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Journal articles on the topic 'Forecast strategy'

Author: Grafiati

Published: 4 June 2021

Last updated: 4 February 2022

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1

Rupp, David E., Thomas C. Wainwright, and Peter W. Lawson. "Effect of forecast skill on management of the Oregon coast coho salmon (Oncorhynchus kisutch) fishery." Canadian Journal of Fisheries and Aquatic Sciences 69, no. 6 (2012): 1016–32. http://dx.doi.org/10.1139/f2012-040.

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Better fisheries management is often given as one justification for research on improving forecasts of fish survival. However, the value gained from expected improvements in forecast skill in terms of achieving management goals is rarely quantified as part of research objectives. Using Monte Carlo simulations of population dynamics, we assessed the effect of forecast skill under two strategies for managing Oregon coast natural (OCN) coho salmon ( Oncorhynchus kisutch ). The first, or status quo, strategy is currently being used to rebuild threatened OCN coho populations. This strategy determin

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Ebert, Elizabeth E. "Neighborhood Verification: A Strategy for Rewarding Close Forecasts." Weather and Forecasting 24, no. 6 (2009): 1498–510. http://dx.doi.org/10.1175/2009waf2222251.1.

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Abstract High-resolution forecasts may be quite useful even when they do not match the observations exactly. Neighborhood verification is a strategy for evaluating the “closeness” of the forecast to the observations within space–time neighborhoods rather than at the grid scale. Various properties of the forecast within a neighborhood can be assessed for similarity to the observations, including the mean value, fractional coverage, occurrence of a forecast event sufficiently near an observed event, and so on. By varying the sizes of the neighborhoods, it is possible to determine the scales for

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Savage, Tamara, Alex Davis, Baruch Fischhoff, and M. Granger Morgan. "A strategy to improve expert technology forecasts." Proceedings of the National Academy of Sciences 118, no. 21 (2021): e2021558118. http://dx.doi.org/10.1073/pnas.2021558118.

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Forecasts of the future cost and performance of technologies are often used to support decision-making. However, retrospective reviews find that many forecasts made by experts are not very accurate and are often seriously overconfident, with realized values too frequently falling outside of forecasted ranges. Here, we outline a hybrid approach to expert elicitation that we believe might improve forecasts of future technologies. The proposed approach iteratively combines the judgments of technical domain experts with those of experts who are knowledgeable about broader issues of technology adop

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Yang, Qichun, Quan J. Wang, Kirsti Hakala, and Yating Tang. "Bias-correcting input variables enhances forecasting of reference crop evapotranspiration." Hydrology and Earth System Sciences 25, no. 9 (2021): 4773–88. http://dx.doi.org/10.5194/hess-25-4773-2021.

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Abstract. Reference crop evapotranspiration (ETo) is calculated using a standard formula with temperature, vapor pressure, solar radiation, and wind speed as input variables. ETo forecasts can be produced when forecasts of these input variables from numerical weather prediction (NWP) models are available. As raw ETo forecasts are often subject to systematic errors, statistical calibration is needed for improving forecast quality. The most straightforward and widely used approach is to directly calibrate raw ETo forecasts constructed with the raw forecasts of input variables. However, the predi

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Salamouris, Ioannis S., and Yaz Gulnur Muradoglu. "Estimating analyst's forecast accuracy using behavioural measures (Herding) in the United Kingdom." Managerial Finance 36, no. 3 (2010): 234–56. http://dx.doi.org/10.1108/03074351011019564.

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PurposeThe purpose of this paper is to identify herding behaviour on financial markets and measure the herding behaviour impact on the accuracy of analysts' earnings forecasts.Design/methodology/approachTwo alternative measures of herding behaviour, on analysts' earnings forecasts are proposed. The first measure identifies herding as the tendency of analysts to forecast near the consensus. The second measure identifies herding as the tendency of analysts to follow the most accurate forecaster. This paper employs the method of The Generalised Method of Moments in order to relax any possible bia

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Shah, Rohan, and Phani R. Jammalamadaka. "Optimal Portfolio Strategy for Risk Management in Toll Road Forecasts and Investments." Transportation Research Record: Journal of the Transportation Research Board 2670, no. 1 (2017): 83–94. http://dx.doi.org/10.3141/2670-11.

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The study leveraged modern portfolio theory and stochastic time series models to develop a risk management strategy for future traffic projections along brownfield toll facilities. Uncertainty in future traffic forecasts may raise concerns about performance reliability and revenue potential. Historical time series traffic data from brownfield corridors were used for developing econometric forecast estimates, and Monte Carlo simulation was used to quantify a priori risks or variance to develop optimal forecasts by using mean-variance optimization strategies. Numerical analysis is presented with

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Yang, Dazhi, and Allan N. Zhang. "Impact of Information Sharing and Forecast Combination on Fast-Moving-Consumer-Goods Demand Forecast Accuracy." Information 10, no. 8 (2019): 260. http://dx.doi.org/10.3390/info10080260.

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This article empirically demonstrates the impacts of truthfully sharing forecast information and using forecast combinations in a fast-moving-consumer-goods (FMCG) supply chain. Although it is known a priori that sharing information improves the overall efficiency of a supply chain, information such as pricing or promotional strategy is often kept proprietary for competitive reasons. In this regard, it is herein shown that simply sharing the retail-level forecasts—this does not reveal the exact business strategy, due to the effect of omni-channel sales—yields nearly all the benefits of sharing

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Hudson, Debra, Andrew G. Marshall, Yonghong Yin, Oscar Alves, and Harry H. Hendon. "Improving Intraseasonal Prediction with a New Ensemble Generation Strategy." Monthly Weather Review 141, no. 12 (2013): 4429–49. http://dx.doi.org/10.1175/mwr-d-13-00059.1.

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Abstract The Australian Bureau of Meteorology has recently enhanced its capability to make coupled model forecasts of intraseasonal climate variations. The Predictive Ocean Atmosphere Model for Australia (POAMA, version 2) seasonal prediction forecast system in operations prior to March 2013, designated P2-S, was not designed for intraseasonal forecasting and has deficiencies in this regard. Most notably, the forecasts were only initialized on the 1st and 15th of each month, and the growth of the ensemble spread in the first 30 days of the forecasts was too slow to be useful on intraseasonal t

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Xin, Chunlin, Jianwen Zhang, and Ziping Wang. "Risk strategy analysis for an online rental problem of durable equipment with a transaction cost." Journal of Algorithms & Computational Technology 15 (January 2021): 174830262110084. http://dx.doi.org/10.1177/17483026211008411.

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This study introduces the second-hand market into the famous ski-rental model, presents an online rental problem of durable equipment with a transaction cost, and designs an optimal deterministic competitive strategy. The traditional competitive analysis is based on the worst-case scenario; hence, its results are too conservative. Even though investors want to manage and control their risks in reality, in some cases, they are willing to undertake higher risk to obtain greater benefits. Considering this situation, this study designs a risk strategy combining the decision makers’ risk tolerance

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Fernández-Vázquez, Esteban, Blanca Moreno, and Geoffrey J. D. Hewings. "A Data-Weighted Prior Estimator for Forecast Combination." Entropy 21, no. 4 (2019): 429. http://dx.doi.org/10.3390/e21040429.

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Forecast combination methods reduce the information in a vector of forecasts to a single combined forecast by using a set of combination weights. Although there are several methods, a typical strategy is the use of the simple arithmetic mean to obtain the combined forecast. A priori, the use of this mean could be justified when all the forecasters have had the same performance in the past or when they do not have enough information. In this paper, we explore the possibility of using entropy econometrics as a procedure for combining forecasts that allows to discriminate between bad and good for

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DellaVigna, Stefano, Nicholas Otis, and Eva Vivalt. "Forecasting the Results of Experiments: Piloting an Elicitation Strategy." AEA Papers and Proceedings 110 (May 1, 2020): 75–79. http://dx.doi.org/10.1257/pandp.20201080.

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Forecasts of experimental results can clarify the interpretation of research results, mitigate publication bias, and improve experimental designs. We collect forecasts of the results of three Registered Reports preliminarily accepted to the Journal of Development Economics, randomly varying four features: (1) small versus large reference values, (2) whether predictions are in raw units or standard deviations, (3) text-entry versus slider responses, and (4) small versus large slider bounds. Forecasts are generally robust to elicitation features, though wider slider bounds are associated with hi

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Kim, Tong Suk, Yun Keun Lee, and Jung-Soon Hyun. "An Empirical Analysis on Trading strategy of KTB and KTF Using the Two Factors CIR Term Structure Model." Journal of Derivatives and Quantitative Studies 13, no. 1 (2005): 77–97. http://dx.doi.org/10.1108/jdqs-01-2005-b0004.

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The term structure of KTB (Korea Treasury Bond) is empirically implemented and forecasted by the extended 2-factor CIR model. Pearson and Sun model. MLE is applied to estimate parameters. Using KTB prices forecasted by the model, strategies of trading and hedge between KTB, KTF (Korea Treasury Futures) are established. In this article we can see that Pearson and Sun model appropriately explains the term structure of KTB but does not fit forecasting KTB prices. However, the model well forecasts the direction of interest rate moving up or down. Through such a forecast‘ profit via trading KTB and

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Drake, Michael, Peter Joos, Joseph Pacelli, and Brady Twedt. "Analyst Forecast Bundling." Management Science 66, no. 9 (2020): 4024–46. http://dx.doi.org/10.1287/mnsc.2019.3339.

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Changing economic conditions over the past two decades have created incentives for sell-side analysts to both provide their institutional clients tiered services and to streamline their written research process. One manifestation of these changes is an increased likelihood of analysts’ issuing earnings forecasts for multiple firms on the same day. We identify this bundling property and show that bundling has increased steadily over time. We provide field evidence that the practice is a cost-saving measure, a natural by-product of analysts focusing on thematic research, and a reflection of fore

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Novak, David R., Jeff S. Waldstreicher, Daniel Keyser, and Lance F. Bosart. "A Forecast Strategy for Anticipating Cold Season Mesoscale Band Formation within Eastern U.S. Cyclones." Weather and Forecasting 21, no. 1 (2006): 3–23. http://dx.doi.org/10.1175/waf907.1.

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Abstract An ingredients-based, time- and scale-dependent forecast strategy for anticipating cold season mesoscale band formation within eastern U.S. cyclones is presented. This strategy draws on emerging conceptual models of mesoscale band development, advances in numerical weather prediction, and modern observational tools. As previous research has shown, mesoscale band development is associated with frontogenesis in the presence of weak moist symmetric stability and sufficient moisture. These three parameters—frontogenesis, weak moist symmetric stability, and moisture—are used as the ingredi

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L’Heureux, Michelle L., Michael K. Tippett, Ken Takahashi, et al. "Strength Outlooks for the El Niño–Southern Oscillation." Weather and Forecasting 34, no. 1 (2019): 165–75. http://dx.doi.org/10.1175/waf-d-18-0126.1.

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Abstract Three strategies for creating probabilistic forecast outlooks for El Niño–Southern Oscillation (ENSO) are compared. One is subjective and is currently used by the NOAA/Climate Prediction Center (CPC) to produce official ENSO outlooks. A second is purely objective and is based on the North American Multimodel Ensemble (NMME). A new third strategy is proposed in which the forecaster only provides the expected value of the Niño-3.4 index, and then categorical probabilities are objectively determined based on past skill. The new strategy results in more confident probabilities compared to

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Jan van Andel, Schalk, Roland K. Price, Arnold H. Lobbrecht, Frans van Kruiningen, and Robert Mureau. "Ensemble Precipitation and Water-Level Forecasts for Anticipatory Water-System Control." Journal of Hydrometeorology 9, no. 4 (2008): 776–88. http://dx.doi.org/10.1175/2008jhm971.1.

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Abstract A method is presented for testing weather forecast products for applications in anticipatory water-system control. The applicability of the ensemble prediction system (EPS) of the ECMWF is tested for flood control in a regional water system in the Netherlands. By performing long-term verification analyses, a full range of probability-threshold-based decision rules to apply anticipatory control actions is evaluated in terms of hits (correct alerts), missed events, and false alarms. The analysis includes forecast horizons from 3 to 9 days for extreme precipitation events and extreme wat

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Pasternack, Alexander, Jonas Bhend, Mark A. Liniger, Henning W. Rust, Wolfgang A. Müller, and Uwe Ulbrich. "Parametric decadal climate forecast recalibration (DeFoReSt 1.0)." Geoscientific Model Development 11, no. 1 (2018): 351–68. http://dx.doi.org/10.5194/gmd-11-351-2018.

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Abstract. Near-term climate predictions such as decadal climate forecasts are increasingly being used to guide adaptation measures. For near-term probabilistic predictions to be useful, systematic errors of the forecasting systems have to be corrected. While methods for the calibration of probabilistic forecasts are readily available, these have to be adapted to the specifics of decadal climate forecasts including the long time horizon of decadal climate forecasts, lead-time-dependent systematic errors (drift) and the errors in the representation of long-term changes and variability. These fea

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Schepen, Andrew, and Q. J. Wang. "Toward Accurate and Reliable Forecasts of Australian Seasonal Rainfall by Calibrating and Merging Multiple Coupled GCMs." Monthly Weather Review 141, no. 12 (2013): 4554–63. http://dx.doi.org/10.1175/mwr-d-12-00253.1.

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Abstract The majority of international climate modeling centers now produce seasonal rainfall forecasts from coupled general circulation models (GCMs). Seasonal rainfall forecasting is highly challenging, and GCM forecast accuracy is still poor for many regions and seasons. Additionally, forecast uncertainty tends to be underestimated meaning that forecast probabilities are statistically unreliable. A common strategy employed to improve the overall accuracy and reliability of GCM forecasts is to merge forecasts from multiple models into a multimodel ensemble (MME). The most widely used techniq

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Coleman, Austin, and Brian Ancell. "Toward the Improvement of High-Impact Probabilistic Forecasts with a Sensitivity-Based Convective-Scale Ensemble Subsetting Technique." Monthly Weather Review 148, no. 12 (2020): 4995–5014. http://dx.doi.org/10.1175/mwr-d-20-0043.1.

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AbstractEnsemble sensitivity analysis (ESA) is a useful and computationally inexpensive tool for analyzing how features in the flow at early forecast times affect different relevant forecast features later in the forecast. Given the frequency of observations measured between model initialization times that remain unused, ensemble sensitivity may be used to increase predictability and forecast accuracy through an objective ensemble subsetting technique. This technique identifies ensemble members with the smallest errors in regions of high sensitivity to produce a smaller, more accurate ensemble

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Qian, Wei, Craig A. Rolling, Gang Cheng, and Yuhong Yang. "On the Forecast Combination Puzzle." Econometrics 7, no. 3 (2019): 39. http://dx.doi.org/10.3390/econometrics7030039.

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It is often reported in the forecast combination literature that a simple average of candidate forecasts is more robust than sophisticated combining methods. This phenomenon is usually referred to as the “forecast combination puzzle”. Motivated by this puzzle, we explore its possible explanations, including high variance in estimating the target optimal weights (estimation error), invalid weighting formulas, and model/candidate screening before combination. We show that the existing understanding of the puzzle should be complemented by the distinction of different forecast combination scenario

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Liu, Dehong, Yucong Liang, Lili Zhang, Peter Lung, and Rizwan Ullah. "Implied volatility forecast and option trading strategy." International Review of Economics & Finance 71 (January 2021): 943–54. http://dx.doi.org/10.1016/j.iref.2020.10.023.

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Di Giuseppe, Francesca, Davide Cesari, and Giovanni Bonafé. "Soil Initialization Strategy for Use in Limited-Area Weather Prediction Systems." Monthly Weather Review 139, no. 6 (2011): 1844–60. http://dx.doi.org/10.1175/2011mwr3279.1.

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Abstract Three diverse methods of initializing soil moisture and temperature in limited-area numerical weather prediction models are compared and assessed through the use of nonstandard surface observations to identify the approach that best combines ease of implementation, improvement in forecast skill, and realistic estimations of soil parameters. The first method initializes the limited-area model soil prognostic variables by a simple interpolation from a parent global model that is used to provide the lateral boundary conditions for the forecasts, thus ensuring that the limited-area model’

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Sitanggang, Miranda Romaully Br, Arief Hidayatullah, and Murliani Murliani. "Prospek dan Strategi Pemasaran Kerupuk Itik “Mama Ami” di Desa Kota Raden Kecamatan Amuntai Tengah Kabupaten Hulu Sungai Utara." RAWA SAINS : JURNAL SAINS STIPER AMUNTAI 3, no. 1 (2013): 143–51. http://dx.doi.org/10.36589/rs.v3i1.24.

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This research aimed to selling forecast duck chip for five year later and know what is the matter with “Mama Ami’s” duck chip business in Kota Raden village with analysis the strengths, weaknesess, opportunities and threats. This is Research use case study method. The Instrument what to use research is SPSS software for forecase marketing, to make a marketing strategy researcher use IFE matric,EFE matric, IE matric. Based on the result forecast selling duck chip refer to selling increase continou. IFE matric result total score 3,134 and 2,521 for score EFE Matric. The score to those dispositio

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Baginski, Stephen P., Saverio Bozzolan, Antonio Marra, and Pietro Mazzola. "Strategy, Valuation, and Forecast Accuracy: Evidence from Italian Strategic Plan Disclosures." European Accounting Review 26, no. 2 (2016): 341–78. http://dx.doi.org/10.1080/09638180.2016.1152905.

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Williams, Daniel W., and Shayne C. Kavanagh. "Local government revenue forecasting methods: competition and comparison." Journal of Public Budgeting, Accounting & Financial Management 28, no. 4 (2016): 488–526. http://dx.doi.org/10.1108/jpbafm-28-04-2016-b004.

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This study examines forecast accuracy associated with the forecast of 55 revenue data series of 18 local governments. The last 18 months (6 quarters; or 2 years) of the data are held-out for accuracy evaluation. Results show that forecast software, damped trend methods, and simple exponential smoothing methods perform best with monthly and quarterly data; and use of monthly or quarterly data is marginally better than annualized data. For monthly data, there is no advantage to converting dollar values to real dollars before forecasting and reconverting using a forecasted index. With annual data

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Guo, Yingni, and Eran Shmaya. "Costly miscalibration." Theoretical Economics 16, no. 2 (2021): 477–506. http://dx.doi.org/10.3982/te3991.

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We consider a platform that provides probabilistic forecasts to a customer using some algorithm. We introduce a concept of miscalibration, which measures the discrepancy between the forecast and the truth. We characterize the platform's optimal equilibrium when it incurs some cost for miscalibration, and show how this equilibrium depends on the miscalibration cost: when the miscalibration cost is low, the platform uses more distant forecasts and the customer is less responsive to the platform's forecast; when the miscalibration cost is high, the platform can achieve its commitment payoff in an

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Hou, Tony Chieh-Tse, Phillip McKnight, and Charlie Weir. "Returns to buying upward revision and selling downward revision stocks." Managerial Finance 42, no. 11 (2016): 1110–24. http://dx.doi.org/10.1108/mf-10-2015-0282.

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Purpose The purpose of this paper is to investigate the role of earnings forecast revisions by equity analysts in predicting Canadian stock returns Design/methodology/approach The sample covers 420 Canadian firms over the period 1998-2009. It analyses investors’ reactions to 27,271 upward revisions and 32,005 downward revisions of analysts’ forecasts for Canadian quoted companies. To test whether analysts’ earnings forecast revisions affect stock return continuation, forecast revision portfolios similar to Jegadeesh and Titman (2001) are constructed. The paper analyses the returns gained from

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Yang, L., F. Tian, Y. Sun, X. Yuan, and H. Hu. "Attribution of hydrologic forecast uncertainty within scalable forecast windows." Hydrology and Earth System Sciences 18, no. 2 (2014): 775–86. http://dx.doi.org/10.5194/hess-18-775-2014.

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Abstract. Hindcasts based on the extended streamflow prediction (ESP) approach are carried out in a typical rainfall-dominated basin in China, aiming to examine the roles of initial conditions (IC), future atmospheric forcing (FC) and hydrologic model uncertainty (MU) in streamflow forecast skill. The combined effects of IC and FC are explored within the framework of a forecast window. By implementing virtual numerical simulations without the consideration of MU, it is found that the dominance of IC can last up to 90 days in the dry season, while its impact gives way to FC for lead times excee

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Estournel, C., F. Auclair, M. Lux, C. Nguyen, and P. Marsaleix. ""Scale oriented" embedded modeling of the North-Western Mediterranean in the frame of MFSTEP." Ocean Science 5, no. 2 (2009): 73–90. http://dx.doi.org/10.5194/os-5-73-2009.

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Abstract. An embedded forecasting system was developed for the North-Western Mediterranean at 3-km resolution. The system is based on the Symphonie hydrodynamic free surface model and on the variational initialization and forcing platform VIFOP. The regional model is initialized and forced at its open lateral boundaries by the MFS GCM and forced at the surface by the ALADIN numerical weather prediction model. Once a week, a five-day forecast is produced after a hindcast of seven days. This pre-modeling period of 7 days before beginning the forecast allows the development of the small scale fea

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Yang, Eun-Gyeong, Hyun Mee Kim, JinWoong Kim, and Jun Kyung Kay. "Effect of Observation Network Design on Meteorological Forecasts of Asian Dust Events." Monthly Weather Review 142, no. 12 (2014): 4679–95. http://dx.doi.org/10.1175/mwr-d-14-00080.1.

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Abstract To improve the prediction of Asian dust events on the Korean Peninsula, meteorological fields must be accurately predicted because dust transport models require them as input. Accurate meteorological forecasts could be obtained by integrating accurate initial conditions obtained from data assimilation processes in numerical weather prediction. In data assimilation, selecting the appropriate observation location is important to ensure that the initial conditions represent the surrounding meteorological flow. To investigate the effect of observation network configuration on meteorologic

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Nagashima, Masayasu, Frederick T. Wehrle, Laoucine Kerbache, and Marc Lassagne. "Impacts of adaptive collaboration on demand forecasting accuracy of different product categories throughout the product life cycle." Supply Chain Management: An International Journal 20, no. 4 (2015): 415–33. http://dx.doi.org/10.1108/scm-03-2014-0088.

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Purpose – This paper aims to empirically analyze how adaptive collaboration in supply chain management impacts demand forecast accuracy in short life-cycle products, depending on collaboration intensity, product life-cycle stage, retailer type and product category. Design/methodology/approach – The authors assembled a data set of forecasts and sales of 169 still-camera models, made by the same manufacturer and sold by three different retailers in France over five years. Collaboration intensity, coded by collaborative planning forecasting and replenishment level, was used to analyze the main ef

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Zhang, Xiaoxiang, Jo-Ting Wei, and Hsin-Hung Wu. "Family firm and analyst forecasts in an emerging economy." Management Decision 55, no. 9 (2017): 2018–37. http://dx.doi.org/10.1108/md-07-2016-0517.

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Purpose The purpose of this paper is to examine how family firms affect analyst forecast dispersion, accuracy and optimism and how earnings smoothness as the moderating factor, affects these relationships in an emerging market context. Design/methodology/approach This paper uses the population sample of firms listed on the Taiwan Stock Exchange from 2009 to 2010 as the research sample, which includes 963 firm-year observations. Findings The findings show that analysts following family firms are more likely to have more dispersed, less accurate and more optimism biased forecasts than those foll

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Kamalapur, Raj. "Impact of Forecast Errors in CPFR Collaboration Strategy." American Journal of Industrial and Business Management 03, no. 04 (2013): 389–94. http://dx.doi.org/10.4236/ajibm.2013.34046.

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Duca, Gheorghe, and Aurelian Gulea. "The Forecast and the Strategy of Chemistry Development." Chemistry Journal of Moldova 1, no. 1 (2006): 8–14. http://dx.doi.org/10.19261/cjm.2006.01(1).06.

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A lasting economy of the state requires continuous progress in technology based on novel scientific achievements. Science and innovation are the basic factors ensuring competitiveness of our industry and agriculture and provide for about 50-85% of economic growth. Science is the nation’s patrimony and it determines the future of the country. The objectives of Science in Moldova are: - to get new knowledge about nature and society; - to create a wide scientific-technologic basis that would ensure: (1) innovation activity in the country; (2) technology progress; (3) world competitiveness of our

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Wang, Yunheng, Jidong Gao, Patrick S. Skinner, et al. "Test of a Weather-Adaptive Dual-Resolution Hybrid Warn-on-Forecast Analysis and Forecast System for Several Severe Weather Events." Weather and Forecasting 34, no. 6 (2019): 1807–27. http://dx.doi.org/10.1175/waf-d-19-0071.1.

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Abstract A real-time, weather adaptive, dual-resolution, hybrid Warn-on-Forecast (WoF) analysis and forecast system using the WRF-ARW forecast model has been developed and implemented. The system includes two components, an ensemble analysis and forecast component, and a deterministic hybrid three-dimensional ensemble–variational (3DEnVAR) analysis and forecast component. The goal of the system is to provide on-demand, ensemble-based, and physically consistent gridded analysis and forecast products to forecasters for making warning decisions. Both components, the WRF-DART system with 36 ensemb

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Kerr, Christopher A., and Xuguang Wang. "Ensemble-Based Targeted Observation Method Applied to Radar Radial Velocity Observations on Idealized Supercell Low-Level Rotation Forecasts: A Proof of Concept." Monthly Weather Review 148, no. 3 (2020): 877–90. http://dx.doi.org/10.1175/mwr-d-19-0197.1.

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Abstract The potential future installation of a multifunction phased-array radar (MPAR) network will provide capabilities of case-specific adaptive scanning. Knowing the impacts adaptive scanning may have on short-term forecasts will influence scanning strategy decision-making in hopes to produce the most optimal ensemble forecast while also benefiting human severe weather warning decision-making. An ensemble-based targeted observation algorithm is applied to an observing system simulation experiment (OSSE) where the impacts of synthetic idealized supercell radial velocity observations are est

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Cha, Donggil. "Forecast of North Korea strategy towards South Korea following its denuclearization strategy." Journal of Korean-Japanese Military and Culture 28 (October 31, 2019): 103–31. http://dx.doi.org/10.47563/kjmc.28.4.

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Taylor, Andrew A., and Lance M. Leslie. "A Single-Station Approach to Model Output Statistics Temperature Forecast Error Assessment." Weather and Forecasting 20, no. 6 (2005): 1006–20. http://dx.doi.org/10.1175/waf893.1.

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Abstract Error characteristics of model output statistics (MOS) temperature forecasts are calculated for over 200 locations around the continental United States. The forecasts are verified on a station-by-station basis for the year 2001. Error measures used include mean algebraic error (bias), mean absolute error (MAE), relative frequency of occurrence of bias and MAE values, and the daily forecast errors themselves. A case study examining the spatial and temporal evolution of MOS errors is also presented. The error characteristics presented here, together with the case study, provide a more d

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He, Xiqiong, and Changping Yin. "The impact of strategic deviance on analysts’ earnings forecasts: evidence from China." Nankai Business Review International 10, no. 3 (2019): 362–81. http://dx.doi.org/10.1108/nbri-10-2018-0060.

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Purpose The purpose of this paper is to explore the effect of firm’s deviant strategy on analysts’ earnings forecasts and further examine the effects of firm’s information transparency and environmental uncertainty on these relationships from information asymmetry perspective. Design/methodology/approach The sample includes listed firms on Shanghai and Shenzhen Stock Exchange during the period 2007-2013. Findings The results indicate that firms’ deviant strategies have effects on analysts’ earnings forecasts, in particular, firms with extreme strategies have less analysts following, larger for

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Lewis-Beck, Michael S., and Charles Tien. "PROXY FORECASTS: A WORKING STRATEGY." PS: Political Science & Politics 46, no. 01 (2013): 39–40. http://dx.doi.org/10.1017/s1049096512001485.

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Our Proxy Model of presidential election forecasting declared, from data issued six months before the November contest, that Obama would garner 52.7% of the two-party popular vote. [See the model release in ourMonkey Cageblog-post (Lewis-Beck and Tien 2012a) on September 18, 2012, and in the October issue ofPS(Lewis-Beck and Tien 2012b).] Thus, that forecast called the correct winner, with a point estimate error of only 0.9 percentage points.

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Mittermaier, Marion P. "A Strategy for Verifying Near-Convection-Resolving Model Forecasts at Observing Sites." Weather and Forecasting 29, no. 2 (2014): 185–204. http://dx.doi.org/10.1175/waf-d-12-00075.1.

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Abstract Routine verification of deterministic numerical weather prediction (NWP) forecasts from the convection-permitting 4-km (UK4) and near-convection-resolving 1.5-km (UKV) configurations of the Met Office Unified Model (MetUM) has shown that it is hard to consistently demonstrate an improvement in skill from the higher-resolution model, even though subjective comparison suggests that it performs better. In this paper the use of conventional metrics and precise matching (through extracting the nearest grid point to an observing site) of the forecast to conventional synoptic observations in

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Materia, Stefano, Andrea Borrelli, Alessio Bellucci, et al. "Impact of Atmosphere and Land Surface Initial Conditions on Seasonal Forecasts of Global Surface Temperature." Journal of Climate 27, no. 24 (2014): 9253–71. http://dx.doi.org/10.1175/jcli-d-14-00163.1.

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Abstract The impact of land surface and atmosphere initialization on the forecast skill of a seasonal prediction system is investigated, and an effort to disentangle the role played by the individual components to the global predictability is done, via a hierarchy of seasonal forecast experiments performed under different initialization strategies. A realistic atmospheric initial state allows an improved equilibrium between the ocean and overlying atmosphere, increasing the model predictive skill in the ocean. In fact, in regions characterized by strong air–sea coupling, the atmosphere initial

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Perera, Treshani, David Higgins, and Woon-Weng Wong. "The evaluation of the Australian office market forecast accuracy." Journal of Property Investment & Finance 36, no. 3 (2018): 259–72. http://dx.doi.org/10.1108/jpif-04-2017-0029.

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Purpose Property market models have the overriding aim of predicting reasonable estimates of key dependent variables (demand, supply, rent, yield, vacancy and net absorption rate). These can be based on independent drivers of core property and economic activities. Accurate predictions can only be conducted when ample quantitative data are available with fewer uncertainties. However, a broad-fronted social, technical and ecological evolution can throw up sudden, unexpected shocks that result in the econometric outputs sceptical to unknown risk factors. Therefore, the purpose of this paper is to

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Love, Robert S. "How well do managers forecast?" European Management Journal 4, no. 3 (1986): 215–19. http://dx.doi.org/10.1016/s0263-2373(86)80044-5.

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Corradini, Riccardo. "A Set of State–Space Models at a High Disaggregation Level to Forecast Italian Industrial Production." J 2, no. 4 (2019): 508–60. http://dx.doi.org/10.3390/j2040033.

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Normally, econometric models that forecast the Italian Industrial Production Index do not exploit information already available at time t + 1 for their own main industry groupings. The new strategy proposed here uses state–space models and aggregates the estimates to obtain improved results. The performance of disaggregated models is compared at the same time with a popular benchmark model, a univariate model tailored on the whole index, with persistent not formally registered holidays, a vector autoregressive moving average model exploiting all information published on the web for main indust

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Merkova, D., I. Szunyogh, and E. Ott. "Strategies for coupling global and limited-area ensemble Kalman filter assimilation." Nonlinear Processes in Geophysics 18, no. 3 (2011): 415–30. http://dx.doi.org/10.5194/npg-18-415-2011.

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Abstract. This paper compares the forecast performance of four strategies for coupling global and limited area data assimilation: three strategies propagate information from the global to the limited area process, while the fourth strategy feeds back information from the limited area to the global process. All four strategies are formulated in the Local Ensemble Transform Kalman Filter (LETKF) framework. Numerical experiments are carried out with the model component of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) and the NCEP Regional Spectral Model (RS

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Simpson, Ludi. "National and local labour force projections for the UK." Local Economy: The Journal of the Local Economy Policy Unit 32, no. 2 (2017): 129–49. http://dx.doi.org/10.1177/0269094217694345.

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Labour force forecasts are required by local planning, legally guided in the UK by regulations on land use. Methods of forecasting the labour force, and data available for UK practice, are reviewed here. A best strategy for sub-national forecasts of the labour supply is found empirically to involve an accurate national forecast with a local starting point. Key trends are the decreasing economic activity of young adults, the increasing activity of older adults and the impact of changing state pension age. However, there exists neither an acceptable national forecast of economic activity nor a s

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A. Toimentseva, Irina, Natalia P. Karpova, Natalia G. Ostroukhova, and Vera D. Chichkina. "Problems and forecast of the development of the Russian fuel and energy complex: the factorial approach." Problems and Perspectives in Management 15, no. 2 (2017): 372–85. http://dx.doi.org/10.21511/ppm.15(2-2).2017.07.

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Existing forecasts of Russian energy sector development have a number of general provisions and differ in approaches to their construction. The most realistic forecast is made within the framework of the Energy Strategy of Russia for the period up to 2035. However, the dynamism and high uncertainty of economic processes, international relations, domestic policy and the rapid growth of scientific and technical progress need a systematic correction of any forecast. The purpose of the article is to develop theoretical provisions and practical recommendations for making a forecast for the developm

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Blanc, Sebastian M., and Thomas Setzer. "Bias–Variance Trade-Off and Shrinkage of Weights in Forecast Combination." Management Science 66, no. 12 (2020): 5720–37. http://dx.doi.org/10.1287/mnsc.2019.3476.

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Combining forecasts is an established approach for improving forecast accuracy. So-called optimal weights (OWs) estimate combination weights by minimizing errors on past forecasts. Yet the most successful and common approach ignores all training data and assigns equal weights (EWs) to forecasts. We analyze this phenomenon by relating forecast combination to statistical learning theory, which decomposes forecast errors into three components: bias, variance, and irreducible error. In this framework, EWs minimize the variance component (errors resulting from estimation uncertainty) but ignore the

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Woodford, Michael. "The Case for Forecast Targeting as a Monetary Policy Strategy." Journal of Economic Perspectives 21, no. 4 (2007): 3–24. http://dx.doi.org/10.1257/jep.21.4.3.

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At central banks around the world, including the Bank of England, Sweden's Riksbank, Norway's Norges Bank, and the Reserve Bank of New Zealand, policy is conducted on the basis of “inflation-forecast targeting”: the central bank constructs quantitative projections of the economy's expected future evolution based on the way in which it intends to control short-term interest rates, and public discussion of those projections plays a critical role in justifying the banks' conduct of monetary policy to the public. What accounts for the appeal of this approach? Should it be adopted more widely or mo

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