本研究旨在探討加密貨幣永續合約資金費率對美股指數期貨之跨市
場關聯性，並聚焦於市場狀態分析。研究樣本涵蓋幣安交易所之比特幣（BTCUSDT）與以太幣（ETHUSDT）永續合約，以及美國小道瓊、小那斯達
克100與小標普500指數期貨。資料期間自2023年10月31日至2025年
12月13日，經重新取樣為8小時與日頻率後，建構包含年化資金費率、資金費率變動率、永續合約標記價格報酬及美股期貨報酬之研究變數。
實證方法首先檢視變數之統計分布特徵；其次，透過控制價格報酬之部分相關分析，剔除價格共振影響以萃取資金費率純粹與變數相關性；最後，採用高低分位（低於25分位數與高於75分位數）分組分析，檢視方向是否有一致偏離隨機水準。
實證結果顯示，資金費率呈現顯著右偏與厚尾特徵。在控制價格因素後，資金費率與美股期貨之全樣本線性關聯微弱，顯示其並非穩定的常態預測因子。然而，在高低分位之外的尾部情境下，比特幣與以太幣對不同美股板塊展現出非對稱的顯著連動，證實了資金費率跨市傳導具有高度的情境依賴性。本研究建議金融機構與投資人應將資金費率視為監控極端槓桿風險之「狀態指標」，並建議後續研究能以更高頻或其餘樣本繼續探討。

This study investigates the cross-market correlation between cryptocurrency perpetual contract funding rates and U.S. equity index futures, specifically focusing on market state. The research sample includes Bitcoin (BTCUSDT) and Ethereum (ETHUSDT) perpetual contracts from the Binance exchange, as well as E-mini Dow, E-mini Nasdaq-100, and E-mini S&P 500 index futures. The data period spans from October 31, 2023, to December 13, 2025. The data is resampled into 8-hour and daily frequencies to construct research variables, including annualized funding rates, funding rate changes, perpetual mark price returns, and futures returns.
The empirical methodology first examines the statistical distribution characteristics of the variables. Second, partial correlation analysis controlling for price returns is employed to remove price co-movement effects and extract pure funding rate signals. Finally, a high-low quantile grouping analysis (below the 25th percentile and above the 75th percentile) is conducted to examine whether directional consistency deviates from randomness. The results indicate
that funding rates exhibit significant right-skewness and fat-tailed characteristics. After controlling for price factors, the full-sample linear correlation between funding rates and U.S. equity futures is weak, suggesting they are not stable predictors under normal conditions. However, in tail scenarios, Bitcoin and Ethereum demonstrate asymmetric and significant linkages with distinct U.S. equity sectors, confirming the high regime dependency of cross-market transmission via funding rates. This study suggests that financial institutions and investors should view funding rates as "state indicators" for monitoring extreme leverage risks and recommends that future research explore this topic with higher-frequency data or broader samples.

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