Support system for speculation by exchange trades funds
Abstract
The paper examines the possibilities of speculating in exchangetraded funds by using artificial intelligence. The main goal of the research is to create a support system for speculative decisionmaking for investors operating in exchange-traded funds market. The research will be based on the theoretical aspects of artificial intelligence and speculation of exchange-traded funds. The support system is developed on the basis of reinforcement learning, the methods of synthesis, concretization and generalization were used to create and detail the system, as well as the methods of mathematical-statistical analysis were used to process them. Successful application of the chosen methodology in the design of the support system has resulted in positive trade results. Successful research broadens the boundaries for usage of deep reinforcement learning, and provides a basis for further development of the support system for exchange-traded funds. The support system put in place will shorten the time between the occurrence of a trading signal and the decision of the investor, which will help to reduce the loss of potential profits.
Article in Lithuanian.
Paramos sistema spekuliavimui biržoje prekiaujamais fondais
Santrauka
Darbe yra nagrinėjamos spekuliavimo biržoje prekiaujamais fondais, naudojant dirbtinį intelektą, galimybės. Pagrindinis mokslinio tyrimo tikslas – remiantis dirbtinio intelekto bei biržoje prekiaujamų fondų spekuliavimo teoriniais aspektais, sukurti spekuliavimo sprendimų priėmimo paramos sistemą investuotojams, veikiantiems biržoje prekiaujamų fondų rinkoje. Paramos sistema yra kuriama remiantis sustiprintuoju mokymusi (angl. reinforcement learning), sistemai sudaryti ir detalizuoti buvo taikyti sintezės, konkretizavimo bei apibendrinimo metodai, taip pat, panaudojus susidarytą sistemą bei gavus rezultatus, jiems apdoroti taikyti matematinės-statistinės analizės metodai. Sėkmingai pritaikius pasirinktą metodologiją, sudarant paramos sistemą, buvo gauti teigiami prekybos rezultatai. Sėkmingas tyrimas išplečia giliojo sustiprintojo mokymosi taikymo suvokimo ribas bei sudaro pagrindą tolesniam biržoje prekiaujamų fondų paramos sistemos vystymui. Sudaryta paramos sistema sutrumpins sugaištamą laiką tarp prekybos signalo atsiradimo ir investuotojo sprendimo priėmimo, o tai padės sumažinti potencialaus pelno praradimą.
Reikšminiai žodžiai: paramos sistema, biržoje prekiaujami fondai, spekuliavimas, dirbtinis intelektas, finansų rinka, sustiprintasis mokymasis, mašininis mokymasis.
Keyword : support system, exchange traded funds, speculation, artificial intelligence, financial market, reinforcement learning, machine learning
This work is licensed under a Creative Commons Attribution 4.0 International License.
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