This paper presents a new methodology to approximate the value of
American options by least-squares Monte Carlo simulation. Whereas Longsta® and
Schwartz`s approach do not utilize the underlying asset price movement, we develop
several methods that incorporates it into option pricing. One category improves the
R-squares from the regressions by using, [1] the weighted regression with the same re-
gressors and, [2] new regressors which are related to the discount factor from the cur-
rent decision to exercise time. The other category improves the computational speed
without sacri¯cing the convergence level by, [1] terminating early during the backwar-
dation procedure and, [2] decreasing the number of observations for the regressors.
Finally, combining both methods, we can get improved R-squares and computational
speed in comparison to Longsta® and Schwartz`s approach.
JEL classi¯cation: G10; G13
Keywords: least-squares Monte Carlo simulation; American put options; Hedge Pa-
rameters
