Bootstrapping the Early Exercise Boundary in the Least-Squares Monte Carlo Method
نویسندگان
چکیده
منابع مشابه
Decision Making Under Uncertainty: Applying the Least-Squares Monte Carlo Method in Surfactant-Flooding Implementation
This study introduces a decision-making evaluation method for flexibility in surfactant flooding. The method aims to capture the effects of uncertainty in the time series for both technical and economic parameters and produce a near-optimal policy with respect to these uncertainties as they vary with time. The evaluation method used was the least-squares Monte Carlo (LSM) method, which is best-...
متن کاملrlsm: R package for least squares Monte Carlo
This short paper briefly describes the implementation of the least squares Monte Carlo method in the rlsm package. This package provides users with an easy manner to experiment with the large amount of R regression tools on any regression basis and reward functions. This package also computes lower and upper bounds for the true value function via duality methods.
متن کاملLeast Squares Monte Carlo Approach to Convex Control Problems
Optimal control problems with convex functions are ubiquitous in applications of stochastic optimization. However, when applied in this context, the classical least squares Monte Carlo methodology makes no attempt to take advantage of this special structure: Given the convexity of value functions, it seems reasonable to search for the best least-squares fit among the elements of a cone of conve...
متن کاملPricing Bounds for VIX Derivatives via Least Squares Monte Carlo
Derivatives on the Chicago Board Options Exchange volatility index (VIX) have gained significant popularity over the last decade. The pricing of VIX derivatives involves evaluating the square root of the expected realised variance which cannot be computed by direct Monte Carlo methods. Least squares Monte Carlo methods can be used but the sign of the error is difficult to determine. In this pap...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2019
ISSN: 1556-5068
DOI: 10.2139/ssrn.3503049