<abstract xmlns="http://www.w3.org/1999/xhtml">The paper presents a method of detecting atypical observations in time series with or without seasonal fluctuations. Unlike classical methods of identifying outliers and influential observations, its essence consists in examining the impact of individual observations both on the fitted values of the model and the forecasts. The exemplification of theoretical considerations is the empirical example of modelling and forecasting daily sales of liquid fuels at X gas station in the period 2012-2014. As a predictor, a classic time series model was used, in which 7-day and 12-month cycle seasonality was described using dummy variables. The data for the period from 01.01.2012 to 30.06.2014 were for the estimation period and the second half of 2014 which was the period of empirical verification of forecasts. The obtained results were compared with other classical methods used to identify influential observations and outliers, i.e. standardized residuals, Cook distances and DFFIT. The calculations were carried out in the R environment and the Statistica package.</abstract>

On the Method of Identification of Atypical Observations in Time Series

<abstract xmlns="http://www.w3.org/1999/xhtml">The problem of small area prediction is considered under a Linear Mixed Model. The article presents a proposal of an empirical best linear unbiased predictor under a model with two correlated random effects. The main aim of the simulation analyses is a study of an influence of the occurrence of a correlation between random effects on properties of the predictor. In the article, an increase of the accuracy due to the correlation between random effects and an influence of model misspecification in cases of the lack of correlation between random effects are analyzed. The problem of the estimation of the Mean Squared Error of the proposed predictor is also considered. The Monte Carlo simulation analyses and the application were prepared in R language.</abstract>

On Empirical Best Linear Unbiased Predictor Under a Linear Mixed Model with Correlated Random Effects

<abstract xmlns="http://www.w3.org/1999/xhtml">The purpose of the article is to assess selected large cities in Poland as senior-friendly. Using the municipal population forecast for 2017-2030 published in 2017, together with the available database, own analyses were made for selected cities in Poland. Additionally for the description of ‘senior-friendly’ cities, it was assumed that the starting point is the WHO definition, which indicated four main criteria determining whether a given city can be considered to be friendly to the elderly. In a city friendly to seniors, the principles, services, environment and structures built up support the active ageing process and avail it for the residents. For the purposes of the research, taking into account the above objectives and based on published sources, a descriptive model was created. The study assessed selected Polish cities as senior-friendly cities, using the robust taxonomic approach.</abstract>

Seniors in Cities and Senior-Friendly Cities Analysis for Selected Polish Cities – Robust Taxonomic Approach

<abstract xmlns="http://www.w3.org/1999/xhtml">The quarterly unemployment rate from the Labour Force Survey covering Poland’s data from the first quarter 2005 to the third quarter 2019 was investigated. The issue was to reveal its stochastic structure as a trend, seasonality and disturbance and to make a prognosis. The analysed data comes from a survey based on rotational design, so the problem of possibly autocorrelated survey errors was taken into consideration. Following Harvey (2000), Pfeffermann, Feder, and Signorelli (1997), Yu and Mantel (1997) and Bell and Carolan (1998) it seemed to be of great importance to include the proper autocorrelation structure of the errors into a statistical treatment. It appeared that for Polish unemployment data that structure was not as it could have been expected. After the model was fitted to the data, a conclusion about the specificity of the unemployment rate with respect to gender was drawn. Unemployment forecast until 2020:Q4 is provided.</abstract>

A Few Remarks on the Stochastic Structure of the Unemployment Rate in Poland by Gender

<abstract xmlns="http://www.w3.org/1999/xhtml">This paper reviews the binomial and trinomial option pricing models and their convergence to the Black-Scholes model result. These models are generalized for the European and American options. The trinomial models are said to be more accurate than the binomial when fewer steps are modelled. These models are widely used for the usual vanilla option types, European or American options, that respectively can be exercised only at the expiration date and at any time before the expiration date. The results are supportive of the conventional wisdom that trinomial option pricing models such as the Kamrad-Ritchken model and the Boyle model are converging faster than the binomial models. When binomial models are compared in terms of convergence, the most efficient model is the Jarrow-Rudd model. This paper concludes that improved binomial models such as the Haahtela model are converging faster to the BS model result. After some trials, binomial distribution follows log-normal distribution assumed by the Black-Scholes model.</abstract>

A Review of the Binomial and Trinomial Models for Option Pricing and their Convergence to the Black-Scholes Model Determined Option Prices

<abstract xmlns="http://www.w3.org/1999/xhtml">The purpose of this paper is to attempt to classify risk which can be observed when one deals with data from the metals market. Usually the general definition of risk includes two dimensions. The first one is the probability of occurrence and the second one are the associated consequences of a set of hazardous scenarios. In this research the authors try to add a new dimension: the source of risk, which can be defined in terms of the level of turnover (volatility of volume) and price (volatility of returns). One can categorize risks in terms of multidimensional ranking based on a comparative evaluation of the consequences, probability, and source of a given risk. Another dimension is the chosen risk measures, in the meaning of the risk model. In risk analysis, some selected quantile risk measures were proposed: VaR, Expected Shortfall, Median Shortfall and GlueVaR. The empirical part presents a multidimensional risk analysis of the metal market.</abstract>

Risk Management on the Metals Market

AHEAD OF PRINT

Volume 27 (2023): Issue 4 (December 2023)

Volume 27 (2023): Issue 3 (September 2023)

Volume 27 (2023): Issue 2 (June 2023)

Volume 27 (2023): Issue 1 (March 2023)

Volume 26 (2022): Issue 4 (December 2022)

Volume 26 (2022): Issue 3 (September 2022)

Volume 26 (2022): Issue 2 (June 2022)

Volume 26 (2022): Issue 1 (March 2022)

Volume 25 (2021): Issue 4 (December 2021)

Volume 25 (2021): Issue 3 (September 2021)

Volume 25 (2021): Issue 2 (June 2021)

Volume 25 (2021): Issue 1 (March 2021)

Volume 24 (2020): Issue 4 (December 2020)

Volume 24 (2020): Issue 3 (September 2020)

Volume 24 (2020): Issue 2 (June 2020)

Volume 24 (2020): Issue 1 (March 2020)

Volume 23 (2019): Issue 4 (December 2019)

Volume 23 (2019): Issue 3 (September 2019)

Volume 23 (2019): Issue 2 (June 2019)

Volume 23 (2019): Issue 1 (March 2019)

Volume 22 (2018): Issue 4 (December 2018)

Volume 22 (2018): Issue 3 (September 2018)

Volume 22 (2018): Issue 2 (June 2018)

Volume 22 (2018): Issue 1 (March 2018)

Econometrics

 The Econometrics journal has been published continuously since 1998. Starting from the first issue, Józef Dziechciarz has been an Editor-in-Chief of the journal. Until 2011, the journal was issued in the series of Academic Research Papers at the Wrocław University of Economics as Econometrics. Applications of quantitative methods. Since 2009, four issues have been published annually. It enables the introduction of regular quarterly release cycle. The Econometrics is published in English. The Scientific Council of our journal also includes professors affiliated with foreign institutions. The list of scientific reviewers includes eminent scientists from both home and abroad. Among the authors of the publications are both scientists from Polish academia, as well as many scientists from foreign universities. High level of scientific works, our confidence and insightful comments from reviewers contribute to the publication of valuable articles and dissemination of national scientific achievements. Until the end of 2017, fifty eight issues of the journal were published.  The subject area of the published articles covers theoretical and practical aspects of the methods of econometrics, statistics and mathematics. The domain of applications of these methods covers wider economic issues, including macro and microeconomic analyses; statistical and econometric analysis and modeling market data, as well as capital investment and insurance problems. Social and demographic analyses cover the issues of education, employment and unemployment, poverty, etc. Many studies have cyclical character, published articles show long-term results of research, include a scientific discussion with the reviewers suggestions formulated on the basis of earlier works. This allows to track the progress of scientific research, and the publications appearing in the Econometrics journal are an inspiration to undertake new research challenges.  econometrics.ue.wroc.pl/　   The Econometrics journal is indexed in Google Scholar and details on the citations can be found on Google Scholar Citations.  Also find us at:   Index Copernicus  Erih Plus    Why subscribe and read The Econometrics is a scientific journal that promotes both theoretical aspects of mathematical, statistical and econometric methods as well as application possibilities. It focuses on the presentation of new and modernization of well-known methods as well as their adaptation in economy, business processes and social sciences in a very broad meaning. Due to the fast publishing production, the presented articles refer to the latest research, papers are always up-to-date, original, scientific, never printed before in other scientific journals. The Econometrics is the place of interdisciplinary debate with the participation of economists and statisticians.  Why submit The journal offers a fast, honest and constructive review, carried out in the double blind review process. After acceptance, an article is evaluated by a native speaker and a statistics editor. After acceptance, the publication process is very fast.The Econometrics journal belongs to the group of magazines that are constantly highly rated and enjoy a good reputation among authors and reviewers.  Rejection Rate   32%   Archiving  Sciendo archives the contents of this journal in Portico - digital long-term preservation service of scholarly books, journals and collections.  Plagiarism Policy  The editorial board is participating in a growing community of Similarity Check System's users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process. 