scholarly journals Modeling Multivalued Dynamic Series of Financial Indexes on the Basis of Minimax Approximation

Energies ◽  
2022 ◽  
Vol 15 (1) ◽  
pp. 366
Author(s):  
Zahid Mamedov ◽  
Irina Vygodchikova ◽  
Ayaz Aliev ◽  
Lira Gurieva ◽  
Natalia Rud

In this article, the problem of modeling a time series using the Minimax method is considered. The expediency of using Minimax to identify points of change in trends and the range of changes in the graphical figures of technical analysis is justified. Spline approximation of the dynamic process with range constraints was performed to improve the quality of the model. Investors are advised to refrain from making hasty decisions in favor of holding reliable shares (such as PJSC Novatek shares), rather than selling them. The purchase of new shares should be carefully analyzed. Through an approximation of the dynamic number of the applicable optimization problem of minimizing the maximum Hausdorff distances between the ranges of the dynamic series and the values of the approximating function, the applied approach can provide reliable justification for signals to buy shares. Energy policy occupies the highest place in the list of progress ratings according to news analytics of businesses related to the energy sector of the economy. At the same time, statistical indicators and technologies of expert developments in this field, including intellectual analysis, can become an important basis for the development of a robotic knowledge program in the field under study, an organic addition to which is the authors’ methodology of development in energy economics as in energy policy. This paper examines the model of approximation of the multivalued time series of PJSC Novatek, represented as a series of ranges of numerical values of the indicators of financial markets, with constraints on the approximating function. The authors consider it advisable for promising companies to apply this approach for successful long-term investment.

2011 ◽  
Vol 28 (7) ◽  
pp. 891-906 ◽  
Author(s):  
H. E. van Piggelen ◽  
T. Brandsma ◽  
H. Manders ◽  
J. F. Lichtenauer

Abstract A method has been developed that largely automates the labor-intensive extraction work for large amounts of rainfall strip charts and paper rolls. The method consists of the following five basic steps: 1) scanning the charts and rolls to high-resolution digital images, 2) manually and visually registering relevant meta information from charts and rolls and preprocessing rolls to locate day transitions, 3) applying automatic curve extraction software in a batch process to determine the coordinates of cumulative rainfall lines on the images, 4) postprocessing the curves that were not correctly determined in step 3, and 5) aggregating the cumulative rainfall in pixel coordinates to the desired time resolution. The core of the method is in step 3. Here a color detection procedure is introduced that automatically separates the background of the charts and rolls from the grid and subsequently the rainfall curve. The rainfall curve is detected by minimization of a cost function. In total, 321 station years of locations in the Netherlands have successfully been digitized and transformed to long-term rainfall time series with 5-min resolution. In about 30% of the cases, semiautomatic postprocessing of the results was needed using a purpose-built graphical interface application. This percentage, however, strongly depends on the quality of the recorded curves and the charts and rolls. Although developed for rainfall, the method can be applied to other elements as well.


Author(s):  
Giuseppe Riva ◽  
Daniela Villani ◽  
Pietro Cipresso ◽  
Andrea Gaggioli

This chapter describes and discusses the “Positive Technology” approach: the scientific and applied approach for the use of technology in improving the quality of our personal experience through its structuring, augmentation and/or replacement - as a way for improving and sustaining personal change. On one side, we suggest that our cognitive system is naturally shaped to identify and counter the experiential conflicts that are usually the main motives for change. Optimal experiences, also defined as “flow experiences”, instead allow the individual to consider long-term personal goals differently and start to experiment with changing them. In other words optimal experiences, when meaningful for the individual, widen the array of thoughts and actions, facilitating generativity and behavioral flexibility. On the other side we claim that it is possible to use technology to manipulate the quality of experience, with the goal of increasing wellness, and generating strengths and resilience in individuals, organizations and society.


Author(s):  
Liudmyla VOLONTYR

Development of modern economic trends in the system of conceptual foundations for the improvements in sugar beet production sector has necessitated the introduction of new approaches in the processes of managing commodity, financial and information flows on the basis of the use of methods of economic and mathematical modeling. The main idea for implementation these methods is to evaluate the development of forecasts in terms of their formalization, systematization, optimization and adaptation under application of new information technologies. The quality of management decision-making depends on the accuracy and reliability of the developed long-term evaluations. In this regard, one of the most important areas of research in the economy is to forecast the parameters of the beet industry development and to obtain predictive decisions that form the basis for effective activity in the process of achieving tactical and strategic goals. Under a significant dispersion of the time series levels, a variety of smoothing procedures are used to detect and distinguish the trend: direct level equalization by the ordinary least squares technique, ordinary and weighted moving averages, exponential smoothing, spectral methods and application of splines, moving average method, or running median smoothing. The most common among them are regular and weighted moving averages and exponential smoothing. Investigation of methods of forecasting parameters of development of beet growing industry taking into account the peculiarities of constructing quantitative and qualitative forecasts requires solving the following tasks: - investigation of the specifics of the use of statistical methods of time series analysis in beet growing; - research of the specificity of the use of forecasting methods for the estimation of long-term solutions in beet growing; - carrying out practical implementation of the methods as exemplified by the estimation of forecasts of sugar beet yields at the enterprises of Ukraine. The method of exponential smoothing proposed by R. G. Brown gives the most accurate approximation to the original statistical series – it takes into account the variation of prices. The essence of this method lies in the fact that the statistical series is smoothed out with the help of a weighted moving average, which is subject to the exponential law. When calculating the exponential value of time t it is always necessary to have the exponential value at the previous moment of time, and therefore the first step is to determine some Sn-1 value that precedes Sn. In practice, there is no single approach to defining initial approximations – they are set in accordance with the conditions of economic research. Quite often, the arithmetic mean of all levels of the statistical series is used as Sn-1. It should be noted that a certain problem in forecasting with the help of exponential smoothing is the choice of the parameter a optimal value, on which the accuracy of the results of the forecast depends to a large extent. If the parameter a is close to the identity element, then the forecast model takes into account only the effects of the last observations, and if it approaches to zero, then almost all the previous observations are usually taken into account. However, scientific and methodical approaches to determining the optimal value of the smoothing parameter have not yet been developed. In practice, the value of a is chosen according to the smallest dispersion of deviations of the predicted values of the statistical series from its actual levels. The method of exponential smoothing gives positive findings when a statistical series consists of a large number of observations and it is assumed that the socioeconomic processes in the forecasting period will occur approximately under the same conditions as in the base period. A correctly selected model of the growth curve shall correspond to the nature of the trend change of the phenomenon under study. The procedure for developing a forecast using growth curves involves the following steps: - choice of one or several curves whose shape corresponds to the nature; - time series changes; - evaluation of the parameters of the selected curves; - verification of the adequacy of the selected curves of the process being foreseen; - evaluation of the accuracy of models and the final choice of the growth curve; - calculation of point and interval forecasts. The most common practice in forecasting are the functions used to describe processes with a monotonous nature of the trend of development and the absence of growth boundaries. On the basis of the studied models, smoothing of the statistical series of the sugar beet gross yields of in Ukraine was carried out. The statistical data from 1990 to 2017 have been taken for the survey. The forecast of the sugar beet yields for 2012-2017 have been used to determine the approximation error by the ordinary moving averages with a length of the smoothing interval of 5 years and 12 years, as well as by the method of exponential smoothing with the parameter α = 0,3 and α = 0, 7 The analysis of the quality of forecasts is based on the average absolute deviation. Therefore, this value is the smallest for the forecast, which is determined by the method of exponential smoothing with the constant value of a = 0,7. By this method, we will determine the forecast for the next 5 years.


Author(s):  
O. M. Zhitinskaya ◽  
L. A. Yarg

The influence of the processes of functioning of the local natural-technical systems (NTS) «Stoilenskoe» and «Lebedinskoe» of the KMA deposit on the environment has been studied with the information obtained during the period of last 7—12 years (2004—2015 y.y.). Results of the analyses of time series and obtained trends in the geological components alteration (in particular, a) level of groundwater, b) chemical composition of groundwater, c) engineering and geological processes) have been given. The ways of regime observations optimization concerning their placement and frequency in time have been offered. The proposed way of the assessment of the current state of NTS allows reducing the observations number, without reducing quality of information. The spatial structure and the time mode of monitoring have to be corrected according to the obtained information. The data received from Lebedinskoye and Stoylinskoye fields can be used for design and development of the similar geological fields.


2008 ◽  
Vol 47 (4) ◽  
pp. 1006-1016 ◽  
Author(s):  
Guang-Yu Shi ◽  
Tadahiro Hayasaka ◽  
Atsumu Ohmura ◽  
Zhi-Hua Chen ◽  
Biao Wang ◽  
...  

Abstract Solar radiation is one of the most important factors affecting climate and the environment. Routine measurements of irradiance are valuable for climate change research because of long time series and areal coverage. In this study, a set of quality assessment (QA) algorithms is used to test the quality of daily solar global, direct, and diffuse radiation measurements taken at 122 observatories in China during 1957–2000. The QA algorithms include a physical threshold test (QA1), a global radiation sunshine duration test (QA2), and a standard deviation test applied to time series of annually averaged solar global radiation (QA3). The results show that the percentages of global, direct, and diffuse solar radiation data that fail to pass QA1 are 3.07%, 0.01%, and 2.52%, respectively; the percentages of global solar radiation data that fail to pass the QA2 and QA3 are 0.77% and 0.49%, respectively. The method implemented by the Global Energy Balance Archive is also applied to check the data quality of solar radiation in China. Of the 84 stations with a time series longer that 20 yr, suspect data at 35 of the sites were found. Based on data that passed the QA tests, trends in ground solar radiation and the effect of the data quality assessment on the trends are analyzed. There is a decrease in ground solar global and direct radiation in China over the years under study. Although the quality assessment process has significant effects on the data from individual stations and/or time periods, it does not affect the long-term trends in the data.


2012 ◽  
Vol 190-191 ◽  
pp. 1029-1032
Author(s):  
Bo Wan ◽  
Li Wang ◽  
Gui Cui Fu

This paper presents a quality monitoring and prognostic method to evaluating quality of electronics through monitoring degradation path. Electronics multiple performance parameter degradation data are treated as multidimensional time series and described using multidimensional time series model to take into account implements of stochastic nature of environmental variables and to predict long-term trend of performance degradation. A degradation test is processed for certain electronics and three kinds of performance parameters degradation data are monitored for prognostics. A comparison between the predicted degradation path using multidimensional time series analysis, the predicted degradation path using one-dimensional time series analysis and the real degradation path of the electronics is processed and the results show that the degradation path prediction using the suggested method is more effective than one-dimensional time series analysis.


Author(s):  
I. A. Kondratenkov ◽  
M. L. Oparin ◽  
O. S. Oparina ◽  
S. V. Sukhov

The present paper is devoted to the study of the possibility of estimating the reproductive potentials of wild ungulate populations, and possibly other large mammals, by the time series of their numbers. We have found out that this is possible, which is confirmed by the high quality of approximation of the time series of abundance by logistic curves, and the corresponding coefficients of their determination for different species ranged from 75 to 96%. For such calculations, one circumstance is necessary, which is that the population of the studied species has been briefly exposed to some unfavorable factor causing a significant reduction in its numbers with subsequent restoration to the previous level, or the time series should contain a well-expressed and extended section of the transition of the population from some lower level to the upper level of the population, passing into a stationary state. The values of the maximum exponential growth rates of ungulate populations that we obtained do not fundamentally differ from the data available in other researchers’ works. In addition, it should be borne in mind that our method for assessing the reproductive potentials of ungulates is statistical, with features accompanying all such methods, for example, in the presence of statistical errors in all determined parameters. However, the evaluation of the magnitude of these errors is a topic for a separate study. 


2021 ◽  
Author(s):  
Gaia Pinardi ◽  
Michel Van Roozendael ◽  
François Hendrick ◽  
Andreas Meier ◽  
Andreas Richter ◽  
...  

<p>Chlorine dioxide is an indicator for chlorine activation in the stratosphere, of importance for understanding spring-time ozone depletion processes in the polar regions of both hemispheres. Within the EUMETSAT AC SAF working group, chlorine dioxide (OClO) was retrieved from the GOME-2 instruments on MetOp-A and MetOp-B platforms, respectively over the time periods 2007-2016 and 2012-2016. Moreover, recent work performed as part of the S5p+ Innovation programme has led to the creation of an additional dataset derived from the TROPOMI instrument, extending the OClO time series in 2018-2020.</p><p>This study analyses the quality of both OClO slant column (SCD) datasets by comparing them to ground-based DOAS zenith-sky measurements at a selection of 8 stations in Arctic and Antarctic regions: Eureka (80°N), Ny Alesund (79°N), Kiruna (68°N), Harestua (60°N), Marambio (64°S), Belgrano (78°S), Neumayer (71°S) and Arrival Heights (78°S). To allow for comparison with satellite data, ground-based OClO spectral analyses are performed using yearly fixed reference spectra recorded at low SZA in the absence of chlorine activation. Furthermore, an additional bias-correction is applied in post-processing to generate a consistent long-term OClO data record covering the 2007-2020 period.</p><p>Daily comparisons of satellite and ground-based SCD data pairs corresponding to similar SZA conditions are performed, assuming similar stratospheric light paths in satellite nadir and ground-based zenith-sky geometries. Daily mean OClO SCD time-series show that satellite and ground-based observations agree well at all stations in terms of short-term variability and seasonal variation. Linear regression plots show a correlation coefficient R of about 0.97, a slope of 0.9 and an intercept of less than 1x10<sup>13</sup> molec/cm² for TROPOMI, while for GOME-2 results are more noisy and tend to be biased low, with correlation coefficients between 0.76 and 0.88, slopes between 0.65 and 0.74 and intercepts up to 2.4 x10<sup>13 </sup>molec/cm².</p>


1993 ◽  
Vol 136 ◽  
pp. 250-256
Author(s):  
D. O’Donoghue ◽  
J. Provencal

AbstractA summary of the results from seven global runs using the Whole Earth Telescope is presented, together with an evaluation of the scientific results obtained to date. Factors such as the distance of the target star from the equator, the nature and timescales of its intrinsic variability, etc. are shown to affect the value and quality of the results, as well as the traditional factors such as brightness and long-term coherent behaviour. Experience with the network shows that, taken as a whole, it enjoys far better weather than any one of its sites, and provides unprecedented ‘uncluttered’ resolution of time-series power spectra.


2020 ◽  
Author(s):  
Larisa Sogacheva ◽  

<p>Satellite instruments provide a vantage point for studying aerosol loading consistently over different regions of the world. However, the typical lifetime of a single satellite platform is on the order of 5-15 years; thus, for climate studies, the use of multiple satellite sensors should be considered.</p><p>We introduce a gridded monthly AOD merged product for the period 1995-2017 obtained by combining 12 major available monthly AOD products, which provides a long-term perspective on AOD changes over different regions of the world. Different approaches for merging the individual AOD products (median, weighted according to the evaluation results) are tested. We show that the quality of the merged product is as least as good as that of individual products.</p><p>We also introduce an approach to combine the merged AOD product with the AOD time series available over land (TOMS) and ocean (AVHRR) from early 1980th.</p><p>The evaluation of the modelled AOD products with the satellite AOD product shows that the agreement between modelled and merged AOD product is closer than one between modelled and individual satellite AOD products.</p>


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