淡江大學機構典藏:Item 987654321/73942
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    Title: 各類投資人買賣不平衡對於市場雜訊的影響
    Other Titles: The effect of investors' order imbalance on trading noise
    Authors: 吳兆元;Wu, Chao-Yuan
    Contributors: 淡江大學財務金融學系碩士班
    林蒼祥
    Keywords: 雜訊;積極委託單不平衡;消極委託單不平衡;Noise;Aggressive order imbalance;Non-aggressive order imbalance
    Date: 2011
    Issue Date: 2011-12-28 17:35:59 (UTC+8)
    Abstract: 本研究利用高頻率的日內資料,研究台灣股票市場當中,外資、散戶、投信基金、其他法人與自營商等五類投資人,其買賣不平衡的交易行為對市場雜訊的日內關係。本研究所使用的資料,為台灣證交所所提供的委託檔、揭示檔與成交檔等資料。其中,利用委託檔配合揭示檔可以計算出積極的委託單不平衡與消極的委託單不平衡,而利用揭示檔,並使用Hu(2006)的方法來估計股票報酬波動中含有雜訊的部分,並分析使用積極的委託單與消極的委託單所隱含的資訊,並從結果判斷市場上的交易者哪些是資訊交易者以及那些屬於雜訊交易者或是流動性交易者。
    實証結果顯示,成交時間的減少代表著資訊流入,以至於對於雜訊以及波動率影響更為劇烈,使用積極委託單的外資、散戶與自營商會減少市場雜訊的產生,平均而言較能精確預測未來市場價格走勢,為資訊交易者,而使用消極委託單的散戶與自營商會增加市場雜訊的產生,並會造成市場價格的反轉,顯示為雜訊交易者。
    This paper uses high-frequency intraday data to discuss the dynamic relationship of the effect of order imbalance on the market trading noise from five categories investors-foreign investors, individual investors, mutual fund, other domestic institution investors and dealers in Taiwan stock market. We use the limit order book, display data and transaction data from TWSE in 2005 to 2006. We can calculate aggressive order imbalance and non-aggressive order imbalance through limit order book and display data. Then we use display data to measure market trading noise and volatility by Hu(2006) and analysis the information content of the aggressive orders and non-aggressive orders. And use this result to determine whether investors are informed traders, noise traders or liquidity traders.
    The empirical result indicates that decreasing the transaction time implied the information inflow and will increase the volatility of noise and volatility. The foreign investors, individual investors and dealers which use aggressive orders will decrease market noise and can forecast the market price movements accurately are informed traders. The individual investors and dealers which use non-aggressive orders will increase market noise and will cause market price reversion are noise traders.
    Appears in Collections:[Graduate Institute & Department of Banking and Finance] Thesis

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