89 research outputs found
Rule Based Forecasting [RBF] - Improving Efficacy of Judgmental Forecasts Using Simplified Expert Rules
Rule-based Forecasting (RBF) has emerged to be an effective forecasting model compared to well-accepted benchmarks. However, the original RBF model, introduced in1992, incorporates 99 production rules and is, therefore, difficult to apply judgmentally. In this research study, we present a core rule-set from RBF that can be used to inform both judgmental forecasting practice and pedagogy. The simplified rule-set, called coreRBF, is validated by asking forecasters to judgmentally apply the rules to time series forecasting tasks. Results demonstrate that forecasting accuracy from judgmental use of coreRBF is not statistically different from that reported from similar applications of RBF. Further, we benchmarked these coreRBF forecasts against forecasts from (a) untrained forecasters, (b) an expert system based on RBF, and (c) the original 1992 RBF study. Forecast accuracies were in the hypothesized direction, arguing for the generalizability and validity of the coreRBF rules
Development and Validation of a Rule-based Time Series Complexity Scoring Technique to Support Design of Adaptive Forecasting DSS
Evidence from forecasting research gives reason to believe that understanding time series complexity can enable design of adaptive forecasting decision support systems (FDSSs) to positively support forecasting behaviors and accuracy of outcomes. Yet, such FDSS design capabilities have not been formally explored because there exists no systematic approach to identifying series complexity. This study describes the development and validation of a rule-based complexity scoring technique (CST) that generates a complexity score for time series using 12 rules that rely on 14 features of series. The rule-based schema was developed on 74 series and validated on 52 holdback series using well-accepted forecasting methods as benchmarks. A supporting experimental validation was conducted with 14 participants who generated 336 structured judgmental forecasts for sets of series classified as simple or complex by the CST. Benchmark comparisons validated the CST by confirming, as hypothesized, that forecasting accuracy was lower for series scored by the technique as complex when compared to the accuracy of those scored as simple. 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. The framework is founded on the concepts of restrictiveness and guidance and offers specific recommendations on how these elements can be built in FDSS to support complexity
Return Postage in Mail Surveys: A Meta Analysis
This paper describes a five-step procedure for meta-analysis. Especially important was the contacting of authors of prior papers. This was done primarily to improve the accuracy of the coding; it also helped to identify unpublished research and to supply missing information. Application of the five-step procedure to the issue of return postage in mail surveys yielded significantly more papers and produced more definitive conclusions than those derived from traditional reviews. This meta-analysis indicated that business reply postage is seldom costeffective because first class postage yields an additional 9% return. Business reply rates were lower than for other first class postage in each of the 20 comparisons.surveys, meta-analysis, return postage
A Behavioural Finance Explanation of a Gearing-ß Inverse Association Referencing Weill’s Liquidity Result (in English)
The authors investigated Arnold’s conjecture that Leverage (Financial Gearing) and Operating Gearing should be positively related to the equity ß of the Sharpe/Lintner CAPM. They find for a sample of the S&P 500 firms that have been on that index continuously for more than 15 years, that ß is negatively associated with Leverage and Operating Gearing. Using Weill’s results for transitional economies, the authors suggest that liquidity may provide an explanation for this anomalous ß-Gearing inversion. The implications are: that (1) one should revaluate the positive associations posited for Financial and Operating gearing with ß and (2) consider the possibility of managing liquidity as a way to affect ß.financial gearing; leverage; liquidity; beta
Replication and Extension of a Forecasting Decision Support System: An Empirical Examination of the Time Series Complexity Scoring Technique
This study presents a conceptual replication of Adya and Lusk’s (2016) forecasting decision support system (FDSS) that identifies the complexity or simplicity of a time series. Prior studies in forecasting have argued convincingly that the design of FDSS should incorporate the complexity of the forecasting task. Yet, there existed no formal way of determining time series complexity until this FDSS, referred to as the Complexity Scoring Technique (CST). 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. The CST was originally validated using statistical forecasts of a small set of 54 time series as well as judgmental forecasts from 14 representative participants to confirm that the FDSS successfully distinguished Simple series from Complex ones. In this study, we (a) replicate the CST on a much larger set of data from both statistical and judgmental forecasting methods, and (b) extend and validate the series classification categories from the binary Simple-Complex used in the original CST to Very Simple, Simple, Complex, and Very Complex thus adding an ordinal link between the two previous binary designations. Findings suggest that both the replication and extension of the CST further validate it, thereby greatly enhancing its use in the practice of forecasting. Implications for research and practice are discussed
Designing Effective Forecasting Decision Support Systems: Aligning Task Complexity and Technology Support
The Horlas: Maupassant\u27s Mirror of Self-Reflection
In their co-authored paper, The Horlas: Maupassant\u27s Mirror of Self-Reflection, Edward J. Lusk and Marion Roeske present a comparative analysis of three works of Maupassant: Lettre d\u27un fou, Le Horla of 1886, and Le Horla of 1887. The authors argue that these works form a trilogy by which Maupassant expresses his struggle to resolve the issues that seem to haunt him during the time that he pens the Horla trilogy. This introspective search is crafted around the failure of a mirror to provide a reflected image and the assessment of the likelihood that the strange events presented in the trilogy are caused either by hallucinations or by a menacing force called Le Horla. Further, to understand the way that Maupassant has developed the story lines as his mirror of self-reflection, Lusk and Roeske examine, in detail, four aspects of Maupassant\u27s life that provide the context for the Horlas: his struggle with syphilis, the relationship he has with Flaubert, the novel of his maternal uncle Alfred Le Poittevin called Une Promenade de BĂ©lial and finally, the intense personal relationship of Flaubert and Alfred Le Poittevin
Profiles of stress: An empirical comparison of employee stress factor differences in Germany and the US
According to The HR Magazine (May, 2006 p. 14), "Today, American workers are saying that they are accomplishing less than they did a decade ago and are feeling more rushed on the job". This is the point of departure for our study. Using a questionnaire based upon the work of Geert Hofstede, we surveyed employees of a MNC headquartered in Germany with branches in the US. We create three stress groupings: High, Middle and Low based upon selected variables meas-ured on Likert-type scales, e.g., How often do you feel nervous or tense at work? We examine these stress groups on a variety of variables to develop profiles of these three groups. The dataset with 1,300 observations on more than 75 variables provides a rich rendering of the profiles both overall and by country. For example, we find for both the German and US respondents that more stress is associated with less satisfaction in particular respecting Fringe Benefits and Having Challenging Work. And the German employees, who were classified as exhibiting high levels of stress, are less satisfied with Fringe Benefits than their US counterparts
Analytical Procedures Phase of PCAOB Audits: A Note of Caution in Selecting the Forecasting Model
The best-practices execution of PCAOB audits requires the use of Analytical Procedures at the Planning and the Substantive Phases. This often finds the auditor using the standard OLS two-parameter linear regression forecasting model [OLSR] to project account-values from the Planning Phase to balances expected at Year-End so as to effect a variance analysis at the Substantive Phase. This is the point of departure of our study. We examine the practical effect of using the OLSR model in a time-series context of the audit. Specifically, this research report provides information on the use of the OLSR model as the model of choice in the audit context compared to the ARIMA(0,2,2)/Holt model which is usually the standard choice for an exponential smoothing model in the presence of autocorrelation of data in the time-stream; autocorrelation is the usual case for longitudinal series taken in the audit. Results: We find that there are reasons to condition the selection of the forecasting model in the Analytical Procedures context based upon autocorrelation in the data-stream. When the time-stream of data exhibits autocorrelation the OLSR model fails in a statistically significant manner to capture the next or one-period ahead client value at the same rate as does the ARIMA/Holt model. This then has implications for the False Negative Investigation Error
Commentary on the Makridakis Time Series Competition (M-Competition)
In 1982, the Journal of Forecasting published the results of a forecasting competition organized by Spyros Makridakis (Makridakis et al., 1982). In this, the ex ante forecast errors of 21 methods were compared for forecasts of a variety of economic time series, generally using 1001 time series. Only extrapolative methods were used, as no data were available on causal variables. The accuracies of methods were compared using a variety of accuracy measures for different types of data and for varying forecast horizons. The original paper did not contain much interpretation or discussion. Partly this was by design, to be unbiased in the presentation. A more important factor, however, was the difficulty in gaining consensus on interpretation and presentation among the diverse group of authors, many of whom have a vested interest in certain methods. In the belief that this study was of major importance, we decided to obtain a more complete discussion of the results. We do not believe that “the data speak for themselves.
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