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2020 Stock Market Crash (view source)
Revision as of 12:42, 14 October 2020
, 12:42, 14 October 2020no edit summary
{{Project|Has title=2020 Stock Market Crash|Has Image=Trader-city-london-trading-stock-5129770.jpg|Has owner=Ed Egan|Has project output=Content|Has project status=Complete|Has sponsor=edegan.com|Has file locations=E:\projects\stockmarketanalysis}}This page details my exploration of data concerning the [[2020 Stock Market Crash]]. This work spawned a short-form academic paper, [[Empirical Regularities in Stock Market Crashes]], as well as a number of Op. Ed. submissions. I ultimately put [https://www.edegan.com/blog/the-pandemic-stock-market-crash-of-2020/ a lay-version of the historical crash analysis up on my blog].
==Summary==
Between the 19th of February, 2020, and the 23rd of March, 2020, the S&P500 ([https://finance.yahoo.com/quote/%5EGSPC ^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 crashretrenchment.
To predict the characteristics of the 2020 stock market crash, I propose examining the market using three techniques:
It loads the DJIA, the GSPC, and the crashes file. It will also load the COMPUSTAT pull.
===Results===
Readers interested in recreating the results in the blog post or paper will want the following data (note that most analysis uses the 'modern era' from 1985 to present, and so excludes the Wall Street Crash of 1929):
{| class="wikitable sortable" style="text-align:center; vertical-align:bottom;"
|- style="font-weight:bold;"
! Category
! style="text-align:left;" | Event
! Year
! Duration
! MarketsLost
! LargestDrop
! PcToDrop
! RateSpread
|-
| 1
| style="text-align:left;" | Friday 13th Mini-crash
| 1989
| 148
| 6
| 0.089
| style="vertical-align:middle;" | 0.524
| style="text-align:left;" | 0.91
|-
| 1
| style="text-align:left;" | Asian Contagion Mini-Crash
| 1997
| 130
| 6
| 0.133
| style="vertical-align:middle;" | 0.442
| style="text-align:left;" | 0.565
|-
| 1
| style="text-align:left;" | Chinese Stock Bubble
| 2007
| 39
| 1
| 0.058
| style="vertical-align:middle;" | 0.211
| style="text-align:left;" | 0.945
|-
| 1
| style="text-align:left;" | Flash Crash
| 2010
| 152
| 8
| 0.136
| style="vertical-align:middle;" | 0.311
| style="text-align:left;" | 1.16
|-
| 2
| style="text-align:left;" | Early 90s recession
| 1990
| 314
| 21
| 0.212
| style="vertical-align:middle;" | 0.192
| style="text-align:left;" | 1.097333333
|-
| 2
| style="text-align:left;" | Great Bond Massacre
| 1994
| 277
| 12
| 0.097
| style="vertical-align:middle;" | 0.152
| style="text-align:left;" | 0.641428571
|-
| 2
| style="text-align:left;" | The Bear Market
| 1998
| 159
| 10
| 0.193
| style="vertical-align:middle;" | 0.190
| style="text-align:left;" | 0.87625
|-
| 2
| style="text-align:left;" | August Fall
| 2011
| 214
| 13
| 0.168
| style="vertical-align:middle;" | 0.502
| style="text-align:left;" | 1.133636364
|-
| 2
| style="text-align:left;" | Stock Market Sell Off
| 2015
| 288
| 15
| 0.145
| style="vertical-align:middle;" | 0.641
| style="text-align:left;" | 1.214285714
|-
| 3
| style="text-align:left;" | Black Monday
| 1987
| 682
| 100
| 0.361
| style="vertical-align:middle;" | 0.054
| style="text-align:left;" | 1.018181818
|-
| 3
| style="text-align:left;" | Dot Com Crash
| 2000
| 1699
| 231
| 0.378
| style="vertical-align:middle;" | 0.410
| style="text-align:left;" | 0.934567901
|-
| 3
| style="text-align:left;" | The Financial Crisis
| 2008
| 1338
| 254
| 0.530
| style="vertical-align:middle;" | 0.253
| style="text-align:left;" | 1.40859375
|-
| 4
| style="text-align:left;" | Wall Street Crash
| 1929
| 6301
| 3484
| 0.892
| style="vertical-align:middle;" | 0.113
| style="text-align:left;" | 1.491754967
|}
If you want to run a [https://www.dummies.com/software/microsoft-office/excel/how-to-use-the-regression-data-analysis-tool-in-excel/ regression in excel], remember to install the Data Analysis Toolkit.
===Op Ed Submissions===
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).
[[Category:Blog Post]]
