Simpler Better Market Betas
- Overview Information:
- Sample Use:
- $ make ; ./mkdistributable < crspsample.csv
|File Name ↓||File Size ↓||Date ↓|
|Makefile||200 B||2022-Feb-12 02:15|
|betas-2020.csv||106.7 KiB||2022-Feb-12 21:34|
|betas-2021.csv||124.5 KiB||2022-Feb-12 21:34|
|betas.csv.gz||27.3 MiB||2022-Feb-12 21:31|
|crspsample.csv||60.9 KiB||2022-Feb-12 01:11|
|csv2sasstata.R||859 B||2020-Aug-18 20:53|
|fregr.cc||4.9 KiB||2020-May-16 19:11|
|fregr.hh||1.4 KiB||2022-Feb-12 01:17|
|mkblock.R||1.2 KiB||2020-Jul-09 03:04|
|mkblock.Rout||4.1 KiB||2020-Jul-09 03:07|
|mkdistributable||51.0 KiB||2022-Feb-12 21:30|
|mkdistributable-post.R||424 B||2022-Feb-12 21:34|
|mkdistributable-post.Rout||1.1 KiB||2022-Feb-12 21:34|
|mkdistributable.cc||8.2 KiB||2022-Feb-12 18:13|
|mksd-by-permno.R||2.9 KiB||2020-Jul-09 22:44|
|mksigma.cc||4.6 KiB||2020-Jul-09 22:44|
|snippet.R||602 B||2020-Jul-09 19:45|
|winsrel-fast.R||1.5 KiB||2020-Jul-09 19:43|
|wuni.hh||1.2 KiB||2020-Jul-09 22:44|
The market-beta estimates are the result of a years-long academic study. These bswa32 market-beta estimates are known to be far better than those from Bloomberg-Merrill-Lynch (Capital IQ or Yahoo-Finance or Google-Finance), Vasicek, Dimson, industry, or any other market-beta estimate when it comes to forecasting future OLS betas (over the next 1 to 12 months, and beyond). Note that regardless of econometric estimator, it is this future not-yet-known to-be-realized OLS beta that most investors care about, because it measures the to-be-realized hedge against market-factor risk. (The lagged OLS beta is not as good a predictor of its own future self as the bswa32 estimator.)
To accomplish its performance, the bswa market-beta estimator does three things:
For more detail, please confer https://ssrn.com/abstract=3371240.
The leap to think this risk should influence expected returns makes sense but it is a leap that is not supported by the data. Nevertheless, beta is useful to improve portfolio performance, but in a portfolio optimization context through the second moment, not through the first moment.
The occasionally-provided standard-deviation estimates, sd0111 are very good estimates of the 1-month ahead plain standard deviation. If someone can find a simple predictor of the one-month ahead plain standard deviation for the CRSP universe that is economically better, please let me know. (No intra-day data and/or implied vol-based estimators, please, because this data neither covers enough securities nor is sufficiently widely available.)
In-time means the estimates are calculated with data only up to this point in time. No future data has been used.
The estimates are forecasts of the 1-12-months ahead plain OLS market-betas (and plain standard deviations). That is, they are noisy estimates of the true but unknown prevailing market-betas and plain standard deviations at the end of the quoted month.
Although the database contains market-beta estimates early on (i.e., in months with as-of-yet few daily return observations), it is advisable not to use market-betas when they are based on too few returns. A good filter is to use only months that also have standard-deviation observations in the database. The latter requires at least one year's worth of data in order not to be set missing. This helps with market-beta reliability.
The betas.csv.gz file has too many lines to fit into excel, but it will read fine into R.
tic, permno, yyyymmdd, n, bswa32 AAC, 14944, 20211231, 1801, 0.654 AAMD, 85390, 20211231, 6111, 1.548 AAME, 15579, 20211231, 25227, 1.187 AAN, 20062, 20211231, 279, 1.127 AAP, 89216, 20211231, 5067, 1.192 ...