IMPLEMENTATION OF AGENT-BASED METHODS IN THE DEVELOPMENT OF SIMULATOR FOR ANALYZING THE STABILITY OF STABLECOIN CRYPTOCURRENCIES

• Main Author: Santoso Putri, Anggietha
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/64583
• Institution: Institut Teknologi Bandung

The development of digital technology is supporting the growth of new digital technology, one of which is in the financial sector (fintech). Cryptocurrency is a digital currency that is a development of financial technology. In early 2022, the Commodity Futures Trading Regulatory Agency (Bappeti) discovered that Indonesia's cryptocurrency users reached 12 million and trading reached Rp. 83.3 trillion. One class of cryptocurrencies is stablecoin, which provides price stability backed by reserve assets, addressing security or privacy concerns and freeing you from volatility. Foreign exchange reserves are usually in the form of fiat currencies, and commodities are in the form of gold or other cryptocurrencies. According to Bappeti regulation Number 7 of 2020 concerning the Establishment of a List of Tradeable Crypto Assets in the Crypto Asset Physical Market, it is stated that the Cryptocurrencies that we know today are not legal tender in the territory of the Republic of Indonesia, but as tradable Crypto Assets. in the Crypto Asset Physical Market. To be successful in the long term, cryptocurrencies face many challenges in terms of technology, usability, and regulation. In this final project, a simulator is developed to analyze the stability of stablecoins which is finally expected to help stakeholders of the financial ecosystem in the future to determine regulations with the development of a decentralized financial system. This simulator was created using the Agent-Based Modelling (ABM) method which is agent-based modelling that simulates the interaction between one agent and another in an ecosystem. Allows each agent to play a role according to its role. Agent-based modelling is often used when modelling complex systems. In this case, it is used to model the financial system, so the results are expected to be more accurate.