Rolling Forecast Research Articles

A New Long-Term Forecast Method of Wind Power

We forecast wind power in a way combining wavelet neutral network and rolling forecast. At the same time, we build a system of forecast deviation. Then we use some data to test our model, which yields a desirable result. In addition, we are informed that our method can predict wind power correctly in a long time and short sampling interval can lead to a better result than long sampling interval.

Wind Power Forecasting Based on Improved Biased Wavelet Neural Network

Wind power prediction is the key to grid-connected wind power system. In this paper, first of all, we decompose and reconstruct the power sequence by wavelet analysis, and reduce the noise of the detail signal, to obtain the strong-regularity subsequence. We adapt the biased wavelet neural network rolling forecast model for the processed sequence to obtain seven days of rolling forecast results through several amendments. For the sequence of 5 minutes interval the prediction accuracy is 98.63%, for the sequence of 15 minutes interval the prediction accuracy is 99.88%.

Study on the Prediction of Rolling Force of 16MnR Hot Rolled Plate

Considering the insufficient recrystallization of austenite has an effect on deformation resistance, meanwhile, referring to the plate of controlling parameters in the hot rolling process, analysis and forecast of load parameters of rolling mill and motor per pass of its rolling process. The result shows that: The production of modern steel rolling, involved in the process, equipment problems associated with rolling load, must be taken into account in its internal organization of metal in the deformation process. The less recrystallization is, the greater the deviation of the calculated results. This should be distinguished from the traditional concept of rolling.

Using diffusion models to forecast market size in emerging markets with applications to the Chinese car market

Marketing managers have to forecast the market size and this forecast guides strategic decisions whether to continue exporting, open new factories or expand existing production operations. Forecasting sales and the market size is a challenging task; even more so in emerging markets where data is limited and the market demand is changeable. This research proposes a novel approach that applies diffusion models using car ownership data to forecast car sales. Car ownership data may be easier to access than sales data in emerging markets but marketing managers are more interested in the sales forecast. Researchers propose using diffusion models to forecast the adoption of new products or products which are new to consumers in a market. This research demonstrates that marketing managers can use diffusion models to predict car sales in China where cars are new products to most consumers in this market. Since the majority of car buyers in China are first time buyers, car manufacturers and retailers must also forecast when the market composition will change. This effectively means predicting when first time car buying will start to slow down and repeat/replacement purchase or second hand car purchase will become more important. To forecast both sales and market composition change, marketing managers must choose a robust model. Managers want insights from models that have been tested robustly especially in less stable market conditions. In this context, this study illustrates the value of using a rolling forecast instead of a fixed horizon approach when comparing and choosing which model to use to forecast both sales and market composition change for the Chinese car market.

Good Bye Traditional Budgeting, Hello Rolling Forecast: Has The Time Come?

This paper argues for a new approach to accounting textbook budgeting material. The business environment is not stable. Change is continuous, for large and small business alike. A business must act and react to generate shareholder value. The rolling forecast provides the necessary navigational insight. The traditional annual static budget does not. Managing a business, looking inwards and backwards and making decisions to hit the annual budget target no longer serves management in generating shareholder value. In most situations this approach to company management only leads to compromised performance. Leadership may not reach long-term shareholder wealth potential in using the traditional annual budget as a command and control device. Our research shows companies are moving to a rolling forecast as a management navigational tool. Leadership uses the forecast to navigate continuous change in creating shareholder value. This paper demonstrates how to build leadership concepts that go along with the rolling forecast, as well as the rolling forecast process itself into the classroom and accounting textbook material. Accounting and graduate business students need this type of education to help lead and increase a business’ chances of success.

Differential Autoregressive of Cycle Prediction Model and its Application

AR model is widely used which based on stationary time series used for short-term prediction. However, in fact the time series we got is often non-stationary, and there is little literature researching the smooth processing, modeling and forecasting and then restoring the results in system. In view of this, this paper provides a method, that is, differential autoregressive of cycle prediction. First, explain the basic principles and give the calculation steps of smooth processing, modeling and forecasting and restoring the results. Then, applied the prediction method in the short-term forecast of coal arrive of a provincial. Model implementation is based on java programming. We get high prediction accuracy, the system easily integrated, can be widely used, and can achieve rolling forecast.

Beyond performance management: why, when, and how to use 40 tools and best practices for superior business performance

There's a bewildering array of management tools out there. And they all promise to help you excel at the toughest parts of your job: defining your organization's strategic direction, managing customers and costs, and boosting workforce performance. But just 30 percent of these tools deliver as intended. Why? As Jeremy Hope and Steve Player reveal in Beyond Performance Management, while many tools are sound in theory, they're misused by most organizations. For example, executives buy and implement a tool without first asking, What problem are we trying to solve? And they use tools to command and control frontline teams, not empower them--a serious and costly mistake. In this eminently useful, clear-eyed book, the authors critically review dozens of well-known management tools--from mission statements, balanced scorecards, and rolling forecasts to key performance indicators, Six Sigma, and performance appraisals. They explain how to select the right tools for your organization, how to implement them correctly, and how to extract maximum value from each. Brimming with rigorous analysis and solid advice, Beyond Performance Management helps you swiftly gauge the value of each management tool, as well as navigate the increasingly crowded field of offerings--so the tools you select deliver fully on their promise.

Antecedents for defining management control system design: empirical evidence from Brazilian firms

This work analyzes the development profile of Brazilian firms regarding management accounting attributes. Much has been written in recent years about the design of management control systems and the use of management control artifacts, but there is a relevant antecedent that has been little explored, namely the profile of these attributes, involving aspects such as scope, timeliness, integration and aggregation (Chenhall & Morris, 1986; Silvola, 2008). These attributes define, limit and expand the power for management control to act (Berry, Broadbent & Otley, 2005) and they are interdependent, since each influences the others. They are the basis on which the organization’s management model is structured and developed. Within the universe of a firm’s management control, there are various artifacts that are implemented with the aim of providing support to managers’ decision-making process, besides coordination and influence on the employees (Anthony & Govindarajan, 2002; Hansen & Mouritsen, 2007). Among the existing artifacts cited in the literature as relevant for the planning and control process are strategic planning, budgeting, capital budgeting, profitability analysis, rolling forecasting and real options. In a changing environment, the attributes can change in terms of form and amplitude, demand and utilization, implying the need for integrated and proactive review and adjustment. The impact of the adequacy of these attributes on the design and use of management control systems is so relevant that they can distort and impair this design and use. To address the theme within a consistent theoretical framework, the idea of attribute in this article is based on some classic works (Chenhall & Morris, 1986; Silvola, 2008). This is a descriptive study, developed from an exploratory perspective, looking ahead to more comprehensive development in the future, given the absence of analogous works on Brazilian firms. The study was carried out through a survey of a sample composed of 125 Brazilian firms, with the data gathered by a structured questionnaire administered over the Internet. The data were analyzed by partial least squares path modeling (PLS-PM). The results suggest that the attributes examined are related in different ways, depending on the profile of the organization’s scope, influencing the existence of some management accounting artifacts, which should be taken into account in defining or updating the management information system. In short, if a firm wants to use artifacts for management control, it should review the structuring of its attributes.

Replacing the Annual Budget with Business Intelligence Driver-Based Forecasts

The fixed annual budget process can be a cumbersome and static process, often failing to deliver intended benefits. Typically detached from business operations and strategic planning goals, the annual budget suffers from inherent weaknesses caused by a lack of business intelligence regarding its underlying assumptions. This weakness is well documented in existing literature and there is ample evidence of improved alternatives to static corporate financial planning. One such alternative utilizes business intelligence as an essential component in the annual budget process, along with rolling forecasts as a critical tool. Utilizing business intelligence supported, driver-based rolling forecasting can align an organization’s budget process with strategic objectives and can further the operational and financial strength of an organization, as well as maximize shareholder value. In order to fully explore this topic, this article will present a review of the conventional annual budget process and the manner in which an approach that bases financial forecasts on business intelligence drivers can align operations with strategic objectives and add value to an organization. An assessment of intelligence-supported, driver-based rolling forecasting will also be presented, demonstrating an im- proved approach to the traditional annual budgeting process.

The investor sentiment endurance index and its forecasting ability

Based on a binomial probability distribution model, this paper creates an investor sentiment endurance index which estimates the probability that the high or low stock market price equals the closing price of a trading session. Results of this study indicate that the index has decent forecasting ability. The overall accuracy of eight-quarter rolling forecasts reaches 44.15%. Therefore, the true forecasting model and accuracy ratio developed in this study provide financial professionals with additional analytical tools.

Coordinated capacity migration and expansion planning for semiconductor manufacturing under demand uncertainties

Semiconductor industry is very capital intensive in which capacity utilization significantly affect the capital effectiveness and profitability of semiconductor manufacturing companies. Due to constant technology advance driven by Moore's Law in semiconductor industry, multiple production technologies generally co-exist in a wafer fabrication facility with utilization of a pool of common tools for multiple technologies and critical tools dedicated for a specific technology. Because part of the equipment is common for products of different technologies, production managers have limited flexibility to dynamically allocate the capacity among the technologies via capacity migration. The possibility of capacity migration and interrelationship among different technologies make capacity planning difficult under demand and product-mix uncertainties. This paper aims to develop a dynamic optimization method that captures the unique characteristics of rolling demand forecast mechanism to solve capacity expansion and migration planning problems in semiconductor industry. In semiconductor industry, demand forecasts are rolling and updated when the latest market and demand information is available. This demand forecast mechanism makes forecast errors in different time periods correlated. We estimate the validity and robustness of the proposed dynamic optimization method in an empirical study in a semiconductor manufacturing company in Taiwan. The results showed practical viability of this approach and the findings can provide useful guidelines for capacity planning process under rolling forecast mechanism.

The Information Content of the ISM Purchasing Managers’ Survey

The Institute for Supply Management indexes are often assumed to be good predictors of future manufacturing and non-manufacturing activity. I use a simple forecasting equation to create ex ante rolling forecasts of a variety of official data that might be predicted using the ISM information during the past 10 years. Adding ISM measures to these forecasting equations typically improves forecasts by 10% or less. A similar forecasting exercise shows somewhat better results for the 1960s and 1970s. Examining the ISM measures around NBER business cycle turning points suggests that the ISM does not provide much information about turning points. The poor performance of the ISM may result from mismeasurement, and/or from parameter instability. While more information about the state of the economy is always better, analysts of the business cycle should realize that the ISM surveys do not supersede or fully anticipate more comprehensive official data.

On ordering adjustment policy under rolling forecast in supply chain planning

Rolling forecast is a useful tool for lowering total cost with regard to practical inventory management. The details regarding a rolling forecast are obtained from a customer’s projected ordering data. The customer estimation of a rolling forecast may deviate from actual orders because of unstable conditions or customer’s deliberation. This study investigates what measures a customer might apply in responding to a situation where the rolling forecast deviates from the actual order. In addition, an appropriate ordering adjustment policy is proposed for better monitoring the supply chain performance with regard to a variant level of error concerning rolling forecast data. This study also considers the influence of lead time and inventory cost structure. We adopted a simulation approach, employing a model developed and examined in several different settings. The proposed ordering adjustment policies are determined by AVG, SD, and RMSE calculated from differences existing between historical forecasts and realized data. Levels of estimate error and estimate bias in a rolling forecast are included in the experimental procedure. Results reveal that the RMSE ordering adjustment policy is the most effective in situations of normal and downside estimation bias, whereas the AVG policy is more appropriate in the case of upside estimation bias. The level of estimation error is irrelevant to the selection of ordering adjustment policies, but it is positively associated with inventory costs. Stock-out costs and lead time are positively associated with inventory costs. Accuracy of the rolling forecast is therefore deemed to be essential in a situation involving a long lead time with high stock-out costs.

The Execution Premium: Linking Strategy to Operations for Competitive Advantage

In a world of stiffening competition, business strategy is more crucial than ever. Yet most organizations struggle in this area--not with formulating strategy but with executing it, or putting their strategy into action. Owing to execution failures, companies realize just a fraction of the financial performance promised in their strategic plans. It doesn't have to be that way, maintain Robert Kaplan and David Norton in The Execution Premium. Building on their breakthrough works on strategy-focused organizations, the authors describe a multistage system that enables you to gain measurable benefits from your carefully formulated business strategy. This book shows you how to: Develop an effective strategy--with tools such as SWOT analysis, vision formulation, and strategic change agendas Plan execution of the strategy--through portfolios of strategic initiatives linked to strategy maps and Balanced Scorecards Put your strategy into action--by integrating operational tools such as process dashboards, rolling forecasts, and activity-based costing Test and update your strategy--using carefully designed management meetings to review operational and strategic data Drawing on extensive research and detailed case studies from a broad array of industries, The Execution Premium presents a systematic and proven framework for achieving the financial results promised by your strategy.

A Theoretical Analysis of the Impact of Adopting Rolling Budgets, Activity-Based Budgeting and Beyond Budgeting

Budgeting accomplishes many goals in an organization and evaluating the potential impact of a change is difficult. I investigate the organization-wide effects of three distinct budgeting alternatives (rolling budgets, activity-based budgeting and beyond budgeting) using a model that incorporates three important budgeting functions: forecasting, operational planning and performance evaluation. From the perspective of the whole organization, each budgeting alternative improves profits. I then examine the department preferences for each alternative when each function is under the control of a different department and each department has its own, department-specific performance metric. Forecasting is judged on the variance of the base demand forecast, operational planning on the expected unit capacity costs and performance evaluation on the salesperson's expected action. In my model all departments always favor rolling forecasts, while only one department always favors beyond budgeting (or activity-based budgeting). For beyond budgeting and activity-based budgeting, the preferences of the two other departments vary depending upon the model parameters.

An exploratory study of operational reasons to budget

AbstractBudgets are used widely but criticized, mainly for performance evaluation reasons. We find that organizations regard budgets as more important for planning and control than evaluation, thus proposing a rationale for their continued use irrespective of evaluation‐based criticisms. This finding is also important, because most extant budget research focuses on evaluation, suggesting a potential disconnect between budget research and practice. We also find that rolling forecasts are used in tandem with the annual budget in most organizations, and for the same reasons. This was unexpected, as coexistence suggests their adoption for different reasons.

IMPROVING FORECAST ACCURACY BY COMBINING RECURSIVE AND ROLLING FORECASTS*

This article presents analytical, Monte Carlo, and empirical evidence on combining recursive and rolling forecasts when linear predictive models are subject to structural change. Using a characterization of the bias–variance trade‐off faced when choosing between either the recursive and rolling schemes or a scalar convex combination of the two, we derive optimal observation windows and combining weights designed to minimize mean square forecast error. Monte Carlo experiments and several empirical examples indicate that combination can often provide improvements in forecast accuracy relative to forecasts made using the recursive scheme or the rolling scheme with a fixed window width.

Empirical analysis and forecasting of volatility dynamics in high-frequency returns with time-varying components

We study intraday return volatility dynamics using a time-varying components approach, and the method is applied to analyze IBM intraday returns. Empirical evidence indicates that with three additive components—a time-varying mean of absolute returns and two cosine components with time-varying amplitudes—together they capture very well the pronounced periodicity and persistence behaviors exhibited in the empirical autocorrelation pattern of IBM returns. We find that the long-run volatility persistence is driven predominantly by daily level shifts in mean absolute returns. After adjusting for these intradaily components, the filtered returns behave much like a Gaussian noise, suggesting that the three-components structure is adequately specified. Furthermore, a new volatility measure (TCV) can be constructed from these components. Results from extensive out-of-sample rolling forecast experiments suggest that TCV fares well in predicting future volatility against alternative methods, including GARCH model, realized volatility and realized absolute value. Copyright © 2009 John Wiley & Sons, Ltd.

SHOULD OIL PRICES RECEIVE SO MUCH ATTENTION? AN EVALUATION OF THE PREDICTIVE POWER OF OIL PRICES FOR THE U.S. ECONOMY

This paper evaluates the potential gains from using oil prices to forecast a variety of measures of inflation, economic activity, and monetary policy–related variables. With a few exceptions, oil prices do not have any predictive content for these variables. This finding is robust to the use of rolling forecast windows, the use of industry‐level data, changes in the forecast horizon, and allowing for nonlinearities. (JEL Q43, E37, C32)

Schneider Electric Argentina: Beyond Budgeting

Nowadays, Schneider Electric is the world leader of electrical distribution, industrial control, and automation - at both product and service levels. Worldwide, Schneider consists of 105.000 employees in 190 countries, 25 research and development centers, 207 production plants, 60 logistic centers, 15.000 sales outlets and consolidated revenues of euro 14 billion. In 2003, Schneider Electric Argentina ceased to use the budget as a control tool - a cornerstone foreseen in the Managerial Performance Project (MAP). This Project promoted by headquarters and implemented in the whole company, implied the joint use of three tools: rolling forecast, consolidated accounting and balanced scorecard instead of the traditional budgeting and local profitability concepts. Three years later, it is time to make a management balance and questions about advantages and future fears arose. The case allows deepening into advantages and problems appeared when implemented a model aligned to the Beyond Budgeting concept. The discussion lets know the alternative model to the traditional budget considering problems and advantages; analyze the existent alignment between compensation, control and performance measurement systems; deal the issue of slacks creation and think about the impact generated by variable and fix compensations. To write this case was used information provided by the company and interviews to leading actors of the case.