Traditional and Machine Learning-Based Methods for Financial Instrument Price Forecasting: A Theoretical Approach

Financial markets are one of the main components of the economy, and their growth and development is a crucial and significant factor in the world. Meanwhile, artificial intelligence is an exponentially developing field. The use of artificial intelligence in financial markets is a new and intensely developing phenomenon, requiring extensive research. The aim of this paper is to present a methodology of machine learning-based method effective application in financial instrument price forecasting in comparison with the traditional method, namely ARIMA. Consequently, the scientific literature on financial markets, traditional and machine learning-based methods were analyzed. Finally, a theoretical model for stock prices forecasting is presented. The main results of the analysis show the most extensively techniques applied in the stock markets and cash markets are methods of time series analysis, econometrics and machine learning. After analysis of methods of machine learning, it can be found most popular supervised learning algorithms are linear regression, decision trees/regression tree, random forest classification/ regression, and support vector machines. As a result of the research, a theoretical model for financial instrument price forecasting is presented and discussed. Based on the theoretical approach proposed several experiments will be performed using ARIMA and Support Vector Regression (SVR) methods

Nuotolinių studijų vartotojų poreikių analizė

Nuotolinės studijos šiuo metu tampa viena populiariausių studijų formų Lietuvoje ir pasaulyje. Besivystant informacinėms ir komunikacinėms technologijoms daugelis žmonių studijuoja neatsitraukdami nuo savo darbo vietų. Tokiame studijų procese dalyvauja skirtingi vartotojai: studentai, dėstytojai, nuotolinių modulių kūrėjai, auditoriai, virtualaus mokymo aplinkų administratoriai. Straipsnyje analizuojamos atskiros vartotojų grupės, šių grupių atstovų poreikiai studijuojant nuotoliniu būdu ir tųporeikių tenkinimo būdai.The Analysis of Distance Education Users NeedsLeonidas Sakalauskas, Saulius Preidys SummaryDifferent users are participating in distance learning process: teachers (tutors), distance course creators, auditors, VLE administrators. The quality of such studies depends on all of these groups: module developed qualitatively will be convenient for the learner and helpful for the tutor. All the study process depends on the administrator’s activities: if server is working with breaks, studies can become unpredictable and not attractive. In this article the needs of different user groups are analysed and conditions are created for the programming agent development which can improve distance education process.ight: 18px;"

Nuotolinio mokymosi stilių personalizavimas

Mokymosi stiliai yra skirtingi. Kai kurie teikia pirmenybę klausymui ir kalbėjimui, kiti teksto analizei arba mokosi pasitelkę vaizdines priemones. Tačiau daugumos studentų mokymosi stilius yra mišrus. Ypač tai aktualu žinoti kuratoriams ir kursų autoriams, dirbantiems su studentais, studijuojančiais nuotoliniu būdu: reikiamai parengta mokymosi medžiaga, suasmenintos užduotys ir asmeniški komentarai padės studentui greičiau pasiekti iškeltus kurso tikslus ir uždavinius. Šiame straipsnyjeautoriai, remdamiesi Honey ir Mumfordo (1992) sukurta tipologija, nagrinėja mokymosi stilių nustatymą ir vizualizavimą, analizuodami studentų veiklą virtualaus mokymosi aplinkose ir sukauptiems duomenims taikydami duomenų gavybos metodus.Personalization of Learning Styles in Distance EducationSaulius Preidys, Leonidas Sakalauskas SummaryDifferent learners have different styles of learning. Some of them give the priority to listening and speaking, others to text analysis or visual tools. Nevertheless, the learning style of many learners is mixed. Tutors and course creators working with distance learners should be aware of this fact. Appropriate learning materials, personalised assignments and personal comments would help the learner in achieving the aims and objectives of the course. Referring to Honey and Mumford (1992), the authors of the article analyse the determination and visualisation of learning styles, by tracking learners’ activities in virtual learning environments and using data mining methods.eight: 18px;">&nbsp

The peculiarities of ICT students‘ drop-out because of academic arrears

Lack of ICT specialists is a big problem in Lithuania for many years. Even ICT specialists are prepared both by universities and colleges, need of those specialists is increasing every year. Students’ enrolment to the ICT related study programmes is increasing a little every year, but only around 51% of them complete their studies. There are very different reasons of students drop-out: health problems, characteristics of personality (lack of responsibility, self-doubts, etc.), socio-economic factors, organisation of study process (Barkauskaitė & Gudžinskienė 2006). In this article a different approach is used to academic arrears – using statistical calculations, academic arrears of students of Vilnius University, Faculty of Mathematics and Informatics from 1991 till 2012 are analysed. At the end of the article, justification of a theoretical model is presented, using which students’ drop-out peculiarities in different study programmes can be observed.DOI: 10.15181/csat.v3i2.111

The peculiarities of ict students‘ drop-out because of academic arrears

Lack of ICT specialists is a big problem in Lithuania for many years. Even ICT specialists are prepared both by universities and colleges, need of those specialists is increasing every year. Students’ enrolment to the ICT related study programmes is increasing a little every year, but only around 51% of them complete their studies. There are very different reasons of students drop-out: health problems, characteristics of personality (lack of responsibility, self-doubts, etc.), socio-economic factors, organisation of study process (Barkauskaitė & Gudžinskienė 2006). In this article a different approach is used to academic arrears – using statistical calculations, academic arrears of students of Vilnius University, Faculty of Mathematics and Informatics from 1991 till 2012 are analysed. At the end of the article, justification of a theoretical model is presented, using which students’ drop-out peculiarities in different study programmes can be observed

Analysis of students’ study activities in virtual learning environments using data mining methods / Studentų, besimokančių virtualaus mokymo aplinkoje, veiklos analizė taikant duomenų gavybos metodus

This article deals with application of data mining methods’ to analysis of learners’ behaviour using the distance learning platform BlackBoard Vista (BlackBoard 2008). Before planning a distance learning course, instructors have to pay attention to the fact that there exist different study methods: some students start reading learning materials from the very beginning to the end, some students look at unclear topics only, some start with the discussions, etc. Therefore after analyzing the learning factors and identifying learner's style, it is possible to prepare individualized learning materials and to choose a proper way of course presentation. Such a way of study organization would improve the quality of studies and make it possible to reach better results. The research was performed by observing the behaviour and results achieved by 528 students in 15 distance learning courses and, using the clustering method, 3 learner's styles using virtual learning environments (VLE) have been identified and work methods proposed for students with regard to those learners’ styles. Besides, the research aims to find out the factors that influence final evaluations of students’. Santrauka Prieš planuodami rengti ir teikti nuotolinio mokymosi kursą, rengėjai turi atsižvelgti į tai, kad žmonės studijuoja skirtingais metodais: vieni pradeda skaityti pateiktą medžiagą iš eiles, kiti peržiūri tik nesuprantamas vietas, treti persikelia į virtualias diskusijas ir pan. Todėl, išanalizavus mokymosi veiksmus ir nustačius studento stilių, vėliau galima pateikti suasmenintą mokymosi medžiagą, parinkti geresnius kurso pateikimo metodus. Toks mokymo organizavimas pagerintų studijų kokybę ir leistų pasiekti geresnių rezultatų. Šiame straipsnyje nagrinėjamas duomenų gavybos metodu taikymas, analizuojant studentų elgseną, naudojantis virtualaus mokymo terpe BlackBoard Vista (BlackBoard 2008). First published online: 21 Oct 2010 Reikšminiai žodžiai: virtualaus mokymo aplinka, nuotolinis mokymas, duomenu gavyba, klasterizavimas, nuotoliniu studiju vartotoju elgsen

Educational Organization’s Security Level Estimation Model

During the pandemic, distance learning gained its necessity. Most schools and universities were forced to use e-learning tools. The fast transition to distance learning increased the digitalization of the educational system and influenced the increase of security incident numbers as there was no time to estimate the security level change by incorporating new e-learning systems. Notably, preparation for distance learning was accompanied by several limitations: lack of time, lack of resources to manage the information technologies and systems, lack of knowledge on information security management, and security level modeling. In this paper, we propose a security level estimation model for educational organizations. This model takes into account distance learning specifics and allows quantitative estimation of an organization’s security level. It is based on 49 criteria values, structured into an AHP (Analytic Hierarchy Process) tree, and arranged to final security level metric by incorporating experts’ opinion-based criteria importance coefficients. The research proposed a criteria tree and obtained experts’ opinions lead to educational organization security level evaluation model, resulting in one quantitative metric. It can be used to model different situations and find the better alternative in case of security level, without external security experts usage. Use case analysis results and their similarity to security experts’ evaluation are presented in this paper as validation of the proposed model. It confirms the model meets experts-based information security level ranking, therefore, can be used for simpler security modeling in educational organizations

Stojančiųjų IKT žinių kitimo tendencijos

Informacinės technologijos (IT) – prioritetinė mokslo šaka Lietuvoje. Informacinės technologijos dėstomos visose kolegijose. Šio dalyko programose yra panašių temų kaip ir vidurinėse mokyklose: tekstų redaktoriai, skaičiuoklės, internetas ir komunikacija. Ar keisime dalyko programą iš esmės, kada tai turėtų įvykti? Apie tai bus kalbama šiame pranešimeInformation and Communication Technology (ICT) is a priority science in Lithuania. Information and Communication Technologies are studied in all colleges. Some themes within this programme are similar to those in secondary schools programme, namely, world processing and calculation programmes, the Internet and communication. Shall we make some principal changes in the programme? If yes, when it should be done? This problem is dealt with in the article hereinVytauto Didžiojo universiteta