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1 – 10 of over 2000
Article
Publication date: 1 April 2006

Zakir Hossain, Quazi Abdus Samad and Zulficar Ali

The purpose of this paper is to generate three types of forecasts, namely, historical, ex‐post and exante, using the world famous Box‐Jenkins time series models for motor, mash…

1185

Abstract

Purpose

The purpose of this paper is to generate three types of forecasts, namely, historical, ex‐post and exante, using the world famous Box‐Jenkins time series models for motor, mash and mung prices in Bangladesh.

Design/methodology/approach

The models on the basis of which these forecasts have been computed were selected by six important information criteria such as Akaike's Information Criterion (AIC), Schwarz's Bayesian Information Criterion (BIC), Theil's R2, Theil's R2, SE(σ) and Mean Absolute Percent Errors (MAPEs). In order to examine the forecasting performance of the selected models, three types of forecast errors were estimated, i.e. root mean square percent errors (RMSPEs), mean percent forecast errors (MPFEs) and Theil's inequality coefficients (TICs).

Findings

The estimates suggest that in most cases the forecasting performances of the models in question are quite satisfactory.

Originality/value

The models developed in this paper can be used for policy purposes as far as price forecasts of the commodities are concerned.

Details

International Journal of Social Economics, vol. 33 no. 4
Type: Research Article
ISSN: 0306-8293

Keywords

Open Access
Article
Publication date: 27 July 2017

Ulrich Gunter

The purpose of this paper is to analyze the ex ante projected future trajectories of real tourism exports and relative tourism export prices of the EU-15, conditional on expert…

2088

Abstract

Purpose

The purpose of this paper is to analyze the ex ante projected future trajectories of real tourism exports and relative tourism export prices of the EU-15, conditional on expert real gross domestic product growth forecasts for the global economy provided by the Organisation for Economic Co-operation and Development for the years 2013-2017.

Design/methodology/approach

To this end, the global vector autoregression (GVAR) framework is applied to a comprehensive panel data set ranging from 1994Q1 to 2013Q3 for a cross-section of 45 countries. This approach allows for interdependencies between countries that are assumed to be equally affected by common global developments.

Findings

In line with economic theory, growing global tourist income combined with decreasing relative destination price ensures, in general, increasing tourism demand for the politically and macroeconomically distressed EU-15. However, the conditional forecast increases in tourism demand are under-proportional for some EU-15 member countries.

Practical implications

Rather than simply relying on increases in tourist income, the low price competitiveness of the EU-15 member countries should also be addressed by tourism planners and developers in order to counter the rising competition for global market shares and ensure future tourism export earnings.

Originality/value

One major contribution of this research is that it applies the novel GVAR framework to a research question in tourism demand analysis and forecasting. Furthermore, the analysis of the ex ante conditionally projected future trajectories of real tourism exports and relative tourism export prices of the EU-15 is a novel aspect in the tourism literature since conditional forecasting has rarely been performed in this discipline to date, in particular, in combination with ex ante forecasting.

Details

Journal of Tourism Futures, vol. 4 no. 2
Type: Research Article
ISSN: 2055-5911

Keywords

Article
Publication date: 11 January 2018

Thai Young Kim, Rommert Dekker and Christiaan Heij

The purpose of this paper is to show that intentional demand forecast bias can improve warehouse capacity planning and labour efficiency. It presents an empirical methodology to…

2530

Abstract

Purpose

The purpose of this paper is to show that intentional demand forecast bias can improve warehouse capacity planning and labour efficiency. It presents an empirical methodology to detect and implement forecast bias.

Design/methodology/approach

A forecast model integrates historical demand information and expert forecasts to support active bias management. A non-linear relationship between labour productivity and forecast bias is employed to optimise efficiency. The business analytic methods are illustrated by a case study in a consumer electronics warehouse, supplemented by a survey among 30 warehouses.

Findings

Results indicate that warehouse management systematically over-forecasts order sizes. The case study shows that optimal bias for picking and loading is 30-70 per cent with efficiency gains of 5-10 per cent, whereas the labour-intensive packing stage does not benefit from bias. The survey results confirm productivity effects of forecast bias.

Research limitations/implications

Warehouse managers can apply the methodology in their own situation if they systematically register demand forecasts, actual order sizes and labour productivity per warehouse stage. Application is illustrated for a single warehouse, and studies for alternative product categories and labour processes are of interest.

Practical implications

Intentional forecast bias can lead to smoother workflows in warehouses and thus result in higher labour efficiency. Required data include historical data on demand forecasts, order sizes and labour productivity. Implementation depends on labour hiring strategies and cost structures.

Originality/value

Operational data support evidence-based warehouse labour management. The case study validates earlier conceptual studies based on artificial data.

Details

International Journal of Physical Distribution & Logistics Management, vol. 48 no. 1
Type: Research Article
ISSN: 0960-0035

Keywords

Article
Publication date: 25 May 2010

Alok Dixit, Surendra S. Yadav and P.K. Jain

The purpose of this paper is to assess the informational efficiency of S&P CNX Nifty index options in Indian securities market. The S&P CNX Nifty index is a leading stock index of…

Abstract

Purpose

The purpose of this paper is to assess the informational efficiency of S&P CNX Nifty index options in Indian securities market. The S&P CNX Nifty index is a leading stock index of India, consists of 50 most frequently traded securities listed on NSE. For the purpose, the study covers a period of six years from 4 June 2001 (the starting date for index options in India) to 30 June 2007.

Design/methodology/approach

The informational efficiency of implied volatilities (IVs) has been tested vis‐à‐vis select conditional volatilities models, namely, GARCH(1,1) and EGARCH(1,1). The tests have been carried out for “in‐the‐sample” as well as “out‐of‐the‐sample” forecast efficiency of implied volatilities.

Findings

The results of the study reveal that implied volatilities do not impound all the information available in the past returns; therefore, these are indicative of the violation of efficient market hypothesis in the case of S&P CNX Nifty index options market in India.

Practical implications

The finance managers, in Indian context, should rely on conditional volatility models (especially the EGARCH(1,1) model) compared to IV‐based forecasts to predict volatility for the horizon of one week. The stock exchanges and market regulator (SEBI) need to take certain initiatives in terms of extending the short‐selling facility and start trading of volatility index (VIX) to enhance the accuracy of IV‐based forecasts.

Originality/value

The paper addresses an issue which is still unexplored in the context of Indian securities market and in that sense makes an important contribution to literature on microstructure studies.

Details

Journal of Advances in Management Research, vol. 7 no. 1
Type: Research Article
ISSN: 0972-7981

Keywords

Article
Publication date: 1 January 1986

ROLAND HERRMANN

Price stabilization in international commodity markets is a main element of the North‐South dialogue. Within the Integrated Programme on Commodities (IPC) of UNCTAD, it is…

Abstract

Price stabilization in international commodity markets is a main element of the North‐South dialogue. Within the Integrated Programme on Commodities (IPC) of UNCTAD, it is intended to create buffer stocks for 10 core commodities: sugar, natural rubber, cocoa, coffee, tea, cotton, jute, hard fibres, copper, and tin. Several theoretical studies justify these plans by stressing the positive effects of a functioning buffer stock scheme on different economic goals. It is argued that price stabilization will, “potentially at least, improve aggregate welfare” (Turnovsky, 1978, p. 143) and that risk benefits in the case of risk‐averse producers “will be far more important” (Bigman, 1982, p. 1984; on the concept, see Newbery/Stiglitz, 1981, pp. 267 et seq.) than the transfer benefits, if income uncertainty is reduced by the stabilization policy. Other positive effects of buffer stocks are stressed with respect to food security (Bignan, 1982, pp. 129 et seq.) and, except for the case of supply‐induced fluctuations and a price elastic import demand, with respect to the stability of export earnings (Nguyen, 1980, pp. 343 et seq.). The export earnings stabilizing effect as well as a mostly earnings‐raising effect is confirmed for several core commodities by simulation analyses (Behrman/Ramangkura, 1978, p. 166) and by dynamic optimization (Lee/Blandford, 1980, p. 385). Moreover, stable export earnings of less developed countries (LDCs) are expected to induce higher growth rates of GNP than unstable ones (Lim, 1976, pp. 311 et seq.).

Details

Studies in Economics and Finance, vol. 10 no. 1
Type: Research Article
ISSN: 1086-7376

Article
Publication date: 19 September 2023

Pamela Fae Kent, Richard Kent and Michael Killey

This study aims to provide insights into US and Australian analysts' views regarding the relative importance of disclosing the direct method (DM) or indirect method (IM) statement…

Abstract

Purpose

This study aims to provide insights into US and Australian analysts' views regarding the relative importance of disclosing the direct method (DM) or indirect method (IM) statement of cash flows and forecasting firm performance.

Design/methodology/approach

Evidence is collected from responses to 104 surveys and 52 interviews completed by US and Australian analysts from 2017 to 2022. The survey and interview questions are developed with reference to the literature.

Findings

US and Australian analysts believe that the DM format provides incremental benefits compared to the IM for (1) confirming the reliability of earnings; (2) improving earnings confidence; (3) more accurate ex ante forecasts of operating cash flow and earnings; and (4) identifying opportunistic accruals manipulation. Analysts view that DM disclosure can lower firm-level cost of equity, although US interviewees more uniformly expect lower costs of equity under DM disclosure when firms yield low earnings quality. DM disclosure is also more important during unstable economic periods, as proxied by COVID-19.

Originality/value

Limited research currently exists regarding disclosure of the DM or IM and its impact on analysts' forecasting accuracy, earnings quality, economic uncertainty and cost of equity. Previous research has relied on archival research to examine differences between the DM and IM methods and are limited by data availability. Our findings are particularly relevant to the US market with few US firms reporting the DM format.

Details

Journal of Accounting Literature, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-4607

Keywords

Article
Publication date: 28 June 2022

Yi-Chung Hu and Geng Wu

Given that the use of Google Trends data is helpful to improve forecasting performance, this study aims to investigate whether the precision of forecast combination can benefit…

Abstract

Purpose

Given that the use of Google Trends data is helpful to improve forecasting performance, this study aims to investigate whether the precision of forecast combination can benefit from the use of Google Trends Web search index along with the encompassing set.

Design/methodology/approach

Grey prediction models generate single-model forecasts, while Google Trends index serves as an explanatory variable for multivariate models. Then, three combination sets, including sets of univariate models (CUGM), all constituents (CAGM) and constituents that survive the forecast encompassing tests (CSET), are generated. Finally, commonly used combination methods combine the individual forecasts for each combination set.

Findings

The tourism volumes of four frequently searched-for cities in Taiwan are used to evaluate the accuracy of three combination sets. The encompassing tests show that multivariate grey models play a role to be reckoned with in forecast combinations. Furthermore, the empirical results indicate the usefulness of Google Trends index and encompassing tests for linear combination methods because linear combination methods coupled with CSET outperformed that coupled with CAGM and CUGM.

Practical implications

With Google Trends Web search index, the tourism sector may benefit from the use of linear combinations of constituents that survive encompassing tests to formulate business strategies for tourist destinations. A good forecasting practice by estimating ex ante forecasts post-COVID-19 can be further provided by scenario forecasting.

Originality/value

To improve the accuracy of combination forecasting, this research verifies the correlation between Google Trends index and combined forecasts in tourism along with encompassing tests.

Google 搜尋趨勢指標與涵蓋性檢定對於旅遊需求組合預測的影響

目的

過去的研究顯示 Google 搜尋趨勢資料有助於改善旅遊需求預測的準確度,本研究就此進一步探討 Google 搜尋趨勢網頁搜尋指標與涵蓋性檢定的使用對於組合預測準確度所造成的影響。

設計/方法論/方法

本研究以 Google 搜尋趨勢指標做為多變量灰色預測模式的解釋變數,並以單變量與多變量灰色模式產生各別預測值。在分別產生由所有的單變量模式 (CUGM)所有的模式 (CAGM), 以及經過涵蓋性檢定所留存下來之模式 (CSET) 所組成之集合後,就各別的組合集以常用的組合方法產生預測值。

發現

以台灣的四個熱搜旅遊城市的旅遊人數進行三個組合集的預測準確度分析。涵蓋性檢定顯示多變量灰色模式在組合預測中扮演重要的角色,而結果亦呈現線性組合方法在 CSET優於在 CUGMCAGM 的準確度,突顯搜尋趨勢指標與涵蓋性檢定對於線性組合方法的有用性。

實踐意涵

藉由 Google 搜尋趨勢網頁搜尋指標與涵蓋性檢定,旅遊部門應可透過線性組合方法的預測規劃旅遊目的地的經營策略。新冠疫情下於各季的事前預測亦可結合情境預測具體呈現。

原創性/價值

為提升組合預測在旅遊需求的預測準確度,本研究結合涵蓋性檢定以分析 Google 搜尋趨勢指標與組合預測準確度之間的關聯性。

關鍵字

旅遊需求,涵蓋性檢定,Google 搜尋趨勢,灰色預測,組合預測

文章类型

研究型论文

El impacto de Google Trends en la previsión de viajes combinados y su evidencia relacionada

Propósito

Dado que el uso de los datos de Google Trends es útil para mejorar la precisión de las predicciones, este estudio examina si el uso del índice de búsqueda web de Google Trends combinado con la agregación de relevancia puede mejorar la precisión del predictor.

Diseño/metodología/enfoque

El modelo predictivo gris genera predicciones bajo un único modelo, mientras que el modelomultivariado utiliza el indicador Google Trends como variable explicativa. Se generaron tresensamblajes generales, incluido el Modelo armónico único (CUGM), los ensamblajes de todos loscomponentes (CAGM) y la prueba de presencia de componentes con predicción (CSET). Laspredicciones individuales encada grupo luego se combinan utilizando métodos de correlación deuso común.

Recomendaciones

Utilizando el número de turistas en las cuatro ciudades más investigadas de Taiwán, los tresgrupos combinados se clasificaron según su precisión. Las pruebas incluidas muestran que losmodelos multivariados en escala de grises son importantes para la predicción. Además, losresultados de las pruebas muestran que el índice de Google Trends y las pruebas que incluyenmétodos de suma lineal son útiles porque los métodos combinados con CSET funcionan majorque los métodos combinados con CSET. CAGM y VCUG.

Implicaciones practices

La industria de viajes puede usar el índice de búsqueda web de Google Trends para desarrollarestrategias comerciales para atracciones basadas en un conjunto lineal de componentes.

Autenticidad/valor

Con el objetivo de mejorar la precisión de los pronósticos agregados, este estudio investiga larelación entre el índice de tendencias de Google y las expectativas generales de viaje junto con laevidencia global.

Palabras clave

Demanda de viajes, Experiencia global, Tendencias de Google, Predicción gris

Tipo de papel

Trabajo de investigación

Article
Publication date: 10 April 2009

Nicolas Savio and Konstantinos Nikolopoulos

Once a policy proposed by the European Commission is approved by European Parliament or Council, its implementation strategy is the responsibility of the member states. Often

Abstract

Purpose

Once a policy proposed by the European Commission is approved by European Parliament or Council, its implementation strategy is the responsibility of the member states. Often, there will be several parallel strategies shaped by a series of incentives financed by the government and naturally, the aim is to choose the most cost effective one. For strategy and planning as well as budgeting purposes, forecasts of the adoption rate of these policy implementation strategies will be an indicator as to their effectiveness. A new hybrid approach combining structured analogies and econometric modelling is proposed for producing such forecasts.

Design/methodology/approach

With every different policy, there will be different qualitative and quantitative data available for producing such implementation strategy adoption rate forecasts. Hence, the proposed hybrid approach, which combines the strengths and reduces the weaknesses of each of its constituents, can be adjusted to match the quantity and nature of the available data.

Findings

This paper reveals a lack of emphasis on such a forecasting application in the existing literature, while stressing its importance to governmental decision makers. What is more, the paper reveals a lack of documentation of this forecasting process in large governmental structures.

Practical implications

If shown to improve the ability to produce such forecasts, the proposed approach could be very beneficial to decision makers when faced with several possible implementation strategies.

Originality/value

The use of expertise is quite common in forecasting policy impact but in an unstructured way. The advanced model proposes structuring the use of analogies in an objective manner. Furthermore, combining with econometric modelling, the incorporation of valuable quantitative information is made possible.

Details

Foresight, vol. 11 no. 2
Type: Research Article
ISSN: 1463-6689

Keywords

Article
Publication date: 1 May 1988

K. Holden and D.A. Peel

The purpose of this article is to provide some further empirical evidence on the ex ante forecasting performance of the three major independent modelling groups in the United…

Abstract

The purpose of this article is to provide some further empirical evidence on the ex ante forecasting performance of the three major independent modelling groups in the United Kingdom, namely, the National Institute of Economic and Social Research (NI), the Centre for Economic Forecasting of the London Business School (LBS) and the Liverpool Modelling Group (LI). The motivation for our analysis is threefold. First is the fact that according to many forecasting practitioners, the ultimate test of an econometric model is its predictive ability.

Details

Journal of Economic Studies, vol. 15 no. 5
Type: Research Article
ISSN: 0144-3585

Article
Publication date: 5 January 2010

Mahfuzul Haque and Oscar Varela

The purpose of this paper is to apply safety‐first portfolio principles in an environment where financial risk exists because of the probability of terrorist attacks, where the…

Abstract

Purpose

The purpose of this paper is to apply safety‐first portfolio principles in an environment where financial risk exists because of the probability of terrorist attacks, where the catastrophic events of September 11, 2001 (911) are the focal point of the analysis.

Design/methodology/approach

Safety‐first portfolios of US equities bilaterally combined with 12 developed and emerging region global equity indices are obtained for 911. Extreme value theory and safety‐first principles are used to optimize these portfolios for US risk‐averse investors. The actual performances of all portfolios in the post‐911 period are compared to the optimal results. The robustness of the results is examined by replicating the analysis for the period following July 7, 2006, when no actual terrorist attacks occurred on US soil.

Findings

Optimal ex ante (ex post) safety‐first portfolios on 911 have high (low) US weights, and on July 7, 2006 low US weights. The differences are attributed to changes in market projections and/or conditions. In all cases, wealth is preserved even without the ex post optimal portfolios.

Practical implications

Safety‐first portfolio optimization can protect wealth given financial risks of extreme events like terrorist attacks.

Originality/value

The paper shows that quantitative assessments of financial risk are feasible, even though uncertainty with experts' risk assessments of extreme events such as 911 exists because of limited historical data and low probability of occurrence. The results are useful to investors developing international diversification strategies to protect wealth given the risks of terrorist attacks.

Details

The Journal of Risk Finance, vol. 11 no. 1
Type: Research Article
ISSN: 1526-5943

Keywords

1 – 10 of over 2000