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Book part
Publication date: 26 April 2014

Petri Kuosmanen and Juuso Vataja

This paper examines the predictive content of financial variables above and beyond past GDP growth in a small open economy in the Eurozone. We aim to clarify potential…

Abstract

Purpose

This paper examines the predictive content of financial variables above and beyond past GDP growth in a small open economy in the Eurozone. We aim to clarify potential differences in forecasting economic activity during periods of steady growth and economic turbulence.

Design/methodology/approach

The out-of-sample forecasting analysis is conducted recursively for two different time periods: the steady growth period from 2004:1 to 2007:4 and the financial crisis period from 2008:1 to 2011:2.

Findings

Our results from Finland suggest that the proper choice of forecasting variables relates to general economic conditions. During steady economic growth, the preferable financial indicator is the short-term interest rate combined with past growth. However, during economic turbulence, the traditional term spread and stock returns are more important in forecasting GDP growth.

Research limitations/implications

The results highlight the importance of long-term interest rates in determining the level of the term spread when the central bank implements a zero interest rate policy. Moreover, during economic turbulence, stock markets are able to signal the expected effects of unconventional monetary policy on GDP growth.

Details

Macroeconomic Analysis and International Finance
Type: Book
ISBN: 978-1-78350-756-6

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Article
Publication date: 18 September 2017

Jari Huikku, Timo Hyvönen and Janne Järvinen

The purpose of this paper is to investigate the initiation of accounting information system projects. Specifically, it examines the role of the predictive analytics (PA…

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1064

Abstract

Purpose

The purpose of this paper is to investigate the initiation of accounting information system projects. Specifically, it examines the role of the predictive analytics (PA) project initiator in the integration of financial and operational sales forecasts.

Design/methodology/approach

The study uses a field study method to address the studied phenomenon in eight Finnish companies that have recently adopted PA systems. The data are primarily based on 19 interviews in the companies and five interviews with the PA consultants.

Findings

The authors found that initiators appear to play a major role regarding the degree of integration of financial and operational sales forecasts. The initiators from an accounting function have a tendency to pay more attention to the integration than the representatives from other functions, such as operations and sales.

Practical implications

The study also makes a practical contribution to companies in showing and discussing the important role of the accounting department as an initiator of a project if the target is to achieve a tight coupling of financial and operational forecast figures, i.e., “one set of numbers”.

Originality/value

Even though companies have increasingly adopted PA systems in recent years, we still know little about how the initiation affects the design of accounting information systems overall. The central contribution of the paper, therefore, is to show that if a PA project is initiated by the accounting department, data integration becomes more likely. It contributes also to the discussion related to the appropriateness of data integration in the context of forecasting.

Details

Baltic Journal of Management, vol. 12 no. 4
Type: Research Article
ISSN: 1746-5265

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Article
Publication date: 1 April 2006

Richard Barrett and Jeremy Hope

More frequent re‐forecasting is becoming an important topic on corporate agendas and is seen by many to be the only way to keep financial performance on track at a time

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1327

Abstract

Purpose

More frequent re‐forecasting is becoming an important topic on corporate agendas and is seen by many to be the only way to keep financial performance on track at a time when revenues are becoming less predictable. The paper aims to investigate this topic.

Design/methodology/approach

For the past four years ALG Software has commissioned a study of the re‐forecasting practices in a sample of the top organisations in the UK by revenue. The objective of the study is to benchmark how frequently the UK's leading organisations currently re‐forecast and what their goals are for the future.

Findings

The results show that the majority of organisations remain dissatisfied with the frequency with which they re‐forecast and wish to re‐forecast more frequently. However, the findings also show that many organisations feel that they cannot re‐forecast as often or as quickly as they would like. In fact, evidence suggests that little, if any, progress has been made during the last four years since this survey was first commissioned. This is due to either the amount of time it takes operational line managers to re‐forecast their resource requirements, or the amount of time it takes the finance function to complete a round of re‐forecasting. The type of application used for budgeting and re‐forecasting appears to make little difference to the time it takes organisations to produce an annual budget or complete a re‐forecast. Central to this issue is the use of non‐financial or “operational” data that predicts future resource requirements, and the limitations of the budgeting systems that organisations currently employ. Regardless of the type of application used for budgeting or re‐forecasting, much of this modelling is still done off‐line on spreadsheets.

Originality/value

The paper is of value to finance managers considering choosing a new budgeting application who will need to ensure that the type of operational modelling of non‐financial driver data, currently done offline on spreadsheets by line managers, can be seamlessly integrated into the central budgeting model.

Details

Measuring Business Excellence, vol. 10 no. 2
Type: Research Article
ISSN: 1368-3047

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Article
Publication date: 1 March 1995

Avi Rushinek and Sara F. Rushinek

Presents a case study demonstrating financial statement ratioanalysis (FSRA). This analysis matches company to industry data andbuilds sales forecasting models. FSRA…

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9200

Abstract

Presents a case study demonstrating financial statement ratio analysis (FSRA). This analysis matches company to industry data and builds sales forecasting models. FSRA imputes forecast standards of sales and costs, and applies them to a budgeted financial statement variance analysis for the EE (electronic and electrical) industry. Develops the concept of industry base standards, integrating them into the more traditional statistical and accounting concepts of quality control standards. Provides an implementation example, and reviews possible improvements to the current methodology and approach. Uses a similar methodology to forecast the stock market value with some exceptions. Models sales and costs of an individual company and an industry based largely on aggregate industry databases. For this purpose, uses a multivariate linear trend regression analysis for the sales forecasting model. Defines and tests related hypotheses and evaluates their significance and confidence levels. For an illustration uses the EE industry and the APM company. Also demonstrates a microcomputer‐based FSRA software that speeds, facilitates, and helps to accomplish the stated objectives. The FSRA software uses industry financial statement databases, computes financial ratios and builds forecasting models.

Details

Managerial Auditing Journal, vol. 10 no. 2
Type: Research Article
ISSN: 0268-6902

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Article
Publication date: 24 August 2021

N. Prabakaran, Rajasekaran Palaniappan, R. Kannadasan, Satya Vinay Dudi and V. Sasidhar

We propose a Machine Learning (ML) approach that will be trained from the available financial data and is able to gain the trends over the data and then uses the acquired…

Abstract

Purpose

We propose a Machine Learning (ML) approach that will be trained from the available financial data and is able to gain the trends over the data and then uses the acquired knowledge for a more accurate forecasting of financial series. This work will provide a more precise results when weighed up to aged financial series forecasting algorithms. The LSTM Classic will be used to forecast the momentum of the Financial Series Index and also applied to its commodities. The network will be trained and evaluated for accuracy with various sizes of data sets, i.e. weekly historical data of MCX, GOLD, COPPER and the results will be calculated.

Design/methodology/approach

Desirable LSTM model for script price forecasting from the perspective of minimizing MSE. The approach which we have followed is shown below. (1) Acquire the Dataset. (2) Define your training and testing columns in the dataset. (3) Transform the input value using scalar. (4) Define the custom loss function. (5) Build and Compile the model. (6) Visualise the improvements in results.

Findings

Financial series is one of the very aged techniques where a commerce person would commerce financial scripts, make business and earn some wealth from these companies that vend a part of their business on trading manifesto. Forecasting financial script prices is complex tasks that consider extensive human–computer interaction. Due to the correlated nature of financial series prices, conventional batch processing methods like an artificial neural network, convolutional neural network, cannot be utilised efficiently for financial market analysis. We propose an online learning algorithm that utilises an upgraded of recurrent neural networks called long short-term memory Classic (LSTM). The LSTM Classic is quite different from normal LSTM as it has customised loss function in it. This LSTM Classic avoids long-term dependence on its metrics issues because of its unique internal storage unit structure, and it helps forecast financial time series. Financial Series Index is the combination of various commodities (time series). This makes Financial Index more reliable than the financial time series as it does not show a drastic change in its value even some of its commodities are affected. This work will provide a more precise results when weighed up to aged financial series forecasting algorithms.

Originality/value

We had built the customised loss function model by using LSTM scheme and have experimented on MCX index and as well as on its commodities and improvements in results are calculated for every epoch that we run for the whole rows present in the dataset. For every epoch we can visualise the improvements in loss. One more improvement that can be done to our model that the relationship between price difference and directional loss is specific to other financial scripts. Deep evaluations can be done to identify the best combination of these for a particular stock to obtain better results.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 14 no. 4
Type: Research Article
ISSN: 1756-378X

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Book part
Publication date: 17 November 2010

Kalyan S. Pasupathy

The article is a description of the real-life experience based on the implementation of a financial forecasting model to inform budgeting and strategic planning. The…

Abstract

The article is a description of the real-life experience based on the implementation of a financial forecasting model to inform budgeting and strategic planning. The organization is a charity-based health system that has hospitals and medical centers that provide care to the community. The health system performs a central budgeting process which is typically based on aggregation of individual budgets from the various hospitals and medical centers within the system. All financial data are reported to a central financial information system. Traditionally budgeting was done based on prior year's financial performance with a slight adjustment based on the hospital or medical center finance department's educated guess. This article describes the new forecasting method instituted to predict revenue and expenses, and to improve the budget planning process. Finally, the forecasts from the model are compared with real data to demonstrate accuracy of the financial forecasts. The model is since then being used in the budgeting process.

Details

Advances in Business and Management Forecasting
Type: Book
ISBN: 978-0-85724-201-3

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Book part
Publication date: 30 November 2011

Massimo Guidolin

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of…

Abstract

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

Details

Missing Data Methods: Time-Series Methods and Applications
Type: Book
ISBN: 978-1-78052-526-6

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Article
Publication date: 1 February 1987

Charles Brandon, Jeffrey E. Jarrett and Saleha B. Khumawala

Earnings forecasts provide useful numerical information concerning the expectations of a firm's future prospects and indicate management's ability to anticipate a firm's…

Abstract

Earnings forecasts provide useful numerical information concerning the expectations of a firm's future prospects and indicate management's ability to anticipate a firm's changing internal structure and external environment. The reasons for studying the accuracy of earnings forecasts is due to the Securities and Exchange Commission's position on financial forecasts and the issuance of a Statement of Position by the AICPA. These statements are important since they, in part, have motivated researchers to the importance of forecasting financial information. Consequently, if the disclosure of earnings forecasts in financial reports is permissable, the improvement of financial forecasts should be one of the primary concerns of the AICPA, the SEC, and numerous other interested groups.

Details

Managerial Finance, vol. 13 no. 2
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 1 March 1995

John D. Wong

Fiscal stress has forced local governments to pay increasing attention to revenue trends and has increased the importance of financial forecasting in local government…

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157

Abstract

Fiscal stress has forced local governments to pay increasing attention to revenue trends and has increased the importance of financial forecasting in local government. After reviewing the role of revenue forecasting in financial planning and discussing the use of regression and econometric analysis in revenue forecasting, this article applies this technique to forecast several key revenue components in a medium-sized city. Three general conclusions may be drawn: (1) systematic revenue forecasting and long-range planning are necessities, not luxuries, (2) risk aversion to "technical" revenue forecasting can be overcome, and (3) the implementation of a systematic revenue forecasting system does not require a battery of "rocket scientists." As municipal revenue bases come to rely less on relatively stable property taxes and more on less stable sources such as sales taxes, fees, and charges, the use of a regression and econometric based model should prove increasingly fruitful.

Details

Journal of Public Budgeting, Accounting & Financial Management, vol. 7 no. 3
Type: Research Article
ISSN: 1096-3367

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Article
Publication date: 1 February 1987

Jeffrey E. Jarrett and Saleha B. Khumuwala

Earnings forecasts provide useful numerical information concerning the expectations of a firm's future prospects and indicate management's ability to anticipate a firms…

Abstract

Earnings forecasts provide useful numerical information concerning the expectations of a firm's future prospects and indicate management's ability to anticipate a firms changing internal structure and external environment. The accuracy of these earnings forecasts that has been given so much attention is due to the S.E.C.'s position on financial forecasts and the issuance of the Statement of Position by the AICPA. These statements are important since they, in part, have motivated researchers to the importance of forecasting financial information. Consequently, if the disclosure of earnings forecasts in financial reports is permissable, the improvement of financial forecasts should be one of the primary concerns of the AICPA, the SEC, and numerous other interested groups.

Details

Managerial Finance, vol. 13 no. 2
Type: Research Article
ISSN: 0307-4358

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