最大報酬個股之市場效率收斂性

Abstract

證券市場是否具有效率性，長期以來一直是學者們爭論的議題；而近年來諸多關於市場異常、行為投資學、投資心理學等之實證研究，卻也似乎與市場效率之說產生了矛盾。市場所呈現的樣貌即為所有投資人行為交互影響之總和，大部分的學者皆主張，這個總和的效果，足以將市場推升至效率的境界；然此推進的過程並非瞬間達成效率，本研究即致力於觀察、捕捉最大報酬個股之市場效率收斂過程。 首先我們以多元線性回歸模型檢驗同期或前期之買賣單不平衡對報酬率的影響。實證結果顯示，同期之買賣單不均衡對報酬率有顯著之正向影響；前一期的買賣單不平衡，對報酬之顯著影響，在沒有考慮當期時，其影響方向大抵為正，而在考慮當期後，前期買賣單不平衡對報酬的影響為負向關係。接著我們以GARCH(1,1)模型觀察同期買賣單不平衡對報酬率的影響，結果顯示其間有正顯著之關係。不論是線性回歸模型、抑或GARCH(1,1)模型，我們皆可觀察到市場效率之收斂過程，即隨著時間範圍的拉大，買賣單不平衡對報酬的影響力逐漸下降。 另外，我們也以GARCH(1,1)模型觀察股價波動性與買賣單不平衡之間的關係，研究顯示其關係並不顯著，表示場內專家(Specialist)對股價波動性的控制良好。接著，經由簡單線性回歸模性之實證顯示，小型股效果僅存在於多元線性回歸模型之買賣單不平衡變數之中，因此我們將其解釋為波動性影響的效果，而非小型股本身之效果。 最後，我們以買賣單不平衡為指標，嘗試發展出一套交易策略，雖然報酬率為正值，但仍無法擊敗最大報酬個股之原始報酬率。

Market efficiency has been a debated topic in the field of finance for a long time, as a great amount of research on the topic of market anomalies and behavioral finance linked to psychology has been revealed. These conflicting topics can be reconciled by the concept of “aggregation.” All kinds of investors gathering together will push the market toward efficiency to the extent that no one could earn an abnormal profit by any trading strategies continuously. It is intuitive that efficiency cannot happen instantaneously in the real world. The central purpose of our study is to investigate the convergence process toward efficiency of daily top gainers in the stock market. First of all, we examine the relation between returns and contemporaneous as well as lagged order imbalances by a multi-regression model. The empirical result shows that the contemporaneous imbalances have a significantly positive impact on returns, and the lagged-one imbalances also have a positive impact on returns disregarding the contemporaneous imbalances. But once we condition on the contemporaneous imbalances, the impact of the lagged-one imbalances on returns generally turns to be negative. Besides, we observe a positive relation between contemporaneous imbalances and returns by the use of a GARCH(1,1) model. The convergence process toward efficiency, whether in the multi-regression model or the GARCH(1,1) model, is observable. That is, the explanatory ability of order imbalances decreases as the time interval increases. In addition, we examine the relation between volatility and order imbalances by a GARCH(1,1) model. The relation is not strong enough, suggesting that market makers do have a capable ability to control volatility of price movements. Moreover, we perform a simple regression model to investigate whether there is any relation between market capitalization and order imbalances. It is significant only in the imbalance variables obtained from the OLS regression model, showing that the effect comes from volatility but not small firm effect itself. Finally, we try to build a trading strategy based on the indicator of order imbalances. This trading strategy earns a positive profit but still cannot beat the original open-to-close return of top gainers.