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25
Predicting Net Discount Rates: A Comparison of Professional Forecasts, Time-series Forecasts and Traditional Methods
, 2010
"... Abstract Previous research proposed two future net discount rate estimators that improved on naïve long-term average and random walk estimators. The proposed estimators were superior in the class of estimators that used only current and past observations on net discount rates. In this paper we cons ..."
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consider two extensions. First we examine whether professional forecasts perform significantly better than the two alternatives. Second, we examine the properties and performance of multivariate estimators that account for the potentially differing time-series behaviors of the underlying wage growth
Modelling and Forecasting Exchange Rates with a Bayesian TimeVarying Coe¢ cient Model,”Journal of Economic Dynamics and Control
, 1993
"... This paper employs a multivariate Bayesian time-varying coetficients (TVC) approach to model and forecast exchange rate data. It is shown that, if used as a data-generating mechanism, a TVC model induces nonlinearities in the conditional moments and leptokurtosis n the unconditional distribution of ..."
Abstract
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Cited by 13 (0 self)
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of the series. It is also shown that leptokurtic behavior disappears under time aggregation. As a forecasting device, a Bayesian TVC model improves over a random walk model. The improvements are robust to several changes in the forecasting environment. I.
Dynamic Financial Index Models: Modeling Conditional Dependencies via Graphs
"... We discuss the development and application of dynamic graphical models for multivariate financial time series in the context of Financial Index Models. The use of graphs generalizes the independence residual variation assumption of index models with a more complex yet still parsimonious model. Worki ..."
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Cited by 6 (1 self)
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We discuss the development and application of dynamic graphical models for multivariate financial time series in the context of Financial Index Models. The use of graphs generalizes the independence residual variation assumption of index models with a more complex yet still parsimonious model
An application of rule-based forecasting to a situation lacking domain knowledge
- International Journal of Forecasting
, 2000
"... Rule-based forecasting (RBF) uses rules to combine forecasts from simple extrapolation methods. Weights for combining the rules use statistical and domain-based features of time series. RBF was originally developed, tested, and validated only on annual data. For the M3-Competition, three major modif ..."
Abstract
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Cited by 5 (0 self)
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to causal forces to allow for this lack of domain knowledge. Second, automatic identification procedures were used for six time-series features that had previously been identified using judgment. This was done to reduce cost and improve reliability. Third, we simplified the rule-base by removing one method
Fitting the Term-Structure in STAMP 8.10
- OxMetrics News, September
, 2008
"... In the Summer of 2008 we have upgraded STAMP to version 8.10 which is the current release version. The new items in version 8.10 are relatively small. The forecasting dialog allows the forecasting of the unobserved components as well as the future observations. More importantly, various errors have ..."
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Cited by 1 (0 self)
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shown that the forecasts obtained from this class of models do not outperform the basic random walk forecasts, see for example Duffee (2002). These findings may not be very surprising given their focus on the cross-section dimension of yields without a reference to the time series dimension. Time series
This journal ar...
"... Rule-based forecasting (RBF) uses rules to combine forecasts from simple extrapolation methods. Weights for combining the rules use statistical and domain-based features of time series. RBF was originally developed, tested, and validated only on annual data. For the M3-Competition, three major modif ..."
Abstract
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to causal forces to allow for this lack of domain knowledge. Second, automatic identification procedures were used for six time-series features that had previously been identified using judgment. This was done to reduce cost and improve reliability. Third, we simplified the rule-base by removing one method
unknown title
"... Anne SABOURIN Mélanges bayésiens de modèles d'extrêmes multivariés, Application à la prédétermination régionale des crues avec données incomplètes. Sous la direction de: ..."
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Anne SABOURIN Mélanges bayésiens de modèles d'extrêmes multivariés, Application à la prédétermination régionale des crues avec données incomplètes. Sous la direction de:
©2007 INFORMS
"... Models of advertising response implicitly assume that the entire advertising budget is spent on disseminating one message. In practice, managers use different themes of advertising (for example, price advertisements versus product advertisements) and within each theme they employ different versions ..."
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the portfolio of ads as well as better manage their scheduling. We develop a model to show how our response model parameters can be used to improve the effectiveness of advertising budget allocation across different themes. We find that a reallocation of resources across different themes according to our model
Results 1 - 10
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25
