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Market Microstructure Daniel Sungyeon Kim. Crashes. Q : Why are we concerned about volatility ?. 2008 Crash. Q: How much did the stock market drop on Sept 30, 2008?. 2008 Crash. Q: Why?. Bubbles , Crashes, and Circuit Breakers.
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Crashes Q: Why are we concerned about volatility?
2008 Crash Q: How much did the stock market drop on Sept 30, 2008?
2008 Crash Q: Why?
Bubbles, Crashes, and Circuit Breakers • Crashes are also a good laboratory: If we learn why prices move in a crash Why prices move normally • As we look at several pieces of evidence on the crashes of 1929, 1987, and 2010, ask yourself how big was the contribution of: • News • Investor sentiment = irrational overreaction • Trading strategies that lead to selling during a price drop • Mechanical breakdowns
Facts of the 1929 Crash • DJIA: • Oct 28 = -13% • Oct 29 = -12% (roughly -25% in two days) • Oct 30 = +12% • Oct 31 = +3% • Then 3 year decline to Great Depression low on July 8, 1932 • Proceeded by 300% increase in 5 years
Facts of the 1929 Crash Q: Looking just at 1924 – 1932, what does it look like?
Why Did the 1929 Crash Happen? Q: What are the possible explanations?
Why Did the 1929 Crash Happen? Q: What is “borrowing on margin”?
Why Did the 1929 Crash Happen? Q: What’s wrong with selling stocks to meet margin?
Facts of the 1987 Crash • DJIA: • Oct 19 = -23% (largest one day loss) • Oct 20 = +2% • Oct 21 = +10% • Preceded by: Oct 16 = -5% • Whole prior week = -9% • Cum loss from high = -17% • Preceded by: 44% increase from start of year • All of 1987 = +2%
Why Did the 1987 Crash Happen? Q: What is the most possible explanation?
Why Did the 1987 Crash Happen? Q: What is portfolio insurance?
Why Did the 1987 Crash Happen? Q: Printer backlog seems quaint. Why didn’t they just electronically route the order?
Roll Fully addresses that the 1987 crash was worldwide, not just the US
Correlations • We are going to look at correlations between country stock returns – recall how correlations work: -1 0 +1 Perfectly Independent Perfectly Opposite Together
Correlations Between Stock Markets • Typical correlation between country stock returns in normal times is low (.2 - .4 range) -1 0 +1 X X Perfectly Independent Perfectly Opposite Normal Crash Together
Shiller Q: What did Shiller find out about news in 1929 crash?
Shiller • Oct 24 = the prior Thursday: • DJIA dropped 12.9% at mid-day – if this was the full-day return, it would have been the largest crash in history • But it recovered to end at 2.1% drop by end of day • Oct 28 Wall Street Journal editorial: “DON’T PANIC!” • Oct 23: No bad news, but a6.3% drop • And recent smaller drops • Conclusion: Negative bubble = earlier drops lead to a larger drop
Shiller Evidence on the 1987 Crash Q: Shiller surveyed investors immediately after 1987 crash. What did he find out?
Shiller Evidence on the 1987 Crash • Presidential commission (the Brady commission) emphasized the role of portfolio insurance = trading strategy • Conclusion: Negative bubble = earlier drops lead to a larger drop
Role of the News Media Shiller examines the role of news media in propagating negative bubbles The media has an economic self-interest in emphasizing sensational things (crime stories, car wrecks, etc.) The media heightened attention to the stock market = “pay attention because something is going on” Thus, the media helps generate feedback from one drop to the next Sometimes the media predicts = “something might happen” (and in this case it did)
Front page article in Wall Street Journal on Oct 19, 1987 suggested the market was overvalued and made an explicit parallel to the 1929 crash
Role of the News Media Shillerconclusion: News media helps propagate negative bubbles
Flash Crash Major stock market event on May 6, 2010 = “Flash crash”
Flash Crash Were there any news events on the day of May 6th? European debt crisis Concern that Greece might default on its debt Euro was declining against the $ and Yen Volatility was up 20%
Flash Crash Were there any major news events from 2:30 – 3:00?
Flash Crash According to the report, why did the flash crash happen? “Liquidity mismatch” – possible withdraw of liquidity No real answers Ruled out: “fat finger” error, computer hacking, or terrorist activity
Flash Crash Timeline Main cause 2:32 pm: a large fundamental trader (a mutual fund complex) initiated a sell program to sell 75,000 E-Mini stock index futures contracts (valued at $4.1 billion) as a hedge = trading strategy Used a sell algorithm to execute via automated execution Trading program feed orders into the E-Mini market without regard for price or time Previous occasion took more than 5 hours to execute this large of a trading program This time executed everything in just 20 minutes High frequency traders (“HFTs”) and other intermediaries initially absorbed this selling
Flash Crash Timeline Liquidity crisis in E-mini 2:41 – 2:44 pm: E-Mini down 3% Same time: Arbitrageurs transferred this selling pressure to equities by buying E-Mini contracts and simultaneously selling individual equities in the S&P 500 Index 2:45:13 – 2:45:27 pm: HFTs sold 27,000 contracts Buy depth (=bid depth) practically disappeared – fell to 1% of normal E-Mini down 5%