Geodesic
On guaranteed forecast estimation
Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ, no. 4 (2014), pp. 82-96 Cet article a éte moissonné depuis la source Math-Net.Ru

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The paper formulates the problem of time series forecast definition with a given probability (guarantee). Two approaches to the task solution are offered. The first method is based on forecasting by a time-variant regression and a relevant histogram. The second method consists of preliminary calculation of a new time series of some statistics and creation of their forecast. The methods offered are used to determine the guaranteed characteristics of Brent oil price in 2013 year and to make a long-term forecast for 2014–2016 years. Bibliogr. 12. Il. 10.
Keywords: time series, forecast with guarantee, Brent oil price.
Mots-clés : regression, estimation by histogram 
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A. V. Prasolov; K. A. Zamuraev. On guaranteed forecast estimation. Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ, no. 4 (2014), pp. 82-96. http://geodesic.mathdoc.fr/item/VSPUI_2014_4_a8/

[1] Barhoumi K., Benk S., Cristadoro R., den Reijer A., Jakaitiene A., Jelonek P., Rua A., Runstler G., Ruth K., Van Nieuwenhuyze C., Short-term forecasting of GDP using large monthly datasets – a pseudo real-time forecast evaluation exercise, ECB Occasional Paper No 84, April 2008, 25 pp.

[2] Keck A., Raubold A., “Forecasting international trade: A time series approach”, Journal of Business Cycle Measurement and Analysis, 2009:2 (2009), 157–176 | DOI

[3] Taylor J. W., McSharry P. E., “Short-term load forecasting methods: An evaluation based on european data”, IEEE Transactions on Power Systems, 22 (2007), 2213–2219 | DOI

[4] Engle R. F., “Autoregressive conditional heteroscedasticity with estimates of Variance of United Kingdom inflation”, Econometrica, 50:4 (1982), 987–1007 | DOI | MR | Zbl

[5] Bollerslev T., “Generalized autoregressive conditional heteroskedasticity”, Journal of econometrics, 31 (1986), 307–327 | DOI | MR | Zbl

[6] Ismail Z., Yahya A., Shabri A., “Forecasting gold prices using multiple linear regression method”, American journal of applied sciences, 6 (2009), 1509–1514 | DOI

[7] Prasolov A. V., Wei K. C., “On forecast of exchange rate of a foreign currency”, IEEE Intern. conference on control applications and IEEE Intern. symposium on computer-aided control systems design (September 25–27, 2000, Anchorage, Alaska, USA), 2000, 14–19

[8] Koenker K., Hallock K. F., “Quantile regression”, Journal of economic perspectives, 15:4 (2001), 143–156 | DOI | MR

[9] Tong H., “Threshold models in time series analysis — 30 years on”, Statistics Its Interface, 4 (2011), 107–136 | DOI | MR

[10] McNeil A. J., Saladin T., Zentrum E., “The peaks over thresholds method for estimating high quantiles of loss distributions”, Proc. of 28 Intern. Astin Colloquium, 1997, 21 pp.

[11] Prasolov A. V., Mathematical methods of economic dynamics, Lan', St. Petersburg, 2008, 352 pp.

[12] Prasolov A. V., Khovanov N. V., “Forecast with the use of statistical and expert methods”, Automation and Remote Control, 69:6 (2008), 1023–1034 | DOI | MR | Zbl