The recent financial crisis has seen huge swings in corporate bond spreads. It is analyzed what quality VAR-based forecasts would have had prior and during the crisis period. Given that forecasts of the mean of interest rates or financial market prices are subject to large uncertainty independent of the class of models used, major emphasis is put on the quality of measures of forecast uncertainty. The VAR considered is based on a model first suggested in the literature in 2005. In a rolling window analysis, both the model’s forecasts and joint prediction bands are calculated making use of recently proposed methods. Besides a traditional analysis of the forecast quality, the performance of the proposed prediction bands is assessed. It is shown that the actual coverage of joint prediction bands is superior to the coverage of naïve prediction bands constructed pointwise.
On 7 April 1968 the Club of Rome was established. In 1972 D.H. Meadows, D.L. Meadows, J. Randers and W.W. Behrens published The Limits to Growth as the first report to the Club of Rome – describing various scenarios for world development to 2100. Since that time the Club of Rome has developed in the world wide apolitical movement.
The essay presents an original application of using the coolhunting method to discover new trends in architecture and design. The ability to identify trends is tied in with the possibility of attaining an advantage over the competition with the use of new designs that can become hits on the market, gaining the favor of customers. The term coolhunting can be broadly defined as the pursuit of inspiration and the forecasting of the directions of development. Initially, the term was applied to fashion, but quickly spread to other spheres of activity, like music, the arts, lifestyle and finally, to architecture and design. The essay is a slightly altered and improved rendition of the author's article published in Zastosowania ergonomii. Wybrane kierunki badań ergonomicznych w roku 2014 . (ed. Charytonowicz J.), Publ. Polskie Towarzystwo Ergonomiczne PTErg, o/Wrocław, 2014, p. 289-304. The method outlined therein is the result of research conducted under the author's supervision at the Institute of Architecture and Spatial Planning of the Poznań University of Technology between the years 2012 and 2014.
In economics we often face a system which intrinsically imposes a structure of hierarchy of its components, i.e., in modeling trade accounts related to foreign exchange or in optimization of regional air protection policy. A problem of reconciliation of forecasts obtained on different levels of hierarchy has been addressed in the statistical and econometric literature many times and concerns bringing together forecasts obtained independently at different levels of hierarchy. This paper deals with this issue with regard to a hierarchical functional time series. We present and critically discuss a state of art and indicate opportunities of an application of these methods to a certain environment protection problem. We critically compare the best predictor known from the literature with our own original proposal. Within the paper we study a macromodel describing the day and night air pollution in Silesia region divided into five subregions.
While personality is strongly related to experienced emotions, few studies examined the role of personality traits on affective forecasting. In the present study, we investigated the relationships between extraversion and neuroticism personality traits and affective predictions about academic performance. Participants were asked to predict their emotional reactions two months before they will get their results for one important exam. At the same time, personality was assessed with the Big Five Inventory. All the participants were contacted by a text message eight hours after that the results were available, and they were requested to rate their experienced affective state. Results show moderate negative correlations between neuroticism and both predicted and experienced feelings, and that extraversion exhibits a weak positive correlation with predicted feelings, but not with experienced feelings. Taken together, these findings confirm that extraversion and neuroticism shape emotional forecasts, and suggest that affective forecasting interventions based on personality could probably enhance their efficiencies.
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.
Changes in capacity of water reservoir Cedzyna during its exploitation since 1972 till 2003 are presented in the paper. Analyses were based on cross sections of the reservoir’s basin from before its fulfillment (1967) and those measured with the echo sounder Ceeducer in 2003. Silting of reser-voir was predicted based on empirical methods. The volume of reservoir was found to decrease by 112.8 thousand m3 during 31 years of its exploitation and reservoir’s life span was assessed at 685 years. An error analysis was additionally made of calculating the surface area of a cross section at varying number of sounding sites. It was found that there was no need to note too many coordinates and depths and for the Cedzyna reservoir the distance between measurement sites up to 16 m was sufficient.
Covering a wide area by a large number of WiFi networks is anticipated to become very popular with Internet-of-things (IoT) and initiatives such as smart cities. Such network configuration is normally realized through deploying a large number of access points (APs) with overlapped coverage. However, the imbalanced traffic load distribution among different APs affects the energy consumption of a WiFi device if it is associated to a loaded AP. This research work aims at predicting the communication-related energy that shall be consumed by a WiFi device if it transferred some amount of data through a certain selected AP. In this paper, a forecast of the energy consumption is proposed to be obtained using an algorithm that is supported by a mathematical model. Consequently, the proposed algorithm can automatically select the best WiFi network (best AP) that the WiFi device can connect to in order to minimize energy consumption. The proposed algorithm is experimentally validated in a realistic lab setting. The observed performance indicates that the algorithm can provide an accurate forecast to the energy that shall be consumed by a WiFi transceiver in sending some amount of data via a specific AP.
Weather forecasting requires knowledge of the laws of atmospheric movement. Apart from classic fluid mechanics, we must consider the rotational motion of our planet, the differential heating of its surface through the absorption of solar radiation, as well as water evaporation and condensation processes.
In the article, mathematical modeling methods are used to study the main trends and macroeconomic determinants of the electric car market development in 2011–2018 on the example of the US. The determinants include economic (GDP), socio-economic (household income), energy (electricity use), and environmental (СО2 emissions) factors. The authors justify the role of electric transport in strengthening national energy security due to the transition to renewable energy technologies and the reduction of fossil fuel use. Based on the constructed linear regression equations, a weak relationship has been revealed between the number of electric vehicles sold and the environmental factor, which can be explained by the small share of electric cars in the US market. The formed multifactor linear model showed a positive impact of both the country’s GDP growth and electricity consumption increase on the number of electric vehicles sold. However, the rise in household incomes negatively influences market development due to insufficient consumer awareness of the electric transport operation benefits, an underdeveloped network of electric vehicle charging stations, etc. Based on the obtained multifactor model, the authors have built optimistic, optimal and pessimistic scenarios for the US electric vehicle market deployment for the next five years. In order to implement the most favorable scenarios, recommendations for market development factors’ management have been made. The results of the study can be used to improve public policy in the US transport and energy sectors, as well as in other countries to optimize the fuel and energy balance, strengthen the energy independence of states by developing clean transport and adapting the model to national specifics.
Coal production in 2018 increased by 3.3% and amounted to 7.81 million tons. Compared to 2010, it increased by 620 million tons. The structure of coal production in the world is very stable in the analyzed period of 2010–2018. Steam coal dominates in production with a share of 77%. Since 1990, the share of coal in the consumption of primary energy carriers has fallen by 3% in the global economy. In the EU, the share of coal in the consumption of primary energy carriers is more than twice lower than in the world, and in 2018 amounted to 13%. BP estimates the sufficiency of coal proven reserves based on 2018 data for the next 132 years. For oil and gas, they are estimated at 51 years. The decline in hard coal production in the European U nion can be dated almost continuously since 1990, which has decreased by 74%. In 2018, 74 million tons of coal were produced in the EU. In 2018, hard coal consumption in EU countries dropped to 226 million tons, i.e. by 20.6%.
In 2018, global trade in steam coal amounted to 1.14 billion tons. The situation in China is crucial for the international coal market. The slight change in the import policy of this country significantly affects the situation in international trade in steam coal. In 2019, coal prices (at Newcastle, Richards Bay, ARA ports) dropped by an average of 23 U SD/ton. The average decreases for these three indices were 33%. The prices of steam coal in the forecasts presented in the paper are under pressure of the falling demand.
The methane hazard is one of the most dangerous phenomena in hard coal mining. In a certain range of concentrations, methane is flammable and explosive. Therefore, in order to maintain the continuity of the production process and the safety of work for the crew, various measures are taken to prevent these concentration levels from being exceeded. A significant role in this process is played by the forecasting of methane concentrations in mine headings. This very problem has been the focus of the present article. Based on discrete measurements of methane concentration in mine headings and ventilation parameters, the distribution of methane concentration levels in these headings was forecasted. This process was performed on the basis of model-based tests using the Computational Fluid Dynamics (CFD). The methodology adopted was used to develop a structural model of the region under analysis, for which boundary conditions were adopted on the basis of the measurements results in real-world conditions. The analyses conducted helped to specify the distributions of methane concentrations in the region at hand and determine the anticipated future values of these concentrations. The results obtained from model-based tests were compared with the results of the measurements in realworld conditions. The methodology using the CFD and the results of the tests offer extensive possibilities of their application for effective diagnosis and forecasting of the methane hazard in mine headings.