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買賣價差之分解-TAIFEX與SGX-DT之比較

Decomposition of Bid-Ask Spreads-The Comparison of TAIFEX and SGX-DT

摘要


本研究探討台指期貨契約於TAIFEX與SGX-DT兩個不同交易機制的市場中,其價差成份之大小。透過LSB(1995)與Glosten and Harris(1988)兩個模型的價差分解,本研究發現台指期的逆選擇相對較小,而摩台指的逆選擇則相對較大;在訂單處理成本方面,透過訂單持續性的影響,推論在集合競價的交易制度下較容易產生將大交易切割成數筆小交易的情形,故在訂單處理成本固定的條件下,台指期每單位的訂單處理成本比較大,而摩台指的訂單處理成本則較小。在日內型態方面,摩台指與台指期的日內價差型態皆呈現U型,尤其以開盤後的第一個時段有較大的價差;在逆選擇的日內型態方面,摩台指大致上於開盤時有較大的逆選擇,而台指期則於開盤與收盤時有較小的逆選擇;在訂單處理成本的日內型態方面,摩台指於收盤時有較大的訂單處理成本,台指期則於開盤與收盤有較大的訂單處理成本,故呈現明顯的U型。

並列摘要


Abstract: This study explores empirically the components of bid-ask spreads and their intraday patterns for the Taiwan stock index futures contracts traded on the SGX-DT and TAIFEX. Using both LSB and Glosten and Harris's models, this study finds that the adverse information component is larger, and the order processing cost component is smaller on the SGX-DT than on the TAIFEX. For both contracts, the intraday spreads follow a U-shaped pattern. The adverse information cost is larger at the opening of a trading day for the SGX-DT whereas the adverse information cost of TAIFEX shows a reverse U-shaped pattern during a day. The order processing cost is larger at the closing of a trading day for the SGX-DT whereas the order processing cost of TAIFEX shows a U-shaped pattern during a day.

參考文獻


Affleck-Graves, J.,Hedge, S. P.,Miller, R. E.(1994).Trading Mechanisms and the Components of the Bid-Ask Spread.The Journal of Finance.49,1471-1488.
Anderson, T. G.,Bollerslev, T.,Das, A.(2001).Variance-Ratio Statistics and High-frequency Data: Testing for Changes in Intraday Volatility Patterns.The Journal of Finance.56,305-327.
Brock, W. A.,Kleidon, A. W.(1992).Periodic Market Closure and Trading Volume: A Model of Intraday Bids and Asks.Journal of Economic Dynamics and Control.16,451-489.
Brockman, P.,Chung, D.Y.(1999).Bid-Ask Spread Components in an Order-Driven Environment.The Journal of Financial Research.12,227-246.
Brocks, R.,Masson, J.(1996).Performance of Stoll`s Spread Component Estimator: Evidence from Simulations, Time-Series, and Cross-Sectional Data.Journal of Financial Research.19,458-476.

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