<![CDATA[Extreme volatility and unpredictable price movements in the cryptocurrency market present significant challenges for investors in selecting optimal investment strategies. In such a dynamic environment, it is crucial to adopt an approach that balances profit potential with risk mitigation. This study compares two algorithm-based investment strategies: Dollar Cost Averaging (DCA), modeled through Dynamic Programming, and the all-in strategy, simulated using the Greedy Algorithm. The analysis focuses on the five largest cryptocurrencies by market capitalization in 2024 Bitcoin (BTC), Ethereum (ETH), Solana (SOL), Binance Coin (BNB), and XRP using monthly price data from January to December 2024. Simulations were conducted with a total capital of IDR 120 million, allocated monthly for DCA and invested fully at the lowest price point for the all-in strategy. The results show that the all-in approach yielded the highest return of 443.74% (XRP), yet carried significantly higher risk due to its dependency on perfect market timing. In contrast, DCA delivered more consistent returns, with a safer way to gain 47,53% (BTC), and offered greater price stability by distributing investments over time. The findings indicate that DCA is more suitable for investors with low to moderate risk tolerance, while the all-in strategy favors high risk tolerant investors with strong market timing skills. This study contributes to the development of algorithmic investment models in the digital asset space and provides practical insights for retail investors seeking to align strategy selection with their individual risk profiles in a highly volatile market.]]>
