证券市场的期现基差与流动性

Futures-cash Basis and Liquidity in Security Market

2015年股市危机期间中国证券市场的流动性尽失,甚至一度出现"千股跌停"这一罕见情形,监管层随后对股指期货和股市现券卖空进行最为严厉的限制,这一系列举措给实证研究带来一个很好的拟自然实验场景,用来研究中国证券市场的流动性和期现基差问题。选取中国沪深300股票指数和沪深300股指期货的5分钟高频数据和日度低频数据为样本,以经典的金融学套利交易理论为基础,对2015年股灾监管前后划分样本区间,使用VAR模型和OLS回归对市场的流动性和期现基差进行分析。研究结果表明,期现基差是导致套利交易的原因,进而造成订单不平衡,从而减弱了流动性。期现的正向基差比负向基差对流动性的影响大,且这种非对称效应在极端行情下差别更大;当期现基差为正时,套利者可以很容易的卖空股指期货并做多现货,这种订单的不平衡引起现货市场的流动性增加,但是一旦出现负向期现基差,很难卖空股票现货同时做多股指期货,导致流动性下降;高频和低频数据的结论都证明正向期现基差会引发套利,从而使流动性增加。在股指期货和融券交易被限制后,套利交易难以有效进行,期现基差为负,无法通过套利交易增加流动性,这可能是造成2015年股市危机期间流动性尽失的一个原因。研究结论不仅对2015年中国股市危机期间流动性缺失提供了一种解释,同时也对监管机构如何应对股票市场危机具有启发意义。

As demonstrated by the ＂Thousands of stocks steep see-off leading to a trading halt＂, the Chinese securities market experienced very serious liquidity issues during the 2015 market crash, and that had led its regulatory agencies to implement a seties of restrictions on the stock market that had never witnessed in Chinese stock trading history. The unprecedented 2015 experience serves as a quasi natural experiment and can be used to study the futures-cash basis and liquidity relationship of the Chinese securities market. Using the 5-minute high frequency and daily low frequency CSI 300 stock index and CSI 300 index futures data and based on the arbitrage trading theory, we apply VAR model and OLS method to investigate the futures-cash basis and liquidity issue in the Chinese securities market, in a subsample approach that splits the samples in pre- and post- the crisis regulation. The main findings are as follows. First, futures-cash basis is the reason of the arbitrage trading. It causes the order imbalance, and weakens the market liquidity. Second, positive futures-cash basis influences the market liquidity more than negative futures-cash basis can do and this asymmetry effect is stronger in extreme periods. This is so because when the futures-cash basis is positive, arbitrageurs can easily short the stock index futures and long the stock spot, and the order imbalance will increase spot market liquidity meanwhile. However, when the futures-cash basis is negative, it is hard to short the stock spot and long the stock index futures because of the decline in liquidity. The finding that positive basis could trigger the arbitrage mechanism and an increase in securities market liquidity holds in the case of high frequency data as well as the case of low frequency data. Third, when stock index futures and short-sellings were restricted, arbitrage became difficult, which makes the futures-cash basis ineffective for improving the security market liquidity. This can be an explanation for the lack of liquidity during the stock market crash period of 2015. Our findings provide an explanation for the loss of liquidity in the Chinese stock market crash in 2015, and it is expected that these findings are to serve as potentially useful information on how to best deal with securities market crisis tbr regulatory agencies.