82 results found
Meade N, Driver C, 2022, Differing behaviours of forecasters of UK GDP growth, International Journal of Forecasting, ISSN: 0169-2070
The literature suggests that the dispersion of agents’ forecasts of an event flows from heterogeneity of beliefs and models. Using a data set of fixed event point forecasts of UK GDP growth by a panel of independent forecasters published by HM Treasury, we investigate three questions concerning this dispersion: (a) Are agent's beliefs randomly distributed or do agents fall into groups with similar beliefs? (b) as agents revise their forecasts, what roles are played by their previous and consensus forecasts? and (c) is an agent's private information of persistent value? We find that agents fall into four clusters, a large majority, a few pessimists, and two idiosyncratic agents. Our proposed model of forecast revisions shows agents are influenced positively by a change in the consensus forecast and negatively influenced by the previous distance of their forecast from the consensus. We show that the forecasts of a minority of agents significantly lead the consensus.
Meade N, Islam T, 2021, Modelling and forecasting national introduction times for successive generations of mobile telephony, TELECOMMUNICATIONS POLICY, Vol: 45, ISSN: 0308-5961
Meade N, Beasley JE, Adcock CJ, 2021, Quantitative portfolio selection: Using density forecasting to find consistent portfolios, EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, Vol: 288, Pages: 1053-1067, ISSN: 0377-2217
Felipe Brito TL, Islam T, Mouette D, et al., 2020, Fuel price elasticities of market shares of alternative fuel vehicles in Brazil, TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, Vol: 89, ISSN: 1361-9209
Brito TLF, Islam T, Stettler M, et al., 2019, Transitions between technological generations of alternative fuel vehicles in Brazil, Energy Policy, Vol: 134, Pages: 110915-110915, ISSN: 0301-4215
The transportation sector is responsible for nearly a quarter of greenhouse gases emissions (GHG); thus, incisive policies are necessary to mitigate the sector’s effect on climate change. Promoting alternative fuel vehicles (AFV) is an essential strategy to reduce GHG emissions in the short term. Here, we study the effects of governmental incentives on the diffusion of ethanol and flex-fuel vehicle technologies in Brazil. We use a multi-generation diffusion model which assumes that new technologies introduce fresh market potential for adopters as well as upgraders from established technologies. Our analysis indicates that tax rates affected the adoption of both gasoline and ethanol technology, but for flex vehicles, the effect of taxation is not significant. The effect of fuel price shocks during the 1990s meant that the introduction of ethanol technology made no significant impact on market potential and a negative word-of-mouth effect contributed to the technology’s failure. In contrast, the introduction of flex technology led to almost a doubling of total market potential. As policy suggestions, we emphasise the importance of tax reduction in addition to promoting versatile technologies, which insulate consumers against price fluctuations.
Driver C, Meade N, 2019, Enhancing survey-based investment forecasts, JOURNAL OF FORECASTING, Vol: 38, Pages: 236-255, ISSN: 0277-6693
Islam T, Meade N, 2018, The direct and indirect effects of economic wealth on time to take-off, INTERNATIONAL JOURNAL OF RESEARCH IN MARKETING, Vol: 35, Pages: 305-318, ISSN: 0167-8116
Adcock CJ, Meade N, 2016, Using parametric classification trees for model selection with applications to financial risk management, European Journal of Operational Research, Vol: 259, Pages: 746-765, ISSN: 0377-2217
We describe two parametric classification tree methods, which allow formal selection of a member of aclass of generalised distributions. In the paper we consider generalised Beta distributions for non-negativerandom variables and the generalised skew-Student distribution for random variables distributed on thereal line. We introduce a class of symmetric generalised multivariate Student distributions, membersof which may also be selected using the classification trees. We present two versions of the parametricclassification tree: specific to general and general to specific. We apply the classification methods todaily returns on stocks from a selection of 15 major, mid-cap and emerging markets. The results showthat the majority of return distributions follow Student’s t, but that a non-negligible minority follow asymmetric generalised Student distribution. We confirm a well-known stylised fact about skewness: ittends not to be persistent. By contrast, kurtosis is persistent. Using the symmetric generalised multivariateStudent distribution, we present a risk management study based on efficient portfolios constructedfrom UKFTSE250 stocks and specifically concerned with the computation of value at risk. The case studydemonstrates that the model selection procedures based on the classification trees lead to more accuratecomputation of VaR than those based on the normal distribution or on non-parametric approaches. Thestudy also shows that the normal distribution may be used for VaR computations for larger portfolioswhen the holding period is longer.
Islam T, Meade N, 2015, Firm level innovation diffusion of 3G mobile connections in international context, INTERNATIONAL JOURNAL OF FORECASTING, Vol: 31, Pages: 1138-1152, ISSN: 0169-2070
Meade N, Islam T, 2015, Forecasting in telecommunications and ICT-A review, INTERNATIONAL JOURNAL OF FORECASTING, Vol: 31, Pages: 1105-1126, ISSN: 0169-2070
Valle CA, Meade N, Beasley JE, 2015, Factor neutral portfolios, OR SPECTRUM, Vol: 37, Pages: 843-867, ISSN: 0171-6468
Valle CA, Meade N, Beasley JE, 2015, An optimisation approach to constructing an exchange-traded fund, OPTIMIZATION LETTERS, Vol: 9, Pages: 635-661, ISSN: 1862-4472
Meade N, Islam T, 2015, Modelling European usage of renewable energy technologies for electricity generation, TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, Vol: 90, Pages: 497-509, ISSN: 0040-1625
Valle CA, Meade N, Beasley JE, 2014, Market neutral portfolios, OPTIMIZATION LETTERS, Vol: 8, Pages: 1961-1984, ISSN: 1862-4472
Valle CA, Meade N, Beasley JE, 2014, Absolute return portfolios, OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, Vol: 45, Pages: 20-41, ISSN: 0305-0483
Islam T, Meade N, 2013, The impact of attribute preferences on adoption timing: The case of photo-voltaic (PV) solar cells for household electricity generation, ENERGY POLICY, Vol: 55, Pages: 521-530, ISSN: 0301-4215
Boomsma TK, Meade N, Fleten S-K, 2012, Renewable energy investments under different support schemes: A real options approach, European Journal of Operational Research
Islam T, Meade N, 2012, The impact of competition, and economic globalization on the multinational diffusion of 3G mobile phones, Technological Forecasting and Social Change
Islam T, Meade N, 2011, Detecting the impact of market factors on sales takeoff times of analog cellular telephones, MARKETING LETTERS, Vol: 22, Pages: 197-212, ISSN: 0923-0645
Meade N, Beasley J, 2011, Detection of momentum effects using an index out-performance strategy, Quantitative Finance, Vol: 11, Pages: 313-326
Meade N, 2010, Oil prices – Brownian motion or mean reversion? A study using a one year ahead density forecast criterion, Energy Economics
For oil related investment appraisal, an accurate description of the evolving uncertainty in the oil price is essential. For example, when using real option theory to value an investment, a density function for the future price of oil is central to the option valuation. The literature on oil pricing offers two views. The arbitrage pricing theory literature for oil suggests geometric Brownian motion and mean reversion models. Empirically driven literature suggests ARMA-GARCH models. A characteristic of the price of oil is its sensitivity to shocks thus the density function of future prices must be able to incorporate the uncertainty due to shocks as well as the underlying volatility of a stable market.In this study, the accuracy of density forecasts for up to a year ahead is the major criterion for a comparison of a range of models of oil price behaviour, both those proposed in the literature and following from data analysis. The Kullbach Leibler information criterion is used to measure the accuracy of density forecasts.Using two crude oil price series, Brent and West Texas Intermediate (WTI) representing the US market, we demonstrate that accurate density forecasts are achievable for up to nearly two years ahead using a mixture of two Gaussians innovation process with GARCH and no mean reversion.
Ding J, Meade N, 2010, Forecasting accuracy of stochastic volatility, GARCH and EWMAmodels under different volatility scenarios', Applied Financial Economics
Meade N, Islam T, 2010, Using copulas to model repeat purchase behaviour - An exploratory analysis via a case study, EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, Vol: 200, Pages: 908-917, ISSN: 0377-2217
Meade N, Islam T, 2010, Modeling and Forecasting Diffusion, Gaining Momentum, Editors: Tidd, Publisher: Imperial College Pr, Pages: 373-426, ISBN: 9781848163546
This book adopts a multi-disciplinary and managerial process approach to understandingand promoting the adoption of innovations, based on the latest research ...
Gormley FM, Meade N, 2007, The utility of cash flow forecasts in the management of corporate cash balances, EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, Vol: 182, Pages: 923-935, ISSN: 0377-2217
Meade N, 2006, An assessment of the comparative accuracy of time series forecasts of patent filings: The benefits of disaggregation in space or time, Forecasting Innovations: Methods for Predicting Numbers of Patent Filings, Pages: 41-72, ISBN: 9783540359913
This work is concerned with methods for forecasting the filing of patents and was earned out in conjunction with the European Patent Office. The filings data were subdivided by:. Blocs-European Patent Convention countries, Japan, US and the Rest of the World. Industries-main Fields of Technology according to headings A-H of the International Patent Classification (WIPO 2000). The issues addressed are: the benefits of multivariate models versus univariate ones in exploiting any correlations between the filings in different blocs or industries; the effect of aggregation over time (from monthly to annual data) and the effect of aggregation by bloc or by industry on the accuracy of the forecast of total EPO filings. Two approaches are used: the ARIMA framework and the dynamic linear model (DLM) in both univariate and multivariate modes. The main results are: monthly data does tend to provide greater accuracy in annual forecasts; there are no significant benefits to be gained by multivariate modelling and no significant benefits are found from aggregating over blocs or industries. There are benefits from using monthly data, rather than annual data. The best modelling approaches are, for monthly data, the univariate dynamic linear model; for annual data either the univariate ARIMA or DLM could be used. The recommended forecast-ing approach provides a benchmark against which other forecasts drawing on different data sources can be compared. The filing of an application for a patent is the first step in achieving protection for intellectual property. The three major patent offices are the European (EPO), the Japanese (JPO) and the US (USPTO) offices. The examination of each application is a labour intensive process, involving technological and legal expertise. The motivation for this study of the forecasting of patent filings with the EPO is that the forecasts are a prerequisite for manpower planning at an aggregate scale and at the level of availability of expertise in dif
Meade N, Islam T, 2006, Modelling and forecasting the diffusion of innovation - A 25-year review, INTERNATIONAL JOURNAL OF FORECASTING, Vol: 22, Pages: 519-545, ISSN: 0169-2070
Meade N, 2006, An assessment of the comparative accuracy of time series forecasts of patent filings: the benefits of disaggregation in space or time, Forecasting Innovations, Methods for Predicting Numbers of Patent Filings, Editors: Hingley, Nicolas M, Heidelberg, Publisher: Springer, Pages: 40-72, ISBN: 978-3-540-35991-3
Meade N, Maier MR, 2003, Evidence of long memory in short-term interest rates, JOURNAL OF FORECASTING, Vol: 22, Pages: 553-568, ISSN: 0277-6693
Meade N, Islam T, 2003, Modelling the dependence between the times to international adoption of two related technologies, International Symposium on Forecasting (ISF), Publisher: ELSEVIER SCIENCE INC, Pages: 759-778, ISSN: 0040-1625
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