Zobrazeno 1 - 10 of 242 pro vyhledávání: '"R A, Donaldson"'
1
Estimating the Equity Premium
Autor: Mark J. Kamstra, R. Glen Donaldson, Lisa A. Kramer
Publikováno v: Journal of Financial and Quantitative Analysis. 45:813-846
Existing empirical research investigating the size of the equity premium has largely consisted of a series of innovations around a common theme: producing a better estimate of the equity premium by using better data or a better estimation technique.
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::48138205661db422808698b5b8860606
https://doi.org/10.1017/s0022109010000347
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2
Towards automation of colour/weave selection in Jacquard designs: model verification through visual assessment
Autor: Abdel-Fattah M. Seyam, Kavita Mathur, R. Alan Donaldson, David Hinks
Publikováno v: Coloration Technology. 124:48-55
A geometric model combined with a colour model to predict the colour contribution of each pre-coloured yarn in terms of colour attributes of each area of a Jacquard pattern was developed. To validate the predicted calculations (colorimetric data), a
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::fd64d4b2851f459c89d8f47e4ac7f247
https://doi.org/10.1111/j.1478-4408.2007.00121.x
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3
Prediction of Color Attributes Through Geometrical Modeling
Autor: David Hinks, Kavita Mathur, Abdel-Fattah M. Seyam, R. Alan Donaldson
Publikováno v: Research Journal of Textile and Apparel. 12:19-31
Today, Jacquard woven fabric producers are able to digitally control each warp yarn individually, pre-program the variable pick density and speed for each filling yarn, and automatically change a pattern without stopping the weaving process. Jacquard
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9d05062b0cc0aeebd4af693299a52643
https://doi.org/10.1108/rjta-12-01-2008-b003
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4
VOLATILITY FORECASTS, TRADING VOLUME, AND THE ARCH VERSUS OPTION-IMPLIED VOLATILITY TRADE-OFF
Autor: Mark J. Kamstra, R. Glen Donaldson
Publikováno v: Journal of Financial Research. 28:519-538
We investigate empirically the role of trading volume (1) in predicting the relative informativeness of volatility forecasts produced by autoregressive conditional heteroskedasticity (ARCH) models versus the volatility forecasts derived from option p
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b2597939bb77fac538eaf90b0e4b02ff
https://doi.org/10.1111/j.1475-6803.2005.00137.x
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5
Neural network forecast combining with interaction effects
Autor: R. Glen Donaldson, Mark J. Kamstra
Publikováno v: Journal of the Franklin Institute. 336:227-236
In this paper we discuss and expand recent innovations in forecast combining with artificial neural networks (ANNs). In particular, we demonstrate that ANNs can outperform traditional forecast combining procedures, such as least-squares weighting, be
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c3bd232faba294d533d1715be430e2c2
https://doi.org/10.1016/s0016-0032(98)00018-0
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6
An artificial neural network-GARCH model for international stock return volatility
Autor: Mark J. Kamstra, R. Glen Donaldson
Publikováno v: Journal of Empirical Finance. 4:17-46
We construct a seminonparametric nonlinear GARCH model, based on the Artificial Neural Network (ANN) literature, and evaluate its ability to forecast stock return volatility in London, New York, Tokyo and Toronto. In-sample and out-of-sample comparis
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f70c71a9986b71f28071530672e865a0
https://doi.org/10.1016/s0927-5398(96)00011-4
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7
A New Dividend Forecasting Procedure that Rejects Bubbles in Asset Prices: The Case of 1929’s Stock Crash
Autor: Mark J. Kamstra, R. Glen Donaldson
Publikováno v: Review of Financial Studies. 9:333-383
We develop a new procedure to forecast future cash flows from a financial asset and then use the present value of our cash flow forecasts to calculate the asset's fundamental price. As an example, we construct a nonlinear ARMA-ARCH-Artificial Neural
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::51834a77d31f6a1a733ed51d790892a6
https://doi.org/10.1093/rfs/9.2.333
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8
Variation of the stress dependent magnetic flux leakage signal with defect depth and flux density
Autor: R. M. Donaldson, T. W. Krause, David L. Atherton, R. Barnes
Publikováno v: NDT & E International. 29:79-86
The effects of uniaxial stress on the normal (radial) component of the magnetic flux leakage (MFL) signal induced by blind-hole defects for depths of 25%, 50% and 75% of the thickness of the pipe wall were investigated with a pipe wall flux density o
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::da888dc678d90b7519576a59e5e4c139
https://doi.org/10.1016/0963-8695(95)00050-x
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10
Forecast combining with neural networks
Autor: R. Glen Donaldson, Mark J. Kamstra
Publikováno v: Journal of Forecasting. 15:49-61
This paper investigates the use of Artificial Neural Networks (ANNs) to combine time series forecasts of stock market volatility from the USA, Canada, Japan and the UK. We demonstrate that combining with nonlinear ANNs generally produces forecasts wh
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::934cb57658b28b9a241c057eae56b243
https://doi.org/10.1002/(sici)1099-131x(199601)15:1<49::aid-for604>3.0.co
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