Robust and accurate Monte Carlo simulation of (cross-) Gammas for Bermudan swaptions in the LIBOR market model

2014 ◽  
Vol 17 (3) ◽  
pp. 87-110 ◽  
Author(s):  
Ralf Korn ◽  
Qian Liang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Market Model ◽  
Libor Market Model ◽  
Bermudan Swaptions

scholarly journals Fast and accurate exercise policies for Bermudan swaptions in the LIBOR market model

2016 ◽  
Vol 03 (01) ◽  
pp. 1650005 ◽  
Author(s):  
Patrik Karlsson ◽  
Shashi Jain ◽  
Cornelis W. Oosterlee
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Monte Carlo Simulations ◽  
Upper Bound ◽  
Market Model ◽  
Monte Carlo Approach ◽  
Lower Upper ◽  
Libor Market Model ◽  
Bermudan Swaptions

This paper describes an American Monte Carlo approach for obtaining fast and accurate exercise policies for pricing of callable LIBOR Exotics (e.g., Bermudan swaptions) in the LIBOR market model using the Stochastic Grid Bundling Method (SGBM). SGBM is a bundling and regression based Monte Carlo method where the continuation value is projected onto a space where the distribution is known. We also demonstrate an algorithm to obtain accurate and tight lower–upper bound values without the need for nested Monte Carlo simulations.

MONTE CARLO SIMULATION OF VOLATILITY CLUSTERING IN MARKET MODEL WITH HERDING

1999 ◽  
Vol 02 (01) ◽  
pp. 83-94 ◽  
Author(s):  
DIETRICH STAUFFER ◽  
PAULO M. C. DE OLIVEIRA ◽  
AMERICO T. BERNARDES
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Root Mean Square ◽  
Cluster Size ◽  
Market Model ◽  
Mean Square ◽  
Trading Activity ◽  
Volatility Clustering

Through slow changes in the position of the traders, we introduce correlations between the volatility (root mean square change) of the prices at different times. We find this volatility correlation to decay slowly with time, as also observed in reality, and quite independent of the dimensionality of the lattice. We also make the trading activity of a cluster of traders proportional to the cluster size.

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