Dynamic Relations between Order Imbalance, Volatility and Return of Top Losers Authors: Yong-Chern Su, Han-Ching Huang, Po-Hsin Kuo and Peiwen Chen (National Taiwan University) Discussant: Yin-Feng Gau (National Central University) NTU Finance Conference 2008 1
Summary l 61 daily “loser” stocks, TAQ database, 12/1/200512/31/2005 l Use GARCH(1, 1) to study the relation b/tw volatility and order imbalance l Use the regression of return on lagged order imbalance to study the predictability of returns l Use VAR of return and order imbalance to study the causal relation l Trading strategy based on order imbalance: buy if order imbalance is positive; sell if order imbalance is negative 2
Comments Where is the “story”? – better if focused on a few important themes l l l 1. 2. Contemporaneous relations b/tw 1) return (Rt) and order imbalance (OIt) : eq (1); Chordia and Subrahmanyam (2004) 2) volatility and order imbalance: eq (2); Chan and Fong (2000) Lagged relations b/tw 1) Rt and OIt, OIt-2, …, OIt-4 : eq(3); Chordia and Subrahmanyam (2004) 2) Rt and OIt-1, OIt-2, …, OIt-5 : eq(4); Chordia and Subrahmanyam (2004) causal relation (Granger, 1969; Chen and Wu, 1999) b/tw return and order imbalance 3 trading strategy based on the order imbalance
Questions about Data l Data frequency: daily or tick-by-tick? l l l P. 3: “the order imbalance is defined as daily net share volume …. How long dose “period t” in models span? If the estimation of models are based on “ intraday” data, how fine the data are? If using the intraday data, the intraday seasonality in volatility should be checked and adjusted Is there intraday seasonality in OIB? Why use the sample of “top loser”? Motivation? 4
Questions about Empirical Results 1. Is the same model (e. g. GARCH(1, 1)) fitted to all 61 stocks studied 2. should take care of the seasonality in intrady volatility, leverage effect, day-of-the-week effect 3. Table 2 shows for 40% of sample returns, coefficient of OIt is positive and significant in eq(2), whereas for 40% of sample, the coefficient of OIt is negative and significant in eq(2) How to judge the effect of OIt on volatility 4. As shown in Panel A of Table 6, three of four trading strategies earn negative returns, and one strategy obtains 1. 06% return. not substantial or significant enough for a profit, because the transaction costs and taxes are not considered yet 5
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