本文利用最小生成樹 (minimum spanning tree) 和三角最大過濾圖 (triangulated maximally filtered graph) 方法，觀察在2005年底至2024年初，東南亞中央銀行 (菲律賓、新加坡、印尼、馬來西亞和泰國) 與9個國家中央銀行情緒指標的相關性。本文利用中央銀行的貨幣政策聲明或決策建構情緒指標，實證結果顯示在東南亞五國情緒指標網絡內，馬來西亞最可能為情緒指標中心，然而東南亞央行情緒指標網絡隨者國家數目地增加，馬來西亞的重要性下降，顯示馬來西亞的影響為地區性。此外，我們觀察到菲律賓、馬來西亞和泰國的情緒指標與歐洲央行較相近；印尼的情緒指標則與美國央行較相近；新加坡與歐洲央行和美國央行皆相關。東南亞情緒指標除了與歐美相關，我們也觀察到東南亞央行情緒指標與亞太區域相關 (如：印度、澳洲與韓國)。

I explore Southeast Asia central banks sentiment connection between December, 2005 and March, 2024. I choose 5 Southeast Asia (Indonesia, Malaysia, Philippines, Thailand and Singapore) and 9 central banks and construct sentiment indexes. I use minimum spanning tree and triangulated maximally filtered graph method to construct Southeast Asia central banks network. I find Malaysia is the most likely to be the sentiment center in 5 Southeast Asia central banks sentiment network. When adding other countries in sentiment network, Malaysia’s sentiment correlations with the other Southeast Asian countries become weaker, which implies Malaysia effect is regional. Besides I find Malaysia, Philippines and Thailand sentiment indexes are more correlated with European Central bank, Indonesia sentiment index is more correlated with Fed and Singapore is correlated with European Central bank and Fed. Southeast Asia sentiment indexes have the correlation with European Central Bank, Fed and Asia-Pacific countries (ex. India, Australia and Korea).

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