✦ LIBER ✦

The anchor and adjustment heuristic in time-series forecasting

✍ Scribed by Michael Lawrence; Marcus O'connor

Publisher: John Wiley and Sons
Year: 1995
Tongue: English
Weight: 659 KB
Volume: 14
Category: Article
ISSN: 0277-6693
DOI: 10.1002/for.3980140504

No coin nor oath required. For personal study only.

✦ Synopsis

This paper explores the relevance of the anchor and adjustment heuristic in judgemental time-series extrapolation. Using a database of real time series it examines the proposition that people anchor on the last history value of the series and make insufficient adjustments from it in making their forecast. In contrast to studies in behavioural decision making, analysis shows that the anchor and adjustment heuristic does not describe the behaviour of time-series forecasters. Adjustments from the anchor are often excessive, not insufficient. A number of possible explanations for this exceptional finding are explored.

📜 SIMILAR VOLUMES

The bias in time series volatility forec

The bias in time series volatility forecasts

✍ Louis H. Ederington; Wei Guan 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 137 KB

## Abstract By Jensen's inequality, a model's forecasts of the variance and standard deviation of returns cannot both be unbiased. This study explores the bias in GARCH type model forecasts of the standard deviation of returns, which we argue is the more appropriate volatility measure for most fina

Back propagation in time-series forecast

Back propagation in time-series forecasting

✍ Gerson Lachtermacher; J. David Fuller 📂 Article 📅 1995 🏛 John Wiley and Sons 🌐 English ⚖ 958 KB

## Abstract One of the major constraints on the use of back propagation neural networks as a practical forecasting tool is the number of training patterns needed. We propose a methodology that reduces the data requirements. The general idea is to use the Box‐Jenkins model in an exploratory phase to

Time-series forecasting of the German un

Time-series forecasting of the German unemployment rate

✍ PD Dr. Michael Funke 📂 Article 📅 1992 🏛 John Wiley and Sons 🌐 English ⚖ 810 KB

The purpose of the paper is to investigate the accuracy of forecasts derived from univariate and multivariate time-series models. An iterative method to adjust for impact assessment in univariate ARIMA models is discussed and illustrated for the German unemployment rate. Finally, we also examine the

Forecasting the federal budget with time

Forecasting the federal budget with time-series models

✍ Hamid Baghestani; Robert McNown 📂 Article 📅 1992 🏛 John Wiley and Sons 🌐 English ⚖ 768 KB

The stochastic properties of conventionally defined federal expenditures and revenues are examined, and cointegration is found. Alternative timeseries models-univariate ARIMA models, vector autoregressions in levels and differences, and an error correction model-are specified and estimated using qua

Linear combination of restrictions and f

Linear combination of restrictions and forecasts in time series analysis

✍ Victor M. Guerrero; Daniel Peña 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 212 KB 👁 2 views

An important tool in time series analysis is that of combining information in an optimal way. Here we establish a basic combining rule of linear predictors and show that such problems as forecast updating, missing value estimation, restricted forecasting with binding constraints, analysis of outlier

Time-series Properties and Forecasts of

Time-series Properties and Forecasts of Crude Steel Consumption in the UK

✍ M. EVANS; S. B. WALTON 📂 Article 📅 1997 🏛 John Wiley and Sons 🌐 English ⚖ 277 KB 👁 2 views

This paper makes use of simple graphical techniques, a seasonal unit root test and a structural time-series model to obtain information on the time series properties of UK crude steel consumption. It shows that steel consumption has, after the removal of some quite substantial outliers, a fairly con