2020 Stock Market Crash

Summary

Between the 19th of February, 2020, and the 23rd of March, 2020, the S&P500 (^GSPC) fell from 3,386.15 to 2,237.40, using adjusted closing prices. It subsequently climbed back to 3,276.02 on the 22nd of July, 2020. Some people seem to think it will keep going. I expect a massive crash.

To predict the upcoming (?) 2020 stock market crash, I propose examining the market using three techniques:

• Historical crash analysis
• Price-to-earnings (or revenue, etc.) analysis that attempts to factor defaults
• Extrapolating based on the market-to-economy relationship

I could also employ a pure chartist approach, perhaps to give the counterfactual.

S&P 500 data

As much as I love the Dow, it accounts for about 25% of the economy, whereas the S&P500 accounts for around 80%. So I'll likely use the S&P500. I'll download both from Yahoo:

• https://finance.yahoo.com/quote/%5EGSPC/history?period1=157766400&period2=1595548800&interval=1d&filter=history&frequency=1d
• https://finance.yahoo.com/quote/%5EDJI/history?period1=157766400&period2=1595548800&interval=1d&filter=history&frequency=1d

COMPUSTAT data

COMPUSTAT updates its fundamentals quarterly and monthly security files daily. I did a pull of the entire fundamentals quarterly database from 2015-01 to 2020-07. It has close prices, as well as highs and lows. I pulled close, as averaging highs and lows seems like it might be skewed given the context (especially over short time periods).

Historic Crashes

Data before the 1980s probably isn't useful. It was a different world back then, both in terms of globalization and in terms of how stock markets worked. So, I'll start with the 1987 crash and go forward from there. I'm going to suggest three classes of crash, like hurricanes:

Class	Description
1	Flash crashes and other short-term market anomalies
2	Short to medium term economic disturbances that are limited to a sector
3	Economic crisis

My starting list comes from a list of stock market crashes.

Using the largest decline on the Dow of the period as the crash day gives:

Data driven approach

Identify crashes as using the largest single-day declines on the DJIA:

Date	Adj Close	Volume	SingleDayChange
10/19/1987	1738.73999	87230000	-22.6%
10/26/1987	1793.930054	35420000	-8.0%
1/8/1988	1911.310059	27440000	-6.9%
10/13/1989	2569.26001	37620000	-6.9%
10/27/1997	7161.200195	91830000	-7.2%
8/31/1998	7539.069824	117890000	-6.4%
4/14/2000	10305.76953	267580000	-5.7%
9/17/2001	8920.700195	565600000	-7.1%
9/29/2008	10365.4502	385940000	-7.0%
10/7/2008	9447.110352	362520000	-5.1%
10/9/2008	8579.19043	436740000	-7.3%
10/15/2008	8577.910156	374350000	-7.9%
10/22/2008	8519.209961	348840000	-5.7%
11/5/2008	9139.269531	264640000	-5.0%
11/19/2008	7997.279785	350470000	-5.1%
11/20/2008	7552.290039	528130000	-5.6%
12/1/2008	8149.089844	321010000	-7.7%
8/8/2011	10809.84961	479980000	-5.5%
3/9/2020	23851.01953	750430000	-7.8%
3/11/2020	23553.2207	663960000	-5.9%
3/12/2020	21200.61914	908260000	-10.0%
3/16/2020	20188.51953	770130000	-12.9%
3/18/2020	19898.91992	871360000	-6.3%
6/11/2020	25128.16992	647780000	-6.9%

Grouping them using 6-month windows gives 9 crashes:

• 1987/1988: 3 obs (including largest)
• 1989: 1 obs
• 1997: 1 obs
• 1998: 1 obs
• 2000: 1 obs
• 2001: 1 obs
• 2008: 9 obs
• 2011: 1 obs
• 2020: 6 obs (and counting, including second and third largest)