Explorando por Autor "Rengifo, Erick W."
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Ítem Acceso Abierto How Investors Face Financial Risk: Loss Aversion and Wealth Allocation(Pontificia Universidad Católica del Perú. CENTRUM, 2010) Rengifo, Erick W.; Trifan, EmanuelaWe studied how the capital allocation decisions and the loss version of nonprofessional investors change subject to behavioral factors. The optimal wealth allocation between risky and risk-free assets results within a value-at-risk (VaR) portfolio model, which involves assessing risk individually according to an extended prospect-theory framework. We showed how the past performance and the portfolio evaluation frequency affect investor behavior and prove myopic loss aversion holds across different evaluation frequencies. We also illustrated that 1 year is the optimal evaluation horizon at which, under practical constraints, maximization of risky holdings occurs. Finally, we presented evidence that indicates that researchers using standard VaR significance levels may be underestimating the loss aversion of individual investors.Ítem Acceso Abierto A Model to Improve the Estimation of Baseline Retail Sales(Pontificia Universidad Católica del Perú. CENTRUM, 2011) Jetta, Kurt; Rengifo, Erick W.This paper develops more accurate and robust baseline sales estimates (sales in the absence of price promotion) using a dynamic linear model (DLM) enhanced with a multiple structural change model (MSCM). We first discuss the value of utilizing aggregated (chain-level) vs. disaggregated (store-level) point-of-sale (POS) data to estimate baseline sales and to measure promotional effectiveness. We then present the practical advantage of the DLM-MSCM modeling approach using aggregated data, and we propose two tests to determine the superiority of a particular baseline estimate: the minimization of weekly sales volatility and the existence of no correlation with promotional activities in these estimates. Finally, we test this new baseline against the industry standard ones on the two measures of performance. Our tests find the DLM-MSCM baseline sales to be superior to the existing log-linear models by reducing the weekly baseline sales volatility by over 80% and by being uncorrelated to promotional activities.