COLUMBIA |
Brief bio
and directory entry |
Last updated October 2023 |
Time
Variation in the News-Returns Relationship,
P. Glasserman, F. Li, and H. Mamaysky, JFQA, to
appear.
Should Bank Stress Tests Be Fair?
P. Glasserman and M. Li, Management Science, to appear
Linear
Classifiers Under Infinite Imbalance
P. Glasserman and M. Li, working paper
Swing Pricing: Theory and Evidence,
A. Capponi, P. Glasserman, and M. Weber, Annual Review
of Financial Economics, to appear.
W-Shaped Implied
Volatility Curves and the Gaussian Mixture Model
P. Glasserman and D. Pirjol, Quantitative Finance 23(4), 557-577, 2023.
Total Positivity and Relative Convexity of Option Prices,
P. Glasserman and D. Pirjol, Frontiers of Mathematical
Finance 2(1), 1-32, 2023.
New News
is Bad News, working paper
P. Glasserman, H. Mamaysky, and J. Qin
Assessing Look-Ahead Bias in Stock Return Predictions Generated By GPT Sentiment Analysis,
P. Glasserman and C. Lin, working paper
Dynamic
Information Regimes in Financial Markets
P. Glasserman, H. Mamaysky, and Y. Shen, Management Science, to appear.
Combined Derivative Estimators,
P. Glasserman, Advances in Modeling and Simulation, Festschrift
for Pierre L'Ecuyer, 2022.
Tail Risk Monotonicity Under Temporal Aggregation in GARCH(1,1) Models,
P. Glasserman, D. Pirjol, and Q. Wu, working paper
Investor Information Choice
with Macro and Micro Information
P. Glasserman and H. Mamaysky, Review of Asset Pricing Studies, 13(1),
1-52, 2023. Internet Appendix.
Maximum
Entropy Distributions with Applications to Graph Simulation
P. Glasserman and E. Lelo de Larrea, Operations Research 71(5), 1908-1924, 2023.
Choosing
News Topics to Explain Stock Market Returns
P. Glasserman, K. Krstovski, P. Laliberte, and H. Mamaysky, Proceedings of
the ACM International Conference on AI in Finance, 2020.
Collateralized
Networks
S. Ghamami, P. Glasserman, and H.P. Young, Management Science 68(3),
2202-2225, 2022.
Buy
Rough, Sell Smooth
P. Glasserman and P. He, Quantitative Finance, vol. 20(3), 363-378,
2020.
Swing
Pricing for Mutual Funds: Breaking the Feedback Loop Between Fire Sales and
Fund Runs,
A. Capponi, P. Glasserman, and M. Weber, Management Science, vol. 66(8),
3295-3798, 2020.
Does
Unusual News Forecast Market Stress?
H. Mamaysky and P. Glasserman, JFQA, vol. 54(5), 1937-1974, 2019.
Bounding
Wrong-Way Risk in CVA Calculation
P. Glasserman and L. Yang, Mathematical Finance, vol. 28, 268-305,
2018.
Contingent
Capital, Tail Risk, and Debt-Induced Collapse
N. Chen, P. Glasserman, B. Nouri, and M. Pelger, Review of Financial
Studies, vol. 30, 3711-3758, 2017.
Does
OTC Derivatives Reform Incentivize Central Clearing?
S. Ghamami and P. Glasserman, OFR working paper, Journal of Financial
Intermediation, vol. 32, 76-87, 2017.
Market-Triggered
Changes in Capital Structure: Equilibrium Price Dynamics
P. Glasserman and B. Nouri, Econometrica, vol. 84, 2113-2153, 2016.
Submodular
Risk Allocation
S. Ghamami and P. Glasserman, Management Science, vol. 65(1),
4656-4675, 2019.
Contagion in
Financial Networks
P. Glasserman and H. P. Young, Journal of Economic Literature, vol.
54, 779-831, 2016.
The
Market-Implied Probability of European Government Intervention in Distressed
Banks
R. Neuberg, P. Glasserman, B. S. Kay and S. Rajan, OFR working paper.
Persistence
and Procyclicality in Margin Requirements
P. Glasserman and Q. Wu, Management Science, vol. 64(12), 5461-5959,
2018.
Hidden
Illiquidity with Multiple Central Counterparties
P. Glasserman, C. C. Moallemi, and K. Yuan, OFR working paper, Operations
Research, vol. 64, 1143-1158, 2016.
How Likely is Contagion in Financial Networks?
P. Glasserman and H. P. Young, Journal of Banking and Finance, vol.
50, 383-399, 2015.
Stress Scenario Selection by Empirical
Likelihood
P. Glasserman, C. Kang, and W. Kang, Quantitative Finance, vol. 15,
25-41, 2015.
Design of Risk Weights
P. Glasserman and W. Kang, Operations Research, vol. 62, 2014.
Robust
Risk Measurement and Model Risk
P. Glasserman and X. Xu, Quantitative Finance, vol. 14, 29-58, 2014.
Robust Portfolio Control with
Stochastic Factor Dynamics
P. Glasserman and X. Xu, Operations Research, 1-20, 2013.
Contingent Capital with a
Capital-Ratio Trigger
P. Glasserman and B. Nouri, Management Science 2012 (with typos
corrected).
Quadratic Transform Approximation for CDO
Pricing in Multifactor Models
P. Glasserman and S. Suchintabandid, SIAM Journal on Financial Mathematics,
vol. 3, 137-162, 2012.
Forward and Future Implied
Volatility
P. Glasserman and Q. Wu, IJTAF vol. 14, 407-432, 2011.
Valuing the Treasury's
Capital Assistance Program
P. Glasserman and Z. Wang, Management Science
vol. 57, 1195-1211, 2011.
Risk Horizon and Rebalancing Horizon
in Portfolio Risk Measurement
P. Glasserman, Mathematical Finance vol 22, 215-249, 2012.
Gamma Expansion of the Heston
Stochastic Volatility Model
P. Glasserman and K. Kim, Finance and Stochastics 1-30, 2009.
Sensitivity Estimates for Portfolio
Credit Derivatives Using Monte Carlo
Z. Chen and P. Glasserman, Finance and Stochastics vol 12, 507-540,
2008.
Moment Explosions and Stationary
Distributions in Affine Diffusion Models
P. Glasserman and K. Kim, Mathematical Finance vol 20, 1-33, 2010.
Saddlepoint Approximations for Affine Jump-Diffusion
Models
P. Glasserman and K. Kim, Journal of Economic Dynamics and Control, vol
33, 37-52, 2009.
Beta Approximations for Bridge Sampling
P. Glasserman and K. Kim, Proceedings of the Winter Simulation
Conference, 569-577, 2008.
Sensitivity Estimates from
Characteristic Functions
P. Glasserman and Z. Liu, Operations Research, vol. 58, 1611-1623,
2010.
Estimating Greeks in Simulating
Levy-Driven Models
P. Glasserman and Z. Liu, Journal of Computational Finance, vol.
14, 3-56, 2010/2011.
Malliavin Greeks without Malliavin Calculus
N. Chen and P. Glasserman, Stochastic Processes and Their Applications,
vol. 117, 1689-1723, 2007.
Correlation Expansions for CDO Pricing
P. Glasserman and S.
Suchintabandid, Journal of Banking and Finance, vol. 31, 1375-1398,
2007.
Fast Pricing of Basket Default Swaps
Z. Chen and P. Glasserman, Operations Research, vol. 56, 286-303,
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, 36-50, 2008.
Fast Simulation of Multifactor Portfolio Credit Risk
P. Glasserman, W. Kang, and P. Shahabuddin, Operations Research,
vol. 56, 1200-1217, 2008.
Additive and Multiplicative Duals for American
Option Pricing
N. Chen and P. Glasserman, Finance and Stochastics, 11, 153-179,
2007.
Large Deviations of Multifactor Portfolio Credit Risk
P. Glasserman, W. Kang, and P. Shahabuddin, Mathematical Finance, vol.
17, 345-379, 2007.
Perwez Shahabuddin, 1962-2005: 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, 286-298, 2006.
Smoking Adjoints: Fast Monte Carlo Greeks
M. Giles and P. Glasserman, Risk, vol. 19, 88-92, 2006.
Importance Sampling for Portfolio Credit Risk
P. Glasserman and Jingyi Li, Management Science, vol 51,
1643-1656, 2005.
Measuring Marginal Risk Contributions in Credit
Portfolios
P. Glasserman, Journal of Computational Finance, vol. 9, 1-41,
2005.
Tail Approximations for Portfolio Credit Risk
P. Glasserman, Journal of Derivatives, 24-42,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, 2090-2119, 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, 298-312, 2005.
Cap and Swaption Approximations in LIBOR Market Models
with Jumps
P. Glasserman and N. Merener, Journal of Computational Finance, vol 7,
1-36, 2003.
The Term Structure of Simple Forward Rates with Jump Risk
P. Glasserman and S.G. Kou, Mathematical Finance, July 2003,383-410.
Numerical Solution of Jump-Diffusion LIBOR Market
Models
P. Glasserman and N. Merener, Finance and Stochastics 7, 1-27, 2003.
Addendum
Convergence of a Discretization Scheme for
Jump-Diffusion Processes
with State-Dependent Intensities
P. Glasserman and N. Merener, Proceedings of the Royal Society of
London, Series A, vol. 460, 1--17, 2003.
Portfolio Value-at-Risk with Heavy-Tailed Risk
Factors
P. Glasserman, P. Heidelberger, and P. Shahabuddin, Mathematical Finance,
vol. 12, 239-270, 2002.
Variance Reduction Techniques for Estimating Value-at-Risk
P. Glasserman, P. Heidelberger, and P. Shahabuddin, Management Science,
vol. 46, 1349-1364, 2000.
Efficient Monte Carlo Methods for Value-at-Risk
P. Glasserman, P. Heidelberger, and P. Shahabuddin, in Mastering Risk: Vol
2, Financial Times-Prentice Hall, 2001.
Importance Sampling and Stratification for Value-at-Risk
P. Glasserman, P. Heidelberger, and P. Shahabuddin, in Computational Finance
1999, Abu-Mostafa, Le Baron, Lo, and Weigend, eds., MIT Press, 2000.
Stratification Issues in Estimating Value-at-Risk
P. Glasserman, P. Heidelberger, and P. Shahabuddin, Proceedings of the
Winter Simulation Conference, 351-359, 1999.
Equilibrium Positive Interest Rates: A
Unified View
Y. Jin and P. Glasserman, Review of Financial Studies, 14:187-214
(2001).
Importance Sampling in the Heath-Jarrow-Morton
Framework
P. Glasserman, P. Heidelberger, and P. Shahabuddin, Journal of Derivatives, 7(1):32-50,
1999.
Asymptotically Optimal Importance Sampling and Stratification
for Pricing Path-Dependent Options,
P. Glasserman, P. Heidelberger, and P. Shahabuddin, Mathematical Finance, 9:117-152,
1999.
Arbitrage-Free Discretization of Lognormal Forward Libor
and Swap Rate Models,
P. Glasserman and X. Zhao, Finance and Stochastics 4:35-68 2000.
Discretization of Deflated Bond Prices
P. Glasserman and H. Wang, Advances in Applied Probability, 32:540-563,
2001.
Fast Greeks by Simulation in Forward Libor Models
P. Glasserman and X. Zhao, Journal of Computational Finance, 3:5-39,
1999.
Source code for numerical examples
Comparing Stochastic
Discount Factors Through Their Implied Measures
P. Glasserman and Y. Jin
Conditioning on One-Step Survival in Barrier Option
Simulations
P. Glasserman and J. Staum, Operations Research, 49:923-937, 2001.
Resource Allocation Among Simulation Time Steps
P. Glasserman and J. Staum, Operations Research, vol. 51, 908-921,
2003.
Stopping Simulated Paths Early
P. Glasserman and J. Staum, Proceedings of the Winter Simulation
Conference, 318-325, 2001.
A Stochastic Mesh Method for Pricing High-Dimensional
American Options
M. Broadie and P. Glasserman, Journal of Computational Finance, vol.
7, 35-72, 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., 32-50, 2000.
A Continuity Correction for Discrete Barrier Options
M. Broadie, P. Glasserman, S.G. Kou, Mathematical Finance 7:325-348,
1997.
Connecting Discrete and Continuous Path-Dependent
Options
M. Broadie, P. Glasserman, S.G. Kou, Finance and Stochastics 3:55-82,
1999.