Here we develop methods for efficient pricing multidimensional discrete time American and Bermudan options by using regression based algorithms together with a new approach towards constructing upper bounds for the price of the option. Applying the sample space with payoffs at the optimal...

In this paper we develop several regression algorithms for solving general stochastic optimal control problems via Monte Carlo. This type of algorithms is particularly useful for problems with a highdimensional state space and complex dependence structure of the underlying Markov process with...

Telecommunications providers' market share risks stem from uncertainties due to overall market performance and competition strategies adopted by providers. In this paper, a framework that allows risk-adjusted forecasting of a provider's market share is presented. Two different stochastic...

The confidence interval is an important statistical estimator of population location and dispersion parameters. The paper considers a robust modified confidence interval, which is an adjustment of the Student's t confidence interval based on the decile mean and decile standard deviation for...

Monte Carlo (MC) simulations are one of the dominant approaches to compare statistical methods. To date, there is no standard procedure for MC simulations. Although internally valid, they exhibit a certain degree of arbitrariness through the various choices that researchers make. In this paper,...

This paper proposes a method to analyze interval-censored data, using multiple imputation based on a heteroskedastic interval regression approach. The proposed model aims to obtain a synthetic data set that can be used for standard analysis, including standard linear regression, quantile...

In the capital market and financing theory, we are currently observing major upheavals. For decades, the neoclassical paradigm has dominated in science and practice. Triggered by economic and political crises, transformations, the COVID-19 pandemic, and political instabilities, a paradigm shift...

We consider estimation and inference for a regression coefficient in panels with interactive fixed effects (i.e., with a factor structure). We show that previously developed estimators and confidence intervals (CIs) might be heavily biased and size-distorted when some of the factors are weak. We...

Control charts are widely used to monitor the quality of industrial processes. It is quite common to assume that the random variable associated to the quality characteristic has a Normal distribution, and the control limits are defined so that the probability of obtaining a false alarm is...