Empirical Regularities in Stock Market Crashes
Jump to navigation
Jump to search
| Academic Paper | |
|---|---|
| Title | Empirical Regularities in Stock Market Crashes |
| Author | Ed Egan |
| Status | Working paper |
| © edegan.com, 2016 | |
This paper develops results discovered in my analysis of the 2020 Stock Market Crash, which spawned a series of Op. Ed. submissions.
Abstract
From version 1.2:
I define a stock market crash as the period from an index's prior peak until its recovery. Then measures of its scale are very highly correlated. These correlations suggest that crashes belong to well-defined categories and become increasingly predictable as they progress. Furthermore, being in a crash is then the default state of U.S. stock markets.
Files
The TeX files, pdfs, and general development files are in:
E:\projects\stockmarketanalysis
Key files include:
- StockMarketAnalsisV1-2-SSRN.tex The source of the version posted at https://ssrn.com/abstract=3679630
- CrashesV2.xlsx The main excel file for building tables and figures
- Analysis.sql The SQL file for loading and processing the source data
- Quick.do (and Time.do) The statistical analysis code
The data files are in:
Z:\stockmarket
The dbase is stockmarket.
Submission History
The paper was submitted as follows:
- Economic Letters: Submitted on Aug 23, 2020 ($65 fee). Desk rejected by Joao F. Gomes on Aug 31. ("...while of some interest...")
The next obvious choices are:
- Finance Research Letters: $150 fee, 2,500 word limit, Cite Score 3.8, Impact Factor 2.02, 2nd quartile, https://www.sciencedirect.com/journal/finance-research-letters
- Economic Bulletin: No fee?, 7-page limit, H-index 25, Impact factor 0.31, 3rd quartile, http://www.accessecon.com/pubs/eb/
