Although typically overlooked, many purchase datasets exhibit a high incidence of products with zero sales. We propose a new estimator for the Random-Coefficients Logit demand system for purchase datasets with zero-valued market shares. The identification of the demand parameters is based on a...

In this paper we propose a new IV estimator to be used in detecting vertical property tax inequity. We conduct Monte Carlo experiments to evaluate the bias of this estimator in comparison to traditional linear and log-linear regression based estimators. We find that the new estimator is more...

We present a theory of homogeneous volatility bridge estimators for log-price stochastic processes. The main tool of our theory is the parsimonious encoding of the information contained in the open, high and low prices of incomplete bridge, corresponding to given log-price stochastic process,...

In this paper we tackle one of the problems that arises in the broad area of credit risk management. We seek a scenario consistent way of modeling the future credit exposure of complex products that do not admit an analytical (closed-form) solution. We present a technique for calculating future...

This paper demonstrates the sensitivity of the linear programming approach in the estimation of productivity measures in the primal framework. Specifically, the sensitivity to the number of constraints (level of dis-aggregation) and imposition of returns to scale constraints is evaluated....

We discuss efficiency of the quadratic bridge volatility estimator in comparison with Parkinson, Garman-Klass and Roger-Satchell estimators. It is shown in particular that point and interval estimations of volatility, resting on bridge estimator, are considerably more efficient than analogous...

Assume asset returns follow a VARMA_MARCH structure, this paper derives the proper multi-horizon mean and covariance matrix estimations that can be used as inputs to mean-variance optimization problem for investors with different horizons. The result is further extended to vector...

The aim of this study is to present an efficient and easy framework for the application of the Least Squares Monte Carlo methodology to the pricing of gas or power facilities as detailed in Boogert and de Jong. As mentioned in the seminal paper by Longstaff and Schwartz, the convergence of the...

Demonstration that our noise filtering procedure is extremely robust on the basis of the following experiment. The noise filtering procedure was applied first to an empirical correlation matrix and, second, to the matrix built from the same time series deliberately contaminated with noise. The...

Demonstration that our noise filtering procedure is extremely robust on the basis of the following experiment. The noise filtering procedure was applied first to an empirical correlation matrix and, second, to the same matrix deliberately contaminated with noise. The final, noise filtered...