Search results - CEJSH

1

Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions

100%

Szubzda F., Chlebus M.

Central European Economic Journal

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2019

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vol. 6

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issue 53

EN

The aim of the presented study was to assess the quality of VaR forecasts in various states of the economic situation. Two approaches based on the extreme value theory were compared: Block Maxima and the Peaks Over Threshold. Forecasts were made on the daily closing prices of 10 major indices in European countries, divided into two groups: emerging countries (Bulgaria, Czech Republic, Lithuania, Latvia, Poland, Slovakia and Hungary) and developed countries (England, France and Germany). Three states of economic situation were analysed: the pre-crisis (2007), the crisis (2008) and the post-crisis (2009) period as out-of-sample. The main conclusion obtained is the too slow process of adapting static EVT-based forecasts to market movements. While in the pre-crisis period the results were satisfactory, in the period of crisis VaR forecasts were too often exceeded.

2

Różniczkowy model inflacji rejestrowanej w Polsce

100%

Kisielińska J.

Metody Ilościowe w Badaniach Ekonomicznych

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2010

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vol. 11

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issue 2

151-160

PL

W artykule przedstawiono addytywny model z amplitudą oscylacji zmieniającą się według dowolnej funkcji czasu. Wykazano, że stanowi on uogólnienie zwykłego modelu addytywnego i multiplikatywnego. Jeśli założona zostanie wykładnicza postać amplitudy i oscylacje w postaci pojedynczej harmoniki szeregu Fouriera, można wyznaczyć współczynniki równania różniczkowego drgań harmonicznych tłumionych opisującego proces. Model zastosowano dla inflacji rejestrowanej od stycznia 1991 do grudnia 2009.

EN

In the article is shown additive model with amplitude of oscillation changing in any function of time. It was proven that this model is generalization of the ordinary additive and multiplicative models. Establishment of the amplitude as an exponential function and oscillations as single harmonics of Fourier’s series will let to write the inflation variability as a homogeneous second order differential equation with damping factor (equation of harmonic vibration damping). The model was used for monthly inflation from January 1991 to December 2009.

3

Verifying the Performance of Multiple Linear Regression in Predicting the Indicator of Mass Accumulation of Waste. The Case of Lubelskie Voivodship

100%

Szul T., Nęcka K.

Barometr Regionalny. Analizy i prognozy

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2016

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issue 1(43)

151-158

EN

In this study, the effectiveness of classical regression models to forecast the indicator of mass accumulation of waste was investigated. The economic and infrastructural variables were used as explanatory variables. The conducted studies show that applying regression models can produce forecasting models generating errors at an acceptable level although only for the municipalities of urban and urban-rural administrative type. For the models where the following were selected as explanatory variables: income indicator, mean number of persons living in a residential building, proportion of arable land in the structure of land use, percentage of buildings in the municipality covered by the waste collection scheme, and the functional type of municipality, the error in the forecast obtained for the test set amounted to 12%–14%. Using the same set of explanatory variables for the rural municipalities caused the models to display forecasting errors for the test set ranging from 35% to 50%. Also, applying another combination of input variables gathered in the course of the studies did not result in developing models of better quality. Therefore, further studies are necessary in the search for more effective methods or other variables describing the mass waste accumulation indicator in rural municipalities.

PL

W pracy badano przydatność klasycznych modeli regresyjnych do prognozowania wskaźnika nagromadzenia odpadów. Jako zmienne objaśniające wykorzystano wskaźniki ekonomiczne i infrastrukturalne. Z wykonanych badań wynika, że stosując modele regresyjne można opracować modele prognostyczne generujące błąd na akceptowalnym poziomie ale tylko dla gmin o typie administracyjnym miejskim i miejsko-wiejskim. Dla modeli, w których zmiennymi objaśniającymi były wskaźnik dochodu, średnią ilość osób zamieszkujących budynek mieszkalny, udział użytków rolnych w strukturze użytkowania, procent budynków w gminie objętych systemem zbiórki oraz typ funkcjonalny gminy uzyskano błąd prognozy dla zbioru testowego na poziomie 12–14%. Wykorzystanie tego samego zestawu zmiennych objaśniających dla gmin wiejskich spowodowało, że opracowane modele miały błąd prognozy dla zbioru testowego na poziomie 35–50%. Również wykorzystanie innej kombinacji zmiennych wejściowych zgromadzonych w trakcie badań nie umożliwiło opracowanie modelu lepszej jakości. Konieczne są więc dalsze badania w kierunku poszukiwania efektywniejszych metod lub innych zmiennych opisujących wskaźnik masowego nagromadzenia odpadów na terenach gmin wiejskich.

4

Wavelet-based forecasting of ARIMA time series - an empirical comparison of different methods

100%

Schlüter S., Deuschle C.

Managerial Economics

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2014

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vol. 15

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issue 1

107-131

EN

By means of wavelet transform, an ARIMA time series can be split into different frequency components. In doing so, one is able to identify relevant patters within this time series, and there are different ways to utilize this feature to improve existing time series forecasting methods. However, despite a considerable amount of literature on the topic, there is hardly any work that compares the different wavelet-based methods with each other. In this paper, we try to close this gap. We test various wavelet-based methods on four data sets, each with its own characteristics. Eventually, we come to the conclusion that using wavelets does improve forecasting quality, especially for time horizons longer than one-day-ahead. However, there is no single superior method: either wavelet-based denoising or wavelet-based time series decomposition is best. Performance depends on the data set as well as the forecasting time horizon.

5

Wykorzystanie modelu PCM w prognozowaniu potencjału zawodowego kandydatów do pracy

100%

Zięba A.

Econometrics. Ekonometria. Advances in Applied Data Analytics

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2014

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issue 4(46)

43-51

EN

The issue of career potential is currently very popular. Experience and potential − that is what the most of employers are looking for. Employers are wondering whether the candidate has the potential to take on a new challenge training. The article attempts to bring the issue to measure the career potential. It presents the most common tools used by employers in the recruitment process and the most common mistakes committed by them. In the next part PCM model is shown, which can be a helpful tool in recruitment procedures − a tool used to assess the potential of training.

6

Application of adaptive methods in demographic variables forecasting

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Sojka E.

Econometrics. Ekonometria. Advances in Applied Data Analytics

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2015

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issue 3 (49)

55-65

EN

The research paper is focused on the assessment of the usefulness of adaptive methods in forecasting demographic variables. The goal of the paper is to conduct the retro and prospective analysis of selected demographic values in the sphere of changes in time, and also to indicate an efficient method for the forecasting of the studied values in subsequent periods. The time series for Poland for the period between 2000 and 2013 are the basis for the development of the forecast. Mean squared errors of ex post forecasts are used as forecast quality measures. The results of the study show that among the applied methods of forecasting, the method of creeping trend with harmonic weights is the most suitable as it gives the smallest forecast errors.

7

Analysis of demand in steel and iron industry – latent variables model

100%

Barska M.

Przegląd Statystyczny

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2019

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vol. 66

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issue 4

247-269

EN

Demand in the steel and iron industry is influenced by multiple factors. Not all of them can be identified and measured. The paper presents the results of the analysis of the levels of demand achieved by a selected enterprise from this sector in the years 2010–2014. The aim of the study is to build a hidden Markov model which would reflect the turning points of this demand, thus making it possible to forecast its future levels. The model’s forecasting properties and stability have been examined. A simulation has been carried out that involved generating a high number of series for selected model parameters and checking their properties. This demonstrated that a three-state second order hidden Markov model was most relevant to the purpose of the study. Thanks to the model’s application, it was possible to describe states which could potentially shape the demand. Moreover, taking the transition state into consideration allowed spotting the signal about the upcoming replacement of the growth phase with the decline phase, and vice versa. The presented second order hidden Markov model can serve as an alternative to the traditional methods of the analysis of time series. The forecast generated by the model informs about the shaping of a trend in demand and serves as an indication of the shifts in economic cycles.

8

Forecasting staffing decisions

100%

Wiśniewski J. W.

Econometrics. Ekonometria. Advances in Applied Data Analytics

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2013

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issue 1(39)

22-29

EN

The purpose of this paper is to present tools to support personnel decisions in the company. The starting point is to measure the results of the work of employees in a given position. Combining the appropriate amount of information on the results of work in the past, a variety of workers and their important personal qualities will enable the construction of an econometric model. This model describes the mechanism of the effects of variation of operations, depending on the various characteristics of the employees. With such a model one can estimate the prediction effectiveness of individual candidates when the position becomes vacant. This may facilitate the selection of a suitable candidate from among many. This candidate has the greatest potential for productivity. The choice of such candidate is weighted with the lowest risk of erroneous personnel decisions.

9

Artificial Intelligence Methods in Spare Parts Demand Forecasting

100%

Rosienkiewicz M.

Logistics and Transport

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2013

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vol. 18

41-50

EN

The paper discusses the problem of forecasting lumpy demand which is typical for spare parts. Several prediction methods are presented in the article – traditional techniques based on time series and advanced methods that use Artificial Intelligence tools. The research conducted in the paper focuses on comparison of eight forecasting methods, including classical, hybrid and based on artificial neural networks. The aim of the paper is to assess the efficiency of lumpy demand forecasting methods that apply AI tools. The assessment is conducted by a comparison with traditional methods and it is based on Root Mean Square Errors (RMSE) and relative forecast errors (ex post) values. The article presents also a new approach to the lumpy demand forecasting issue – a method which combines regression modelling, information criteria and artificial neural networks.

10

Assessment of Composite Leading Indicators Usefulness in Forecasting Loans and Deposits Cyclical Fluctuations

100%

Garczarczyk J., Skikiewicz R.

Prace i Materiały Instytutu Rozwoju Gospodarczego SGH

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2011

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vol. 86:Business Surveys, Business Cycles. Polish Contribution to the 30th CIRET Conference

135-160

EN

The article has been focused on the application of the business cycle barometers for predicting the cyclical fluctuations of the two main categories in the banking market in Poland - PLN loans and PLN deposits. The barometers built for the first time for the Polish banking sector are based on sets of indicators, including both quantitative variables (official statistics data) and qualitative (among others derived from the business tendency survey conducted in the banking sector). Among the components of barometers both macro-economic indicators for the whole economy, as well as the variables from the financial sector and other sectors (including industry and trade) were used. The main aim of the article has been an evaluation of the characteristics of various types of composite leading indicators constructed on the basis of differentiated sets of variables. Then an attempt to construct three types of barometers: with the short, medium and long lead was made. In addition, the best composite leading indicators for each reference variable - PLN loans and PLN deposits were chosen.

11

Corporate Model of the Algerian National Marble Company

100%

Nibouche F., Belmokhtar O.

Folia Oeconomica Stetinensia

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2009

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vol. 8

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issue 1

19-48

EN

In today's dynamic and competitive environment, planning for effective use of the company resources requires an analytical and integrated approach of its essential functions. With such goal in mind, the corporate planning model, in which the modules of production and marketing are related to the financial module, presents a very efficient solution. It is particularly well suited for the needs of Algerian companies operating in an environment that has undergone a transformation from planned economy to market economy where risks and uncertainties are ubiquitous. Furthermore, Algerian companies should take account of the importance of strategic planning and forecasting where, in that context, the corporate planning model provides a powerful tool for decision-making. This work provides a corporate planning model specified for the Algerian National Marble Company. The presented model has been devised and validated from the company data to generate physical and financial short-term forecasts. The obtained empirical results show the usefulness of such a model for the managers in terms of providing a precise model of the essential functions of the company, helping to evaluate the consequences of different management scenarios and assisting in the decision-making process. Furthermore, using prospective simulations, the presented model can be used as a tool for forecasting.

12

100%

Kaczmarzyk J.

FINANSE Czasopismo Komitetu Nauk o Finansach PAN

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2018

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issue 1(11)

140-150

EN

The aim of the paper is to point out that the Monte Carlo simulation is an easy and flexible approach when it comes to forecasting risk of an asset portfolio. The case study presented in the paper illustrates the problem of forecasting risk arising from a portfolio of receivables denominated in different foreign currencies. Such a problem seems to be close to the real issue for enterprises offering products or services on several foreign markets. The changes in exchange rates are usually not normally distributed and, moreover, they are always interdependent. As shown in the paper, the Monte Carlo simulation allows for forecasting market risk under such circumstances.

18

Heurystyki w prognozowaniu w przedsiębiorstwie

100%

Dittmann I.

Econometrics. Ekonometria. Advances in Applied Data Analytics

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2014

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issue 4(46)

98-107

EN

Forecasts built for the needs of the enterprise may be inaccurate. Actual forecast errors (errors ex post) may be greater than the user-defined acceptable prediction errors. One reason for this may be the impact of psychological factors on the forecaster (eg. emotions) and the application of heuristics (usually unconsciously). The purpose of this article was, first, to draw attention to the issue of the possibility of various kinds of heuristics during the construction of forecasts in the company and second to indicate the possibility of eliminating the adverse effects of heuristics on the course and outcome of the forecasting process.

19

Forecasting by econometric models as support to management

100%

Seregelj T. D.

Perspectives of Innovations, Economics and Business

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2011

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vol. 7

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issue 1

72-76

EN

In the contemporary environment characterized by the dynamic structure of factors and the unpredictability of the relations existing between them, the central problem is the selection of strategic goals. Forecasting is the necessary precursor to the planning process and includes research into the future course of events. Numerous methods and techniques of forecasting are used nowadays. Econometric models can be used successfully for predicting the future development of a phenomenon, and thereby facilitate the choice of strategic goals.

20

Macroeconomic forecasting in Poland: The role of forecasting competitions

100%

Rybacki J.

Central European Economic Journal

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2020

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vol. 7

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issue 54

EN

Macroeconomic forecasters are often believed to idealistically work on improving the accuracy of their estimates based on for example the Root Mean Squared Error (RMSE). Unfortunately, reality is far more complex. Forecasters are not awarded equally for each of their estimates. They have their targets of acquiring publicity or to earn prestige. This article aims to study the results of Parkiet's competitions of macroeconomic forecasting during 2015–2019. Based on a logit model, we analyse whether more accurate forecasting of some selected macroeconomic variables (e.g. inflation) increases the chances of winning the competition by a greater degree comparing to the others. Our research shows that among macroeconomic variables three groups have a significant impact on the final score: inflation (CPI and core inflation), the labour market (employment in the enterprise sector and unemployment rate) and financial market indicators (EUR/PLN and 10-year government bond yields). Each group is characterised by a low disagreement between forecasters. In the case of inflation, we found evidence that some forecasters put a greater effort to score the top place. There is no evidence that forecasters are trying to somehow exploit the contest.

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