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The complexity of forecast testing

Lance Fortnow, Rakesh Vohra
2008 Proceedings of the 9th ACM conference on Electronic commerce - EC '08  
We look at the computational complexity of such forecasters and exhibit a linear-time test and a distribution of nature such that any forecaster without knowledge of the future that can fool the test must  ...  We consider tests that given a finite sequence of forecast predictions and outcomes will either pass or fail the forecaster.  ...  Tests More Complex than the Forecast We show that no forecasting algorithm can ignorantly pass a test that is more complex itself.  ... 
doi:10.1145/1386790.1386814 dblp:conf/sigecom/FortnowV08 fatcat:vjqnluvkwjd6fasdow4bwmpcra

The complexity of forecast testing

Lance Fortnow, Rakesh V. Vohra
2008 ACM SIGecom Exchanges  
We look at the computational complexity of such forecasters and exhibit a linear-time test and a distribution of nature such that any forecaster without knowledge of the future that can fool the test must  ...  We consider tests that given a finite sequence of forecast predictions and outcomes will either pass or fail the forecaster.  ...  Tests More Complex than the Forecast We show that no forecasting algorithm can ignorantly pass a test that is more complex itself.  ... 
doi:10.1145/1486877.1486885 fatcat:wwjvctnuaffe3ktsxqzucgeuke

The Complexity of Forecast Testing

2009 Econometrica  
We look at the computational complexity of such forecasters and exhibit a linear-time test and a distribution of nature such that any forecaster without knowledge of the future that can fool the test must  ...  We consider tests that given a finite sequence of forecast predictions and outcomes will either pass or fail the forecaster.  ...  Tests More Complex than the Forecast We show that no forecasting algorithm can ignorantly pass a test that is more complex itself.  ... 
doi:10.3982/ecta7163 fatcat:ignd4cxs5jbqvj7qvouj2qt4ka

Replication and Extension of a Forecasting Decision Support System: An Empirical Examination of the Time Series Complexity Scoring Technique

Monica Adya, Edward Lusk
2018 AIS Transactions on Replication Research  
Prior studies in forecasting have argued convincingly that the design of FDSS should incorporate the complexity of the forecasting task.  ...  The CST uses characteristics of the time series to trigger 12 rules that score the complexity of a time series and classify it along the binary dimension of Simple or Complex.  ...  Their tests confirmed that complexity detrimentally impacted the accuracy of judgmental forecasts.  ... 
doi:10.17705/1atrr.00025 fatcat:axvtyyvau5bv5dmho7py5osrcy

Do analysts understand the economic and reporting complexities of derivatives?

Hye Sun Chang, Michael Donohoe, Theodore Sougiannis
2016 Journal of Accounting & Economics  
We investigate whether and how the complexity of derivatives influences analysts' earnings forecast properties.  ...  These results do not appear to be driven by the economic complexity of derivatives, but rather the financial reporting of such economic complexity.  ...  Main results Descriptive statistics and univariate tests (2) because analyst-level tests would not address the issue of whether there are cross-firm differences in forecasts due to the complexity of  ... 
doi:10.1016/j.jacceco.2015.07.005 fatcat:f4kqa3ipgjhtph2r7ibvxgszmi

Simple versus complex forecasting: The evidence

Kesten C. Green, J. Scott Armstrong
2015 Journal of Business Research  
None of the papers provide a balance of evidence that complexity improves forecast accuracy.  ...  They can rate the simplicity of forecasters' procedures using the questionnaire at simple-forecasting.com.  ...  The forecast errors, MAPEs, from the no-change model were half those of forecasts from the most complex extrapolation method tested, generalized adaptive filtering.  ... 
doi:10.1016/j.jbusres.2015.03.026 fatcat:g5tutodwrrawhpneaeibnnnmfe

Development and validation of a rule-based time series complexity scoring technique to support design of adaptive forecasting DSS

Monica Adya, Edward J. Lusk
2016 Decision Support Systems  
there exists no formal way of characterizing the complexity of forecasting tasks.  ...  The study concludes with a comprehensive framework for design of FDSS that can integrate the CST to adaptively support forecasters under varied conditions of series complexity.  ...  Our appreciation also extends to participants at the 2014 International Symposium on Forecasting, Rotterdam and those at SBE Research Workshop at SUNY: Plattsburgh for their discussions of complexity in  ... 
doi:10.1016/j.dss.2015.12.009 fatcat:6wq7hzerajd4vhuxoucuhlhade

Earthquake forecasting during the complex Amatrice-Norcia seismic sequence

Warner Marzocchi, Matteo Taroni, Giuseppe Falcone
2017 Science Advances  
We show that the current Italian operational earthquake forecasting system issued statistically reliable and skillful space-time-magnitude forecasts of the largest earthquakes during the complex 2016-2017  ...  This capability to deliver statistically reliable forecasts is an essential component of any program to assist public decision-makers and citizens in the challenging risk management of complex seismic  ...  The authors are responsible of the content of this paper, which does not necessarily reflect the official position and policies of the Department of Civil Protection.  ... 
doi:10.1126/sciadv.1701239 pmid:28924610 pmcid:PMC5597309 fatcat:ia55b6ixxzfcviuedm4244k7ga

DETERMINANTS OF BUDGET FORECAST ERRORS AND THEIR IMPACTS ON BUDGET EFFECTIVENESS: EVIDENCE FROM INDONESIA

Baldric Siregar, Lilis Susanti
2019 Journal of Economics, Business & Accountancy  
Partial least square is used to test hypotheses. The results show that the significant factors affecting budget forecast errors are revenue growth, expenditure growth, and government complexity.  ...  The hypotheses tested including revenue growth, expenditure growth, delays in budget approval, government complexity, and government type impacts on budget forecast errors and the errors impact on budget  ...  The test on the effect of government complexity on budgeting forecasting error resulted in the path coefficients and p values of -0.103 and 0.014 respectively.  ... 
doi:10.14414/jebav.v21i3.1468 fatcat:qdgld4mrijfydgmf7wy4xlppyy

A COMPARATIVE STUDY OF FORECASTING MODELS FOR TREND AND SEASONAL TIME SERIES DOES COMPLEX MODEL ALWAYS YIELD BETTER FORECAST THAN SIMPLE MODELS

Suhartono Suhartono
2005 Jurnal Teknik Industri  
In this empirical research, we study on the effectiveness of the forecasting performance, particularly to answer whether a complex method always give a better forecast than a simpler method.  ...  Additionally, we also find the possibility to do further research especially the use of hybrid model by combining some forecasting method to get better forecast, for example combination between decomposition  ...  We can clearly see that the more complex of FFNN model tends to overfitting the data in the training and due to have poor forecast in testing.  ... 
doaj:01a45a6ffb34484b8d79cd54910d7c71 fatcat:zy7dwennj5eghc7pzml53ps5qq

Personalized Forecasting System for Complex Product Quality Based on Predictive Control Model of Multiple Linear Regression Analysis

Jihong Pang
2016 International Journal of u- and e- Service, Science and Technology  
Then, an example shows the feasibility of using predictive control model in complex product quality personalized forecasting.  ...  And these variables of personalized forecasting system dealt with defects, mistakes and symptoms of failure. The personalized forecasting system for complex product quality is presented in Figure 1 .  ...  Acknowledgments This work was supported by the National Natural Science Foundation, China (No.71301120), the Provincial Natural Science Foundation, Zhejiang, China (No.LY13G010002).  ... 
doi:10.14257/ijunesst.2016.9.7.03 fatcat:b7yybc2kcbdo3ip4rmgvmzpvw4

Forecasting with Econometric Methods: Folklore Versus Fact

J. Scott Armstrong
1978 The journal of business  
Two beliefs of econometricians were examined: (1) Econometric methods provide more accurate short-term forecasts than do other methods; and (2) more complex econometric methods yield more accurate forecasts  ...  A review of the published empirical evidence yielded little support for either of the two statements in the 41 studies.  ...  Fair (1971) found little difference between his simple model and the more complex Wharton model in a test of ex post predictive validity.  ... 
doi:10.1086/296016 fatcat:xyix7w33k5b4bjbcythwhkm4d4

Comparing Simple Forecasting Methods and Complex Methods: A Frame of Forecasting Competition

Emrah Gulay
2018 Scientific Annals of Economics and Business  
In addition, the contribution of this study is to show how important to use domestic savings in forecasting GCF.  ...  Therefore, forecasting GCF is the key subject to the economists' decisions making.  ...  In this paper, I use simple forecasting methods and complex ones to make comparison of methods in terms of out-of-sample forecasting.  ... 
doi:10.2478/saeb-2018-0010 fatcat:62rj6y7jrrez7gjqifglg6a3wm

A comparison of LSTM and GRU networks for learning symbolic sequences [article]

Roberto Cahuantzi, Xinye Chen, Stefan Güttel
2021 arXiv   pre-print
We explore relations between the hyper-parameters of a recurrent neural network (RNN) and the complexity of string sequences it is able to memorize.  ...  Our results also indicate that the learning rate and the number of units per layer are among the most important hyper-parameters to be tuned.  ...  The other two tests explore the remaining parameters with seed strings of low and high complexity, respectively.  ... 
arXiv:2107.02248v1 fatcat:ilsxako76fgodm2aukyworvjl4

Learning, Portfolio Complexity and Informational Asymmetry in Forecasts of Sell-Side Analysts

Melquiades Junior
2017 Brazilian Business Review  
The aim of this study was to analyze the association of learning and complexity in the target price forecasts and sell-side analysts' recommendations on the BM&FBovespa.  ...  Learning, portfolio complexity and informational asymmetry in forecasts of sell-side analysts BBR, Braz.  ...  The tests applied in the models of consensus analysis were (1): Lagrange's Multiplier Test-time effects (Breusch-Pagan), (2) F test for individual effects, (3) Hausman's test, (4) Breusch-Godfrey's test  ... 
doi:10.15728/bbr.2017.14.2.1 fatcat:cbgvocibsffvtopfwxtjnw7kqq
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