Search results for " forecasting"

FISCAL READJUSTMENTS IN THE UNITED STATES: A NONLINEAR TIME-SERIES ANALYSIS

2009

We analyze the fiscal adjustment process in the United States using a multivariate threshold vector error regression model. The shift from single-equation to multivariate setting adds value both in terms of our economic understanding of the fiscal adjustment process and the forecasting performance of nonlinear models. We find evidence that fiscal authorities intervene to reduce real per capita deficit only when it reaches a certain threshold and that fiscal adjustment takes place primarily by cutting government expenditure. The results of out-of-sample density forecast and probability forecasts suggest that a shift from a univariate autoregressive model to a multivariate model improves fore…

Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19.2 million …

2016

Copyright © NCD Risk Factor Collaboration. Open Access article distributed under the terms of CC BY.

Diagnostic accuracy of computed tomographic colonography for the detection of advanced neoplasia in individuals at increased risk of colorectal cance…

2009

CONTEXT: Computed tomographic (CT) colonography has been recognized as an alternative for colorectal cancer (CRC) screening in average-risk individuals, but less information is available on its performance in individuals at increased risk of CRC. OBJECTIVE: To assess the accuracy of CT colonography in detecting advanced colorectal neoplasia in asymptomatic individuals at increased risk of CRC using unblinded colonoscopy as the reference standard. DESIGN, SETTING, AND PARTICIPANTS: This was a multicenter, cross-sectional study. Individuals at increased risk of CRC due to either family history of advanced neoplasia in first-degree relatives, personal history of colorectal adenomas, or positiv…

Fusion of technology management and financing management - Amazon's transformative endeavor by orchestrating techno-financing systems

2020

Amazon became the world R&D leader in 2017 by rapidly increasing R&D investment. Its R&D investment in 2017 was double that of 2015, 5 times that of 2012, and 10 times that of 2011. This rapid increase continued in 2018, and Amazon accomplished a skyrocketing increase in its market capitalization, closing to being the world's biggest company. Such a rapid increase in R&D and subsequent market value has raised questions about how to conduct R&D and secure a large amount of funds needed for high-risk investments. Amazon has provided hypothetical answers to both of these questions. Amazon has been conducting innovative R&D to transform routine or periodic alterations into significant improveme…

Sensitivity of external resources to cash flow under financial constraints

2014

Abstract This paper explores the external financing–cash flow relationship in capital structure theory by comparing unlisted (financially constrained) and listed (financially unconstrained) companies. We postulate that investment is determined endogenously in the case of unlisted firms, as they are strongly dependent on internally generated funds (cash flow). Consequently, unlisted firms invest their cash flow in profitable projects, using any residual cash flow to increase their holdings of safe assets. In turn, listed companies determine their investment exogenously and may reduce leverage if they raise an excess of cash flow. As a result, listed companies would react more negatively to s…

Improving demand forecasting accuracy using nonlinear programming software

2006

We address the problem of forecasting real time series with a proportion of zero values and a great variability among the nonzero values. In order to calculate forecasts for a time series, the model coefficients must be estimated. The appropriate choice of values for the smoothing parameters in exponential smoothing methods relies on the minimization of the fitting errors of historical data. We adapt the generalized Holt–Winters formulation so that it can consider the starting values of the local components of level, trend and seasonality as decision variables of the nonlinear programming problem associated with this forecasting procedure. A spreadsheet model is used to solve the problems o…

Corrigendum to “Aggregation systems for sales forecasting” [J. Bus. Res. 68(11) (2015) 2299–2304]

2016

Aggregation systems for sales forecasting

2015

Abstract Sales forecasting consists of calculating the expected sales of a specific product or company. An important issue when dealing with sales forecasting is the calculation of the average sales, usually using the arithmetic mean or the weighted average. This study introduces new methods for calculating the average sales. These methods are two modern aggregation operators: the ordered weighted average, and the unified aggregation operator. The main advantage of this approach is the possibility to deal with uncertain and complex environments in a more complete way. The study develops some key examples through multi-person and multi-criteria techniques. The study also presents a numerical…

Forecasting the Equity Risk Premium in the European Monetary Union

2018

This article examines the performance of several variables that could be good predictors of the equity risk premium in the European Monetary Union for a period that spans from 2000 to 2015. In-sample, technical indicators display predictive power, matching or exceeding that of traditional economic forecasting variables. We also find consistent results in the fact that combining information from technical and economic variables improves equity risk premium forecasts, compared to using these variables alone. Nevertheless, out-of-sample exercises do not confirm in-sample results. Economic predictors show stronger out-of-sample forecasting ability than technical indicators, and apart from volum…

Functional Data Analysis for Optimizing Strategies of Cash-Flow Management

2017

The cash management deals with problem of automating and managing cash-flow processes. Optimization of the management processes greatly reduces overall cash handling costs. The present analysis is an empirical study of cash flows, from and to bank branches, deriving an underlying theoretical framework, which can in a reasonable way be connected with the optimal strategy. Functional data analysis is considered an appropriate framework to analyze the dynamics of the time series behavior of cash flows: since the observations are not equally spaced in time and their number is different for each series, they are converted into a collection of random curves in a space spanned by finite dimensiona…