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Journal : International Conference on Health Science, Green Economics, Educational Review and Technology (IHERT)

FUNDAMENTAL ECONOMIC RISK FACTORS IN INCREASING THE VALUE OF DIGITAL ASSET INVESTMENTS IN INDONESIA Reza Juanda; Falahuddin; Muttaqien; Rico Nur Ilham; Frengki Putra Ramansyah; Muhammad Multazam
International Conference on Health Science, Green Economics, Educational Review and Technology Vol. 6 No. 1 (2024): 6th IHERT (2024): IHERT (2024) FIRST ISSUE: International Conference on Health
Publisher : Universitas Efarina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ihert.v6i1.403

Abstract

Already has a permit to be traded in exchange trading through the Indonesian Commodity Futures Trading Supervisory Agency (BAPEPTI). Digital crypto assets traded in Indonesia are quite a lot through the Indodax trading company. The purpose of this study is focused on formulating a risk management process in investing in digital cryptocurrency assets. In addition, the results of this study will produce policy recommendations known as LCTR or "Legal Cryptocurrency and Tax Revenue" which are expected to be considered by the government in formulating policies on digital crypto assets so that the interests of all parties can be accommodated in order to realize maximum state revenue from trading digital crypto asset commodities. This type of research is quantitative descriptive with a research population of 10 cryptocurrency coins with the largest market caps in Indonesia, namely Cryptocurrency Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), Bitcoin Cash (BCH), Litecoin (LTC), Stellar, DASH, Dogecoin, Zcash, Monero in Indonesia. The type of data in this study is time series data taken from January 2017 to December 2020 by conducting a documentation study conducted on the publication of monthly cryptocurrency transaction reports, so that a target population of 480 (4 years x 12 months x 10 coins) monthly report data was obtained for the research sample. The data analysis method in this study uses multiple linear regression and data analysis using e-views statistical software version 10.