Hong, Liang Cai (2022) Optimal double deep q-learning network and support vector machine for maximum profit of cryptocurrency trading bot. Masters thesis, Universitas Pelita Harapan.
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Abstract
Since a couple years back, a virtual currency cryptocurrency has grown
significantly in popularity. Many parties including investors and scholars alike have
developed an interest in this trending subject due to its immense profit potential.
Cryptocurrency trading requires a fast yet proper analysis and decision making that
relies on the trader to analyze a large amount of data. Many have tried to automate
the cryptocurrency trading flow by utilizing various algorithms that fall in the
category of prediction models and reinforcement learning to simplify it. In this
thesis an automated cryptocurrency trading bot that combines Double Deep Q�Learning Network and Support Vector Machine algorithm to automatically trade
effectively in unpredictable situation and gain a sizeable profit is implemented. The
trading bot using Double Deep Q-Learning Network and Support Vector Machine
produced better profitability. Using hyperparameters of gamma 100 and C 100 in
BTC/IDR cryptocurrency pair, gamma 100 and C 100 in ETH/IDR pair, and gamma
80 and C 18 in USDT/IDR pair, the hybrid trading bot scores 24 times more profits
in BTC/IDR pair, 52 times more profits in ETH/IDR pair, and 5 times more profit
in USD/IDR pair. / Sejak beberapa tahun yang lalu, cryptocurrency mata uang virtual telah
tumbuh secara signifikan dalam popularitas. Banyak pihak termasuk investor dan
cendekiawan sama-sama tertarik pada topik yang sedang tren ini karena potensi
keuntungannya yang sangat besar. Perdagangan cryptocurrency membutuhkan
analisis dan pengambilan keputusan yang cepat namun tepat yang bergantung pada
pedagang untuk menganalisis sejumlah besar data. Banyak yang mencoba
mengotomatiskan alur perdagangan cryptocurrency dengan memanfaatkan
berbagai algoritma yang termasuk dalam kategori model prediksi dan pembelajaran
penguatan untuk menyederhanakannya. Tesis ini bertujuan untuk membangun bot
perdagangan cryptocurrency otomatis yang menggabungkan algoritma Double
Deep Q-Learning Network dan Support Vector Machine dengan tujuan untuk
berdagang secara otomatis secara efektif dalam situasi yang tidak terduga dan
mendapatkan keuntungan yang cukup besar. Bot perdagangan menggunakan
Double Deep Q-Learning Network dan Support Vector Machine menghasilkan
profitabilitas yang lebih baik. Dengan menggunakan hyperparameter gamma 100
dan C 100 dalam pasangan mata uang kripto BTC/IDR, gamma 100 dan C 100
dalam pasangan ETH/IDR, dan gamma 80 dan C 18 dalam pasangan USDT/IDR,
bot perdagangan hibrida mencetak keuntungan 24 kali lebih banyak dalam BTC/
Pasangan IDR, 52 kali lebih banyak keuntungan dalam pasangan ETH/IDR, dan 5
kali lebih banyak keuntungan dalam pasangan USD/IDR.
Item Type: | Thesis (Masters) |
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Creators: | Creators NIM Email ORCID Hong, Liang Cai NIM01679210006 liangcai.stdnt@gmail.com UNSPECIFIED |
Contributors: | Contribution Contributors NIDN/NIDK Email Thesis advisor Yugopuspito, Pujianto NIDN0324086701 yugopuspito@uph.edu Thesis advisor Tjahyadi, Hendra NIDN0410076901 hendra.tjahyadi@uph.edu |
Uncontrolled Keywords: | Cryptocurrency ; Reinformcent Learning ; Support Vector Machine ; Trading |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | University Subject > Current > Faculty/School - UPH Karawaci > School of Information Science and Technology > Master of Informatics Current > Faculty/School - UPH Karawaci > School of Information Science and Technology > Master of Informatics |
Depositing User: | Users 29052 not found. |
Date Deposited: | 16 Feb 2023 00:28 |
Last Modified: | 16 Feb 2023 00:28 |
URI: | http://repository.uph.edu/id/eprint/54420 |