit Risk
P. Glasserman and Jingyi Li, Management Science, vol 51,
16431656, 2005.
Measuring
Marginal Risk Contributions in Credit Portfolios
P. Glasserman, Journal of Computational Finance, vol. 9, 141,
2005.
Tail
Approximations for Portfolio Credit Risk
P. Glasserman, Journal of Derivatives, 2442,Winter 2004.
Number of Paths Versus Number of Basis Functions in American Option Pricing
P. Glasserman and Bin Yu, Annals of Applied Probability, vol. 14,
no. 4, 20902119, 2004.
Pricing American Options by Simulation: Regression Now or Regression
Later?
P.Glasserman and Bin Yu,
(H. Niederreiter, ed.), Springer,
Importance
Sampling for a Mixed Poisson Model of Portfolio Credit Risk
P. Glasserman and Jingyi Li, Proceedings of the Winter Simulation
Conference 2003
Large Sample Properties of Weighted Monte Carlo Estimators
P. Glasserman and Bin Yu, Operations Research, vol. 53, 298312, 2005.
Cap
and Swaption Approximations in LIBOR Market Models with Jumps
P. Glasserman and N. Merener, Journal of Computational Finance, vol 7,
136, 2003.
The
Term Structure of Simple Forward Rates with Jump Risk
P. Glasserman and S.G. Kou, Mathematical Finance, July 2003,383410.
Numerical
Solution of JumpDiffusion LIBOR Market Models
P. Glasserman and N. Merener, Finance and Stochastics 7, 127, 2003.
Addendum
Convergence
of a Discretization Scheme for JumpDiffusion Processes
with StateDependent Intensities
P. Glasserman and N. Merener, Proceedings of the Royal Society of
London, Series A, vol. 460, 117, 2003.
Portfolio
ValueatRisk with HeavyTailed Risk Factors
P. Glasserman, P. Heidelberger, and P. Shahabuddin, Mathematical Finance,
vol. 12, 239270, 2002.
Variance
Reduction Techniques for Estimating ValueatRisk
P. Glasserman, P. Heidelberger, and P. Shahabuddin, Management Science,
vol. 46, 13491364, 2000.
Efficient
Monte Carlo Methods for ValueatRisk
P. Glasserman, P. Heidelberger, and P. Shahabuddin, in Mastering Risk: Vol
2, Financial TimesPrentice Hall, 2001.
Importance
Sampling and Stratification for ValueatRisk
P. Glasserman, P. Heidelberger, and P. Shahabuddin, in Computational Finance
1999, AbuMostafa, Le Baron, Lo, and Weigend, eds., MIT Press, 2000.
Stratification
Issues in Estimating ValueatRisk
P. Glasserman, P. Heidelberger, and P. Shahabuddin, Proceedings of the
Winter Simulation Conference, 351359, 1999.
Equilibrium
Positive Interest Rates: A Unified View
Y. Jin and P. Glasserman, Review of Financial Studies, 14:187214
(2001).
Importance
Sampling in the HeathJarrowMorton Framework
P. Glasserman, P. Heidelberger, and P. Shahabuddin, Journal of Derivatives, 7(1):3250,
1999.
Asymptotically
Optimal Importance Sampling and Stratification for Pricing PathDependent
Options,
P. Glasserman, P. Heidelberger, and P. Shahabuddin, Mathematical Finance, 9:117152,
1999.
ArbitrageFree
Discretization of Lognormal Forward Libor and Swap Rate Models,
P. Glasserman and X. Zhao, Finance and Stochastics 4:3568 2000.
Discretization
of Deflated Bond Prices
P. Glasserman and H. Wang, Advances in Applied Probability, 32:540563,
2001.
Fast
Greeks by Simulation in Forward Libor Models
P. Glasserman and X. Zhao, Journal of Computational Finance, 3:539,
1999.
Source
code for numerical examples
Comparing Stochastic
Discount Factors Through Their Implied Measures
P. Glasserman and Y. Jin
Conditioning
on OneStep Survival in Barrier Option Simulations
P. Glasserman and J. Staum, Operations Research, 49:923937, 2001.
Resource
Allocation Among Simulation Time Steps
P. Glasserman and J. Staum, Operations Research, vol. 51, 908921,
2003.
Stopping
Simulated Paths Early
P. Glasserman and J. Staum, Proceedings of the Winter Simulation
Conference, 318325, 2001.
A
Stochastic Mesh Method for Pricing HighDimensional American Options
M. Broadie and P. Glasserman, Journal of Computational Finance, vol.
7, 3572, 2004.
Pricing
American Options by Simulation Using a Stochastic Mesh with Optimized Weights
M. Broadie, P. Glasserman, and Z. Ha, in Probabilistic Constrained
Optimization, S.P. Uryasev, ed., 3250, 2000.
A
Continuity Correction for Discrete Barrier Options
M. Broadie, P. Glasserman, S.G. Kou, Mathematical Finance 7:325348,
1997.
Connecting
Discrete and Continuous PathDependent Options
M. Broadie, P. Glasserman, S.G. Kou, Finance and Stochastics 3:5582,
1999.