Interpreting Eviction Filings as a REIT Return Signal
Summary
The document describes an exploratory analysis linking eviction data with a REIT index. It reports regressions at weekly, monthly, and yearly frequencies, with the strongest stated fit at the yearly frequency. It also describes a backtest that used an autoregressive projection of eviction counts, selected weeks in the highest observed eviction range using out-of-sample data, and rebalanced the portfolio monthly. The reported Sharpe ratios were higher for the eviction-filtered approach than for the weekly comparison, prompting the author to ask why elevated filings might coincide with stronger REIT returns.
A possible explanation offered is that court filings may precede judgments and tenant turnover, which could eventually restore rent collection or bring in new tenants. This is speculation, not a demonstrated causal mechanism. The account provides limited methodology and no details on controls, transaction costs, robustness checks, or the construction of the index and signals, so the reported associations do not establish that eviction filings predict returns reliably.
Key ideas
- The analysis compares eviction measures with REIT index returns across several time frequencies.
- The described strategy uses projected eviction counts to filter periods and is rebalanced monthly.
- The author suggests tenant turnover and resumed rent payments as possible explanations for the observed association.
- The reported regression and Sharpe results are exploratory and do not establish causation.
- Missing methodological detail limits conclusions about robustness and investability.
Tags
Full text
# Why does an increase in eviction court filings result in an increase in REIT returns? # Why does an increase in eviction court filings result in an increase in REIT returns? I'm a data mining developer working for a company that wholesales eviction record data on a national level. I was recently assigned a project to build a program to mine all county courts in Oklahoma for eviction data. I was just curious if this data could be used for investment research purposes and the results of a linear regression kinda stunned me. It only has a 0.046 R^2 on a weekly timeframe for $ value of evictions vs returns of a REIT Index and 0.16 R^2 on a monthly timeframe and 0.81 R^2 on a yearly for eviction filing counts and returns. When a backtest was built by taking the AR model projected weeks evictions based on previous week(s) eviction, and filtering only the weeks with the top 5% of evictions where recorded (based on OOS data.) The portfolio was rebalanced monthly. The Sharpe ratio was 0.6013 vs 0.4855 on a weekly. 25% higher! WOAH! Why would it do this? Here is weekly return vs $ value of evictions And Here is monthly return vs eviction filings Any idea behind why more evictions means better returns? I suspect It may have to do with the fact that evictions can take up to 90 days before a forcible entry and detainer is court ordered which means lost revenue. Perhaps this means that Judgments issued are either payed or new paying tenants are allowed to move in who often pay first months rent, a deposit, and sometimes second months rent. I'm not really an expert on real estate however, It took me 5 months to master all the terminology used in courts and I still feel a little lost. Just to clarify, my question is: Any idea behind why more evictions means better returns on REIT Indexes? PS Pardon my grammar and spelling, I'm kinda dumb and not really sure how I got my job given I dropped out of highschool.
Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.