This study endeavors to enrich investment prospects in cryptocurrency by establishing a rationale for investment decisions. The primary objective involves evaluating the predictability of four prominent cryptocurrencies – Bitcoin, Ethereum, Litecoin, and EOS – and scrutinizing the efficacy of trading strategies developed based on the prediction model. To identify the most effective prediction model for each cryptocurrency annually, we employed three methodologies – AutoRegressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Prophet – representing traditional statistics and artificial intelligence. These methods were applied across diverse periods and time intervals. The result suggested that Prophet trained on the previous 28 days' price history at 15-minute intervals generally yielded the highest performance. The results were validated through a random selection of 100 days (20 target dates per year) spanning from January 1st, 2018, to December 31st, 2022. The trading strategies were formulated based on the optimal-performing prediction model, grounded in the simple principle of assigning greater weight to more predictable assets. When the forecasting model indicates an upward trend, it is recommended to acquire the cryptocurrency with the investment amount determined by its performance. Experimental results consistently demonstrated that the proposed trading strategy yields higher returns compared to an equal portfolio employing a buy-and-hold strategy. The cryptocurrency trading model introduced in this paper carries two significant implications. Firstly, it facilitates the evolution of cryptocurrencies from speculative assets to investment instruments. Secondly, it plays a crucial role in advancing deep learning- based investment strategies by providing sound evidence for portfolio allocation. This addresses the black box issue, a notable weakness in deep learning, offering increased transparency to the model.

Cryptocurrency transactions are subject to private law regulations. This article reviews the legal nature of cryptocurrency from the perspective of general civil law theory. The undeniable nature of property in cryptocurrency has led to an increased demand for judicial systems to effectively operate in regards to cryptocurrency. The right to cryptocurrency cannot be regarded as intellectual property rights. Cryptocurrency cannot also be regarded as a bond, as it is merely units of information listed in the distributed ledger with no counterparty. Cryptocurrency can be understood as an “things” under civil law because there is a possibility of management through an electronic wallet private key and also independence through a distributed ledger. Among the requirements of an things, the requirement of ‘corporeal things’ or ‘natural force’ can be flexibly interpreted in regards of transactions between related parties. On the other hand, cryptocurrency cannot be regarded as “money” among things. Cryptocurrency cannot function as a “measure of value”, which is a fundamental function of money, due to its inherent nature of volatility and price differences between its exchanges. As a result, the legal nature of cryptocurrency can be recognized as a things, not money, through which current existing judicial systems such as compulsory execution law and bankruptcy law becomes able to operate in regards to cryptocurrency, ultimately promoting legal predictability. However, legislation on cryptocurrency should ultimately be completed through legislation, not interpretation. This requires further in-depth discussion in academic and practice sectors.