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We provide a general valuation approach for capital budgeting decisions involving the modularization of a system. Within the framework developed by Baldwin and Clark (2000), we implement an approach using a numerical procedure based on the Least Squares Monte Carlo method proposed by Longstaff...
Persistent link: https://www.econbiz.de/10003962024
Least squares Monte Carlo (LSM) is an approximate dynamic programming (ADP) technique commonly used for the valuation of high dimensional financial and real options, but has broader applicability. It is known that the regress-later version of this method is an approximate linear programming...
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This paper shows that the presence of conditional staging in R&D (Research & Development) has a critical impact on portfolio risk, and changes diversification arguments when a portfolio is constructed. When R&D projects exhibit option-like characteristics, correlation between projects plays a...
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In this paper we use Monte Carlo simulation to investigate the impact of effect size heterogeneity on the results of a meta-analysis. Specifically, we address the small sample behaviour of the OLS, the fixed effects regression and the mixed effects meta-estimators under three alternative...
Persistent link: https://www.econbiz.de/10011372995
Skewed data is the main issue in statistical models in healthcare costs. Data transformation is a conventional method to decrease skewness, but there are some disadvantages. Some recent studies have employed generalized linear models (GLMs) and Cox proportional hazard regression as alternative...
Persistent link: https://www.econbiz.de/10010528658
We investigate, if it pays off for a company to invest into complex swing option algorithms. We first introduce least squares Monte Carlo as a complex valuation algorithm and explain in detail how it works. Using a simulation study and two backtest scenarios we compare the output of this method...
Persistent link: https://www.econbiz.de/10011534754
In this paper, we propose a modification of the three-pass regression filter (3PRF) to make it applicable to large mixed frequency datasets with ragged edges in a forecasting context. The resulting method, labeled MF-3PRF, is very simple but compares well to alternative mixed frequency factor...
Persistent link: https://www.econbiz.de/10011541230