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...

In this paper, we illustrate how to value American-style options using the Least-Squares Monte Carlo (LSM) approach proposed by Longstaff and Schwartz (2001) and investigate whether there exists an optimal regression complexity in the LSM framework for options pricing. In particular, we use the smoothing spline in the regression step, which allows us to control the regression complexity on a co...

The Ordinary Least Squares (OLS) method is the most popular technique in statistics and is often use to estimate the parameters of a model because of tradition and ease of computation. The OLS provides an efficient and unbiased estimates of the parameters when the underlying assumptions, especially the assumption of contant error variances (homoscedasticity), are satisfied. Nonetheless, in real...

Relations are derived that can be used to infer parameters in situations where theoretical predictions can be compared to experimental data only indirectly via Monte Carlo simulation. We consider least square and likelihood ratio fits. Parameter changes in the fitting procedures are performed by reweighting Monte Carlo events. Formulas for goodness-of-fit tests based on the w2 and the likelihoo...

The idea that Monte Carlo simulation can not be applied to the pricing of options (real or financial) with early exercise features has been overridden in the light of new research results in the last decade. This paper attempts to contribute to this revived interest on Monte Carlo simulation valuation, by applying the proposed least–squares simulation method to the valuation of a hypothetical n...

Hedonic methods are a prominent approach in the construction of house price indexes. This paper investigates in a comprehensive way whether or not there exists any kind of link between the type of price index to be computed (Dutot or Jevons) and the form of hedonic functions, hedonic methods and estimation methods, with a link being defined as a specific combination of price indexes, functions ...

Hedonic methods are a prominent approach in the construction of quality-adjusted price indexes. This paper shows that the process of computing such indexes is substantially simplified if arithmetic (geometric) price indexes are computed based on exponential (log-linear) hedonic functions estimated by the Poisson pseudo maximum likelihood (ordinary least squares) method. A Monte Carlo simulation...

Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. For variance-based structural equation modeling, such as partial least squares, the FornellLarcker criterion and the examination of cross-loadings are the dominant approaches for evaluating discriminant validity. By means of a simulation study, we show that these a...