DARI WALL STREET KE BLOCKCHAIN: MENELUSURI EFISIENSI PASAR DENGAN MULTIFRAKTAL

This study aims to examine market efficiency across two major asset classes, stock indices and cryptocurrencies, using the Multifractal Detrended Fluctuation Analysis (MFDFA) method. The research analyzes stock indices such as the S&P 500, NASDAQ Composite, Dow Jones, NYSE, FTSE 100, Shenzhen, and Hang Seng, as well as major cryptocurrencies including Bitcoin (BTC), Ethereum (ETH), Tether (USDT), USD Coin, and XRP. By evaluating the multifractal characteristics of each asset, the study assesses the extent to which these markets conform to the Efficient Market Hypothesis (EMH). The findings suggest that stock indices tend to exhibit monofractal behavior, reflecting a higher degree of informational efficiency. In contrast, cryptocurrencies display pronounced multifractal patterns, indicating a significant level of inefficiency, likely driven by extreme volatility, immature market structures, and the influence of sentiment and external shocks. This study makes an important contribution to understanding the behavioral differences between traditional and digital markets and offers practical implications for investors in terms of diversification strategies and risk management.