daily interval
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2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Lu Zhang ◽  
Junbiao Zhang ◽  
Tao Xiong ◽  
Chiao Su

This paper examines the interval forecasting of carbon futures prices in one of the most important carbon futures market. Specifically, the purpose of this study is to present a novel hybrid approach, which is composed of multioutput support vector regression (MSVR) and particle swarm optimization (PSO), in the task of forecasting the highest and lowest prices of carbon futures on the next trading day. Furthermore, we set out to investigate if considering some potential predictors, which have strong influence on carbon futures prices, in modeling process is useful for achieving better prediction performance. Aiming at testing its effectiveness, we benchmark the forecasting performance of our approach against four competitors. The daily interval prices of carbon futures contracts traded in the Intercontinental Futures Exchange from August 12, 2010, to November 13, 2014, are used as the experiment dataset. The statistical significance of the interval forecasts is examined. The proposed hybrid approach is found to demonstrate the higher forecasting performance relative to all other competitors. Our application offers practitioners a promising set of results with interval forecasting in carbon futures market.


2009 ◽  
Vol 8 (sup2) ◽  
pp. 697-699 ◽  
Author(s):  
Angela Gabriella D’Alessandro ◽  
Rosanna De Petro ◽  
Salvatore Claps ◽  
Michele Pizzillo ◽  
Giovanni Martemucci

2008 ◽  
Vol 349 (3-4) ◽  
pp. 512-523 ◽  
Author(s):  
Neil K. Ganju ◽  
Noah Knowles ◽  
David H. Schoellhamer
Keyword(s):  

1982 ◽  
Vol 50 (3_suppl) ◽  
pp. 1228-1230
Author(s):  
G. P. Nowak ◽  
M. A. Persinger ◽  
M. R. Dewson

16 rats that had been given either one or two training days of 50, response-contingent rewards per day were placed upon one of two schedules in which the daily interval between nonresponse-contingent rewards was either increased or decreased. In the expanding time condition, the fixed interval of nonresponse-contingent reward delivery changed from 10 sec. to 14 min. over 9 consecutive days while in the collapsing-time condition, the intervals were reduced from 14 min. to 10 sec. over the same duration. Whereas both one-day and two-day training groups in the collapsing-time condition and the two-day group in the expanding-time condition demonstrated typical extinction profiles, the one-day expanding-time group maintained significantly higher total responses over the entire period.


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