Decomposing Bitcoin Returns into Latent Market Factors Using Independent Component Analysis

This paper investigates the hidden factors influence Bitcoin's price dynamics by applying Independent Component Analysis (ICA) to historical daily returns. Motivated by the growing complexity of financial markets, which increase systemic risk, the study's objective is about to identify statistically independent sources influencing market structural behavior such as sentiment, liquidity, and macroeconomic components. The methodology contains preprocessing Bitcoin price data and performing ICA to decompose observed returns into independent components. The dominant component then used to provide a regime signal, indentifying bullish and bearish periods. The results demonstrate ICA's effectiveness in isolating latent market drivers, providing insights into regime shifts and systemic influences in cryptocurrency markets. This approach offers a structured framework for analyzing complex financial systems and supports informed decision-making in risk management and trading strategies.

کلیدواژه ها:

Independent Analysis ، Bitcoin Compnoent ، Price Dynamics ، Financial Latent Factor