看过“Monte carlo methods in financial engineering”的人就知道这个牛人了吧， Paul Glasserman，他主页上有巨多Paper，感兴趣的可以下来学习学习。
http://www2.gsb.columbia.edu/faculty/pglasserman/Other/
Downloadable Papers
Malliavin Greeks without Malliavin Calculus
N. Chen and P. Glasserman
Correlation Expansions for
CDO Pricing
P. Glasserman and S. Suchintabandid, Journal of Banking and Finance, to appear.
Fast Pricing of Basket Default Swaps
Z. Chen and P. Glasserman
Uniformly Efficient Importance Sampling for the Tail Distribution of Sums of Random Variables
P. Glasserman and S. Juneja, Mathematics of Operations Research, to appear.
Additive and Multiplicative Duals for American Option Pricing
N. Chen and P. Glasserman, Finance and Stochastics, to appear.
Large Deviations of Multifactor Portfolio Credit Risk
P. Glasserman, W. Kang, and P. Shahabuddin, Mathematical Finance, to appear.
Fast Simulation of Multifactor Portfolio Credit Risk
P. Glasserman, W. Kang, and P. Shahabuddin
Perwez Shahabuddin, 1962-2005: A Professional Appreciation
S. Androdottir, P. Glasserman, P.W. Glynn, P. Heidelberger and S. Juneja, ACM TOMACS, to appear.
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, Monte Carlo and Quasi-Monte Carlo Methods 2002,
(H. Niederreiter, ed.), Springer, Berlin.
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
