本文探讨了在市场之间联系愈发紧密情况下，针对单一市场"围堵"式的临时监管限制措施可能引发的跨市场风险。以2015年股指急剧下跌后对股指期货交易加大管制为背景，本文发现，一系列限制措施出台后，股指期货市场出现整体流动性萎缩，现货市场则出现了较为显著的收益率与成交量的正反馈效应，造成极端下跌事件的自我实现。本文认为，对股指期货交易的过度限制，使得机构投资者在下跌行情中无法通过期货对冲风险，加剧了现货市场抛售压力，引发了现货市场极端下跌事件。因此，监管层在设计和运用监管限制时应当审慎、全面分析目前的市场关联结构变化，避免政策的失灵和不恰当政策带来的风险。
In this essay, the cross-market risk events caused by temporary regulatory restrictions are discussed under the circumstances that markets are linked much more closely than ever before.
Over the past three decades, financial market risk events appeared one after another. Especially when facing sharp market crashes, financial regulators tend to urgently introduce a series of stringent regulatory restrictions to stabilize the market. However, it has been found that these temporary control measures can stabilize part of the market in the short term but may have a spillover effect on the associated market and lead to greater turbulence due to the tightening of financial markets, and also damage the quality of financial markets as a result.
During the mid-2015 market crash in China, the China Financial Futures Exchange adjusted three times during a short period (August 25, August 28 and September 2) the exchange margin, intraday open position and intraday close position fee, which aimed at controlling over-speculation trades. However, the trading restrictions on stock index futures were likely to further reduce the spot market liquidity, increase the spot market selling pressure, which may cause the formation of positive feedback effect, thereby increasing the futures and spot market abnormal fluctuations.
Based on this view, the VAR model is used to study the positive feedback effect between the CSI 300 index yield (CSI 300 stock index futures yield) and the volume. In the year 2015, a total of 23 intraday extreme market crash events are selected as the research sample (including 16 events before stock index futures trading restrictions, and 7 events afterwards).
Focusing on the strict trading limits implemented on the stock index futures market during 2015 market crash, it is found that liquidity shrank in the stock index futures, and a significant positive feedback between return and order flow lead to the self-actualization of extreme events. Institutional investors fail to hedge risk via stock index futures due to the strict trading limits, which strengthens the selling pressure on stock market and causes the market crash.
Therefore, regulators should comprehensively analysis the structure changes in the current market when using regulatory restrictions to avoid policy failure.
[1] Amihud Y, Mendelson H. Liquidity and the 1987 stock market crash[J]. Journal of Portfolio Management,1990,16(3):65-69.
[2] Grossman S J, Miller M H. Liquidity and market structure[J].Journal of Finance,1988, 43(3):617-633.
[3] Tambakis D N. Feedback trading and intermittent market turbulence[J].Quantitative Finance,2008, 9(4):477-489.
[4] Cohen B H, Shin H S. Positive feedback trading under stress:Evidence from the US treasury securities market[R].Working Paper,Bank for International Settelments,2002.
[5] 李红权,汪寿阳,马超群.股价波动的本质特征是什么?——基于非线性动力学分析视角的研究[J].中国管理科学,2008,16(5):1-8.
[6] 陈国进,张贻军,王磊.股市崩盘现象研究评述[J].经济学动态,2008,(11):116-120.
[7] Ozdenoren E, Yuan K. Feedback effects and asset prices[J].Journal of Finance,2008, 63(4):1939-1975.
[8] Allen F, Gale D. Stock-Price Manipulation[J].Review of Financial Studies, 1992,5(3):503-29.
[9] 冯芸,施杰,董珊珊.操纵性投机行为对金融市场质量的影响:基于计算机仿真平台的研究[J].系统管理学报,2016,25(3):422-438.
[10] 李少平,顾广彩.中国证券市场正反馈交易的实证研究[J].系统工程,2007,(9):111-115.
[11] 张恩众.正反馈交易对证券市场的影响——来自上海证券市场的证据[J].山东社会科学,2009,(10):83-86.
[12] Shiller R J,Kon-Ya F,Tsutsui Y. Investor behavior in the October 1987 stock market crash:Survey evidence[J].Journal of the Japanese and International Economics,1991,5(1):1-13.
[13] Hong H, Stein J C. Differences of opinion, short-sales constraints, and market crashes[J].Review of Financial Studies,2003, 16(2):487-525.
[14] Brunnermeier M K, Abreu D. Bubbles and crashes[J].Econometrica,2003, 71(1):173-204.
[15] Huang J, Wang Jiang. Liquidity and market crashes[J].Review of Financial Studies,2009, 22(7):2607-2643.
[16] 肖辉,吴冲锋.现货市场与期货市场微观结构比较研究[J].管理科学学报,2009,12(1):93-100.
[17] 袁怀宇.金融危机下卖空管制对证券市场的影响——以台湾市场为例[J].中国证券期货,2010,(2):9-11.
[18] Goldstein M A, Kavajecz K A. Liquidity provision during circuit breakers and extreme market movements[R].Working Paper,White Ctr for Financial Research,New Orleans,2000.
[19] Goldstein M A, Kavajecz K A. Trading strategies during circuit breakers and extreme market movements[J].Journal of Financial Markets,2004,7(3):301-333.
[20] 刘睿智,周勇.期现货市场订单流动性层面的"遛狗效应"——基于交易量刻度的高频交易数据研究[J].中国管理科学2016,24(4):19-26.
[21] 曹栋,张佳.基于GARCH-M模型的股指期货对股市波动性影响的研究[J].中国管理科学,2017,25(1):27-34.
[22] Hasbrouck J. Measuring the information content of stock trades[J]. Journal of Finance,1991,46(1):179-207.
[23] Moazzami B, Dadgostar B. Return and volume and the 2008 market crash[J].Journal of Applied Business & Economics, 2013,15(2):33-37.
[24] Mu Guohua, Zhou Weixing, Chen Wei, et al. Order flow dynamics around extreme price changes on an emerging stock market[J].New Journal of Physics, 2010,12(7):1653-1655.
