I have gathered some information from various studies with an overview and a brief explanation of each study in the link provided above. I have also used Chat GTP to extract a summary of most of the studies. In the English explanation, I have only used…“=GOOGLETRANSLATE(N4;“nb”;“en”)”
Yes, the “Description” column in the CZ tab of that file is just what I was looking for. Thank you!
TL;DR: The authors of this paper using Bootstrapping to get p-values along with the Benjamini-Hochberg Procedure (BH) to get a false discovery rate (FDR) correctly state that they get a different result from a paper using Bayesian analysis: Is There a Replication Crisis in Finance?
Both papers are ultimately about False Discovery Rates (FDR) so there is a true disparity in the results of the papers, I believe.
The latter paper has been sited frequently in the forum. I first became aware of it when Yvual mentioned it and he has mentioned it since as well as blogging about it I think:. E.g, in this thread: Why such a large discrepancy between backtesting and real-life results?. it is an interesting paper and I have also discussed it in the forum. I don’t mean to imply that Yuval or I endorse or use anything within the paper or what we might use if we do use some of it. Probably we find some similar lessons as well as some different lessons from the paper.
So which paper is right? Lots of good factors or surprisingly few?
One could probably explore this on their own with P123 data. The BH is not that hard to do. The bootstrapped p-value could be a little challenging. I am not sure that there is a Python library that does this (although there is a library in Scikit-Learn that gives confidence intervals using bootstrapping), but you can find multiple examples of code to do this with a google search. I believe R does this and a bootstrapped p-value could be obtained using an iterative approach over at JASP.
Here is a simple video by Stat Quest explaining getting a p-value using Bootstrapping: Using Bootstrapping to Calculate p-values!!! For someone on the forum who has sent me links about Stat Quest (you know who you are or if you have ever watched the Stat Quest videos) I cannot help but say: Bam!
Some Bayesian analysis can be found at JASP, PyMC3 with Python or over at R using the BEST program.
Jim
I’ve made a quick start in converting the descriptions to P123 factors (or what I understood from it). Took the 6 (edit: 26 now, will do more later) with the highest t-value , hope to add them all later.
https://www.portfolio123.com/app/ranking-system/409467
Results are not bad.
Thanks, Victor. That’s nice and helpful.
Thanks Victor. Very helpful.
I think the topic of this thread may have changed and I may be hijacking it a little. That’s cool and I like people changing the topics. My apologies if this is off topic now.
But the paper does talk about bootstrapped p-values which I find, personally, to be one of the most interesting parts of the paper.
AND I did get the code from ChatGPT which is consistent with the original post. The print out the below code (and a random factor) was P-value: 0.71199999999999996625
FWIW for those interested……
Code:
import numpy as np
import pandas as pd
observed_statistic = 0
Load data from file
df = pd.read_csv(‘~/Desktop/bootstrap.csv’)
data=df[[‘factor’]]
Define the function to calculate the test statistic (e.g. mean)
def test_statistic(data):
return np.mean(data)
Define the number of bootstraps to perform
n_bootstraps = 1000
Initialize an array to store the bootstrap replicates
bootstrapped_statistics = np.empty(n_bootstraps)
Perform bootstrapping
for i in range(n_bootstraps):
# Resample data with replacement
resampled_data = np.random.choice(data.values.flatten(), size=len(data), replace=True)
# Calculate test statistic for resampled data
bootstrapped_statistics[i] = test_statistic(resampled_data)
Calculate the p-value
#observed_statistic = test_statistic(data.values.flatten())
p_value = np.sum(bootstrapped_statistics <= observed_statistic) / n_bootstraps
Print the p-value
#print("P-value: ", p_value)
print("P-value: ", “%0.20f” % p_value)
Thank you!!!
I see that you have assigned different weights to the different nodes. How did you determine the weight of each node?
I took this list from a study, converted it, and sorted it.
Acronym | Economic category | R | t(R) | SD | SR | maxDD | Min | 0,05 | 0,95 | Max | Start | N |
---|---|---|---|---|---|---|---|---|---|---|---|---|
STreversal | Other | 35,56 | 13,989 | 24,316 | 1,462 | 50,364 | −36,964 | −4,485 | 14,123 | 79,534 | 10805 | 1,098 |
IO ShortInterest | Other | 34,32 | 4,803 | 45,799 | 0,749 | 70,314 | −58,515 | −17,895 | 24,4 | 46,499 | 29189 | 493 |
RD q | Profitability | 17,385 | 4,26 | 23,083 | 0,753 | 36,337 | −14,516 | −6,727 | 12,271 | 45,744 | 32539 | 384 |
IndRetBig | Momentum | 16,529 | 11,663 | 13,557 | 1,219 | 64,652 | −24,055 | −4,223 | 7,183 | 34,887 | 10805 | 1,098 |
ProbInformedTrading | Trading frictions | 16,034 | 4,325 | 16,159 | 0,992 | 27,94 | −25,799 | −5,687 | 7,995 | 15,767 | 30741 | 228 |
Frontier | Intangibles | 15,599 | 6,651 | 17,785 | 0,877 | 41,978 | −18,694 | −6,052 | 9,343 | 25,927 | 23223 | 690 |
AccrualsBM | Investment | 14,974 | 6,299 | 17,854 | 0,839 | 41,987 | −17,393 | −5,982 | 8,985 | 31,215 | 23589 | 677 |
SmileSlope | Trading frictions | 14,699 | 10,479 | 7,001 | 2,099 | 4,775 | −4,653 | −1,22 | 4,196 | 15,482 | 35124 | 299 |
FirmAgeMom | Momentum | 14,562 | 7,056 | 19,543 | 0,745 | 85,36 | −43,68 | −7,27 | 8,968 | 32,022 | 10805 | 1,076 |
retConglomerate | Momentum | 13,997 | 6,753 | 13,433 | 1,042 | 24,048 | −16,426 | −4,368 | 8,037 | 21,581 | 27817 | 504 |
roaq | Profitability | 13,804 | 5,206 | 19,575 | 0,705 | 66,879 | −33,62 | −7,489 | 8,434 | 42,393 | 24317 | 654 |
EPq | Value vs, growth | 13,652 | 12,36 | 8,472 | 1,611 | 37,4 | −13,883 | −2,369 | 4,906 | 12,79 | 22735 | 706 |
CFq | Value vs, growth | 13,434 | 6,362 | 16,264 | 0,826 | 72,984 | −39,397 | −5,16 | 6,67 | 32,551 | 22553 | 712 |
IntMom | Momentum | 13,308 | 5,545 | 22,958 | 0,58 | 88,552 | −83,162 | −8,599 | 10,886 | 20,057 | 10805 | 1,098 |
AnnouncementReturn | Momentum | 13,184 | 14,3 | 6,481 | 2,034 | 13,483 | −19,375 | −1,533 | 3,363 | 6,943 | 26176 | 593 |
SP q | Value vs, growth | 12,761 | 6,168 | 15,935 | 0,801 | 66,272 | −36,687 | −4,668 | 7,546 | 30,01 | 22553 | 712 |
MS | Other | 12,29 | 5,003 | 16,464 | 0,746 | 32,814 | −19,743 | −4,647 | 7,197 | 65,859 | 27302 | 539 |
ChNAnalyst | Intangibles | 12,088 | 1,84 | 37,447 | 0,323 | 99,981 | −99,843 | −10,287 | 13,574 | 55,667 | 27908 | 390 |
BMq | Value vs, growth | 11,959 | 4,936 | 18,212 | 0,657 | 52,478 | −28,28 | −5,351 | 8,163 | 39,226 | 23589 | 678 |
Mom6mJunk | Momentum | 11,686 | 3,346 | 21,627 | 0,54 | 53,689 | −36,607 | −7,183 | 8,839 | 42,169 | 28853 | 460 |
XFIN | Investment | 11,679 | 4,836 | 16,817 | 0,694 | 61,192 | −36,495 | −5,99 | 8,208 | 24,596 | 26511 | 582 |
ChTax | Intangibles | 11,678 | 10,049 | 8,87 | 1,317 | 21,738 | −20,135 | −2,648 | 4,727 | 18,141 | 22950 | 699 |
MomOffSeason | Other | 11,535 | 5,47 | 20,173 | 0,572 | 63,137 | −14,896 | −5,955 | 9,224 | 59,863 | 10805 | 1,098 |
ChangeRoA | Profitability | 11,065 | 7,787 | 10,393 | 1,065 | 38,746 | −19,908 | −2,886 | 4,576 | 17,454 | 24684 | 642 |
OperProfRDLagAT q | Profitability | 10,99 | 4,371 | 17,601 | 0,624 | 67,867 | −45,839 | −7,098 | 7,137 | 19,732 | 26329 | 588 |
MomSeasonShort | Other | 10,98 | 6,629 | 15,844 | 0,693 | 76,656 | −54,927 | −5,166 | 6,675 | 43,246 | 10805 | 1,098 |
AssetGrowth | Investment | 10,953 | 7,36 | 12,317 | 0,889 | 35,141 | −9,133 | −3,978 | 6,394 | 28,474 | 19206 | 822 |
NetEquityFinance | Investment | 10,836 | 5,378 | 14,033 | 0,772 | 53,302 | −26,395 | −5,692 | 6,355 | 18,058 | 26511 | 582 |
RD | Profitability | 10,822 | 5,567 | 16,206 | 0,668 | 45,119 | −15,353 | −5,082 | 8,037 | 50,778 | 18840 | 834 |
BM | Value vs, growth | 10,817 | 5,02 | 16,62 | 0,651 | 48,562 | −25,557 | −5,14 | 7,991 | 40,615 | 22493 | 714 |
ChangeRoE | Profitability | 10,813 | 6,858 | 11,533 | 0,938 | 32,843 | −16,991 | −3,18 | 4,249 | 47,698 | 24684 | 642 |
MomVol | Momentum | 10,757 | 3,481 | 29,56 | 0,364 | 99,313 | −68,026 | −11,043 | 11,546 | 37,009 | 10805 | 1,098 |
EarningsStreak | Other | 10,655 | 10,064 | 6,367 | 1,673 | 14,726 | −14,726 | −1,678 | 3,672 | 5,792 | 31016 | 434 |
AssetLiquidityMarket | Other | 10,564 | 7,569 | 10,621 | 0,995 | 34,046 | −15,988 | −3,277 | 5,62 | 17,601 | 23070 | 695 |
NOA | Investment | 10,314 | 7,101 | 11,062 | 0,932 | 40,426 | −12,749 | −3,967 | 5,737 | 27,47 | 23042 | 696 |
PS q | Other | 10,286 | 5,751 | 10,88 | 0,945 | 47,416 | −13,94 | −4,492 | 5,216 | 12,435 | 30712 | 444 |
ResidualMomentum | Momentum | 10,279 | 8,113 | 12,058 | 0,852 | 43,496 | −29,36 | −4,184 | 5,683 | 17,812 | 11139 | 1,087 |
cfpq | Value vs, growth | 9,781 | 5,407 | 12,565 | 0,778 | 47,498 | −29,978 | −4,275 | 5,664 | 14,11 | 26603 | 579 |
Price | Other | 9,713 | 3,106 | 29,918 | 0,325 | 79,409 | −24,709 | −8,14 | 13,004 | 100,833 | 10805 | 1,098 |
ShortInterest | Trading frictions | 9,553 | 5,975 | 11,068 | 0,863 | 20,305 | −15,606 | −4,439 | 5,62 | 16,318 | 26723 | 575 |
REV6 | Momentum | 9,534 | 4,131 | 15,368 | 0,62 | 64,114 | −34,365 | −6,128 | 6,317 | 14,066 | 28033 | 532 |
PS | Other | 9,52 | 2,824 | 23,601 | 0,403 | 61,673 | −37,699 | −8,8 | 10,718 | 38,949 | 26329 | 588 |
Mom12mOffSeason | Other | 9,507 | 3,443 | 26,415 | 0,36 | 97,148 | −87,633 | −10,624 | 9,943 | 29,996 | 10805 | 1,098 |
Mom12m | Momentum | 9,296 | 3,13 | 28,413 | 0,327 | 99,532 | −88,699 | −11,678 | 10,508 | 29,484 | 10805 | 1,098 |
dNoa | Investment | 9,251 | 8,419 | 8,404 | 1,101 | 17,888 | −14,126 | −2,654 | 4,623 | 16,915 | 22858 | 702 |
MomSeason | Other | 9,173 | 6,861 | 12,789 | 0,717 | 58,009 | −27,835 | −4,105 | 6,268 | 24,178 | 10805 | 1,098 |
DolVol | Trading frictions | 9,164 | 4,109 | 21,331 | 0,43 | 46,791 | −16,811 | −6,052 | 7,922 | 83,559 | 10805 | 1,098 |
CBOperProfLagAT q | Profitability | 9,091 | 5,741 | 11,151 | 0,815 | 39,919 | −28,827 | −4,442 | 4,766 | 14,235 | 26114 | 595 |
AgeIPO | Intangibles | 8,995 | 3,316 | 17,173 | 0,524 | 54,993 | −23,749 | −7,144 | 7,796 | 21,436 | 29586 | 481 |
FEPS | Other | 8,843 | 2,848 | 20,811 | 0,425 | 80,805 | −31,77 | −7,216 | 10,261 | 31,558 | 27817 | 539 |
AssetLiquidityMarketQuart | Other | 8,732 | 5,001 | 13,115 | 0,666 | 47,901 | −14,251 | −4,816 | 6,71 | 19,52 | 23620 | 677 |
EarningsSurprise | Momentum | 8,607 | 9,543 | 6,844 | 1,258 | 32,039 | −13,24 | −2,326 | 3,658 | 9,629 | 23190 | 691 |
OScore | Profitability | 8,459 | 3,276 | 18,076 | 0,468 | 65,41 | −42,947 | −7,634 | 8,33 | 20,511 | 26329 | 588 |
GPlag q | Profitability | 8,4 | 4,878 | 12,054 | 0,697 | 56,507 | −22,77 | −4,786 | 5,319 | 10,972 | 26329 | 588 |
RIO MB | Other | 8,37 | 4,166 | 15,259 | 0,549 | 70,199 | −19,43 | −5,652 | 7,779 | 26,724 | 23042 | 692 |
DelDRC | Profitability | 8,271 | 1,582 | 23,673 | 0,349 | 48,281 | −42,979 | −3,801 | 5,549 | 42,596 | 36738 | 246 |
SP | Value vs, growth | 8,269 | 5,123 | 13,457 | 0,615 | 58,84 | −25,006 | −4,67 | 6,493 | 20,62 | 18840 | 834 |
CredRatDG | Profitability | 8,212 | 3,145 | 14,537 | 0,565 | 56,133 | −23,704 | −6,132 | 6,529 | 12,815 | 31471 | 372 |
BMdec | Value vs, growth | 8,125 | 6,002 | 11,204 | 0,725 | 43,023 | −16,354 | −4,12 | 5,823 | 18,12 | 19206 | 822 |
AMq | Value vs, growth | 8,071 | 3,587 | 16,912 | 0,477 | 74,096 | −40,193 | −5,875 | 8,328 | 21,328 | 23589 | 678 |
MomSeason06YrPlus | Other | 8,014 | 7,009 | 10,786 | 0,743 | 39,311 | −21,163 | −3,203 | 5,274 | 32,475 | 11718 | 1,068 |
RDIPO | Intangibles | 7,986 | 3,291 | 16,034 | 0,498 | 54,932 | −26,903 | −6 | 7,171 | 19,231 | 28156 | 524 |
LRreversal | Other | 7,929 | 3,658 | 20,733 | 0,382 | 67,396 | −22,419 | −5,603 | 7,674 | 75,696 | 10805 | 1,098 |
BidAskSpread | Trading frictions | 7,873 | 2,443 | 30,825 | 0,255 | 84,23 | −22,807 | −8,812 | 12,451 | 102,674 | 10805 | 1,098 |
MomOffSeason06YrPlus | Other | 7,854 | 6,034 | 12,286 | 0,639 | 43,147 | −31,543 | −3,781 | 5,546 | 41,583 | 11688 | 1,069 |
AnalystRevision | Momentum | 7,801 | 8,734 | 5,981 | 1,304 | 24,575 | −13,81 | −2,132 | 3,265 | 5,551 | 27850 | 538 |
InvGrowth | Investment | 7,771 | 7,191 | 8,945 | 0,869 | 34,881 | −8,768 | −3,457 | 4,663 | 16,469 | 19206 | 822 |
RIO Disp | Other | 7,766 | 3,534 | 14,688 | 0,529 | 52,278 | −16,378 | −5,047 | 7,493 | 25,716 | 27817 | 536 |
NetDebtFinance | Investment | 7,729 | 8,854 | 6,079 | 1,271 | 15,284 | −4,989 | −2,139 | 3,568 | 8,317 | 26511 | 582 |
Cash | Value vs, growth | 7,705 | 3,137 | 17,236 | 0,447 | 62,28 | −16,82 | −6,668 | 7,818 | 46,972 | 26235 | 591 |
EntMult | Value vs, growth | 7,7 | 5,418 | 11,848 | 0,65 | 49,869 | −17,387 | −4,551 | 6,28 | 19,392 | 18840 | 834 |
NetPayoutYield | Value vs, growth | 7,672 | 4,332 | 14,551 | 0,527 | 59,081 | −23,302 | −5,789 | 7,424 | 17,538 | 19571 | 810 |
OrgCapNoAdj | Intangibles | 7,67 | 4,989 | 12,818 | 0,598 | 48,007 | −17,128 | −4,183 | 6,163 | 33,081 | 18840 | 834 |
DivYield | Value vs, growth | 7,628 | 3,464 | 21,061 | 0,362 | 77,561 | −31,775 | −8,32 | 9,507 | 88,791 | 10805 | 1,098 |
ExchSwitch | Trading frictions | 7,486 | 4,924 | 11,596 | 0,646 | 26,117 | −13,52 | −4,582 | 6,374 | 12,93 | 22980 | 698 |
EBM q | Value vs, growth | 7,464 | 5,685 | 9,603 | 0,777 | 28,163 | −17,715 | −3,055 | 4,308 | 21,2 | 24590 | 642 |
MomRev | Momentum | 7,454 | 3,507 | 20,322 | 0,367 | 95,38 | −60,502 | −7,601 | 8,663 | 35,977 | 10805 | 1,097 |
CustomerMomentum | Other | 7,437 | 2,136 | 22,965 | 0,324 | 87,213 | −61,346 | −6,128 | 9,473 | 36,098 | 28335 | 522 |
DivOmit | Value vs, growth | 7,433 | 4,146 | 16,946 | 0,439 | 62,135 | −26,05 | −6,89 | 7,662 | 42,036 | 10805 | 1,072 |
iomom cust | Momentum | 7,264 | 3,175 | 13,518 | 0,537 | 44,183 | −33,24 | −4,821 | 6,553 | 15,782 | 31471 | 419 |
RevenueSurprise | Momentum | 7,233 | 8,584 | 6,394 | 1,131 | 18,352 | −12,137 | −1,746 | 2,927 | 14,765 | 23190 | 691 |
ChInv | Investment | 7,2 | 8,028 | 7,423 | 0,97 | 24,401 | −6,697 | −2,644 | 4,178 | 15,967 | 19206 | 822 |
betaVIX | Trading frictions | 7,167 | 3,328 | 12,723 | 0,563 | 44,428 | −13,073 | −4,288 | 6,959 | 18,266 | 31471 | 419 |
MaxRet | Trading frictions | 7,166 | 2,682 | 25,561 | 0,28 | 84,963 | −45,188 | −10,793 | 11,013 | 48,034 | 10805 | 1,098 |
Activism2 | Intangibles | 7,032 | 1,763 | 16,157 | 0,435 | 54,174 | −12,828 | −6,804 | 7,906 | 16,228 | 33177 | 197 |
iomom supp | Momentum | 7,028 | 2,953 | 14,044 | 0,5 | 39,746 | −22,748 | −5,279 | 6,547 | 20,423 | 31471 | 418 |
PM q | Profitability | 7,025 | 2,947 | 18,363 | 0,383 | 66,098 | −47,176 | −8,132 | 7,529 | 20,543 | 22553 | 712 |
RetNOA q | Profitability | 6,997 | 3,255 | 16,123 | 0,434 | 63,183 | −36,101 | −6,855 | 7,057 | 18,418 | 23680 | 675 |
DelBreadth | Intangibles | 6,88 | 2,899 | 14,976 | 0,459 | 42,848 | −29,964 | −5,476 | 6,541 | 29,975 | 29433 | 478 |
VolumeTrend | Other | 6,864 | 5,387 | 12,188 | 0,563 | 29,105 | −25,261 | −3,691 | 5,264 | 45,626 | 10805 | 1,098 |
ChangeInRecommendation | Intangibles | 6,745 | 7,128 | 4,924 | 1,37 | 7,211 | −6,466 | −1,408 | 2,642 | 6,657 | 34334 | 325 |
zerotradeAlt1 | Trading frictions | 6,741 | 3,638 | 17,724 | 0,38 | 56,42 | −27,511 | −6,513 | 8,349 | 54,367 | 10805 | 1,098 |
OperProfLag q | Profitability | 6,731 | 3,001 | 16,404 | 0,41 | 68,712 | −39,694 | −6,718 | 6,686 | 18,946 | 24590 | 642 |
NetDebtPrice | Value vs, growth | 6,727 | 4,133 | 12,343 | 0,545 | 35,617 | −15,666 | −4,773 | 5,217 | 21,375 | 23223 | 690 |
InvestPPEInv | Investment | 6,598 | 8,666 | 6,324 | 1,043 | 28,493 | −7,032 | −2,053 | 3,457 | 13,252 | 19024 | 828 |
CapTurnover q | Other | 6,572 | 4,065 | 11,936 | 0,551 | 48,146 | −17,783 | −4,505 | 5,518 | 22,782 | 24317 | 654 |
DivYieldST | Value vs, growth | 6,554 | 8,976 | 6,981 | 0,939 | 17,29 | −11,302 | −1,963 | 3,267 | 34,66 | 10805 | 1,097 |
RIO Volatility | Other | 6,54 | 3,507 | 17,813 | 0,367 | 73,855 | −21,933 | −7,098 | 8,195 | 50,584 | 10805 | 1,095 |
AssetTurnover q | Other | 6,451 | 4,68 | 10,453 | 0,617 | 31,334 | −12,193 | −4,277 | 5,167 | 16,28 | 23223 | 690 |
PriceDelayRsq | Trading frictions | 6,438 | 3,466 | 17,737 | 0,363 | 43,594 | −31,971 | −5,739 | 7,316 | 64,449 | 10805 | 1,094 |
MomSeason11YrPlus | Other | 6,435 | 7,117 | 8,287 | 0,777 | 23,154 | −18,298 | −2,924 | 4,337 | 12,701 | 13545 | 1,008 |
zerotrade | Trading frictions | 6,432 | 3,305 | 18,614 | 0,346 | 46,739 | −27,052 | −7,2 | 7,963 | 67,172 | 10805 | 1,098 |
Mom6m | Momentum | 6,282 | 2,288 | 26,267 | 0,239 | 99,264 | −77,393 | −9,823 | 8,814 | 32,091 | 10805 | 1,098 |
IdioRisk | Trading frictions | 6,26 | 2,66 | 22,511 | 0,278 | 88,132 | −39,119 | −10,011 | 9,601 | 38,075 | 10805 | 1,098 |
tang q | Intangibles | 6,218 | 4,622 | 9,497 | 0,655 | 52,453 | −9,233 | −3,559 | 4,753 | 27,608 | 26023 | 598 |
DelFINL | Investment | 6,152 | 11,461 | 4,443 | 1,385 | 18,264 | −5,483 | −1,545 | 2,52 | 7,868 | 19206 | 822 |
MomSeason16YrPlus | Other | 6,026 | 6,577 | 8,144 | 0,74 | 16,833 | −8,477 | −2,89 | 3,969 | 17,795 | 15372 | 948 |
std turn | Trading frictions | 5,982 | 2,895 | 19,769 | 0,303 | 80,934 | −45,882 | −8,529 | 8,966 | 25,169 | 10805 | 1,098 |
CBOperProf | Profitability | 5,936 | 3,523 | 12,886 | 0,461 | 53,472 | −14,01 | −5,3 | 6,505 | 17,411 | 22858 | 702 |
ConsRecomm | Other | 5,891 | 2,409 | 12,746 | 0,462 | 42,565 | −12,732 | −5,186 | 6,761 | 19,279 | 34303 | 326 |
skew1 | Trading frictions | 5,853 | 4,086 | 7,151 | 0,818 | 18,39 | −9,273 | −2,32 | 3,658 | 7,431 | 35124 | 299 |
OPLeverage q | Intangibles | 5,831 | 3,274 | 13,118 | 0,445 | 42,393 | −15,361 | −5,231 | 6,544 | 21,029 | 24317 | 651 |
ReturnSkew | Trading frictions | 5,82 | 7,715 | 7,216 | 0,806 | 31,453 | −18,157 | −2,099 | 3,169 | 12,179 | 10805 | 1,098 |
DelEqu | Investment | 5,585 | 3,969 | 10,761 | 0,519 | 36,342 | −8,165 | −3,651 | 5,597 | 21,525 | 22858 | 702 |
RDcap | Intangibles | 5,563 | 2,954 | 11,985 | 0,464 | 39,292 | −9,083 | −4,353 | 6,098 | 20,935 | 29433 | 486 |
sfe | Value vs, growth | 5,529 | 1,714 | 21,573 | 0,256 | 88,5 | −54,648 | −8,49 | 9,102 | 21,883 | 27880 | 537 |
AdExp | Intangibles | 5,515 | 2,577 | 16,114 | 0,342 | 53,395 | −20,097 | −5,655 | 6,895 | 43,517 | 20299 | 680 |
ShareVol | Trading frictions | 5,502 | 3,197 | 16,395 | 0,336 | 77,968 | −29,05 | −7,302 | 7,471 | 28,075 | 10805 | 1,089 |
PayoutYield q | Value vs, growth | 5,439 | 4,427 | 9,049 | 0,601 | 30,056 | −13,113 | −3,384 | 4,117 | 16,62 | 24411 | 651 |
depr | Other | 5,431 | 3,677 | 12,357 | 0,44 | 51,003 | −14,443 | −4,405 | 5,822 | 30,729 | 18659 | 840 |
ChEQ | Intangibles | 5,404 | 4,02 | 10,282 | 0,526 | 29,477 | −14,126 | −3,669 | 4,943 | 21,503 | 22858 | 702 |
IdioVol3F | Trading frictions | 5,349 | 2,233 | 22,907 | 0,233 | 91,773 | −43,016 | −9,771 | 9,48 | 39,316 | 10805 | 1,098 |
EarningsForecastDisparity | Intangibles | 5,295 | 3,518 | 9,399 | 0,563 | 35,356 | −14,629 | −3,599 | 4,209 | 10,182 | 29980 | 468 |
Leverage q | Profitability | 5,283 | 2,342 | 16,651 | 0,317 | 77,886 | −41,682 | −5,998 | 7,953 | 17,376 | 24317 | 654 |
NetPayoutYield q | Value vs, growth | 5,264 | 2,148 | 18,053 | 0,292 | 64,716 | −30,815 | −7,553 | 8,439 | 36,091 | 24411 | 651 |
OptionVolume1 | Trading frictions | 5,24 | 2,021 | 12,92 | 0,406 | 55,349 | −23,404 | −4,069 | 5,505 | 19,543 | 35153 | 298 |
NumEarnIncrease | Momentum | 5,225 | 9,206 | 4,286 | 1,219 | 19,702 | −6,137 | −1,62 | 2,415 | 5,178 | 23407 | 684 |
ForecastDispersion | Intangibles | 5,198 | 2,273 | 15,323 | 0,339 | 59,378 | −25,571 | −6,72 | 6,97 | 13,746 | 27817 | 539 |
CBOperProfLagAT | Profitability | 5,176 | 3,218 | 12,249 | 0,423 | 42,409 | −27,702 | −5,954 | 5,064 | 13,288 | 23042 | 696 |
hire | Intangibles | 5,168 | 5,322 | 7,234 | 0,714 | 27,421 | −9,683 | −2,733 | 4,139 | 11,145 | 23953 | 666 |
zerotradeAlt12 | Trading frictions | 5,162 | 3,39 | 14,564 | 0,354 | 46,51 | −21,01 | −5,145 | 6,463 | 58,4 | 10805 | 1,098 |
AM | Value vs, growth | 5,139 | 3,016 | 14,205 | 0,362 | 70,638 | −28,135 | −5,176 | 7,341 | 20,865 | 18840 | 834 |
ShareIss1Y | Investment | 5,085 | 6,228 | 7,81 | 0,651 | 25,524 | −13,625 | −2,875 | 4,232 | 10,95 | 10805 | 1,098 |
Accruals | Investment | 5,022 | 6,651 | 6,25 | 0,804 | 20,468 | −8,761 | −2,194 | 3,471 | 7,165 | 19206 | 822 |
MRreversal | Other | 4,992 | 3,137 | 15,222 | 0,328 | 67,114 | −13,021 | −4,228 | 5,373 | 61,602 | 10805 | 1,098 |
EquityDuration | Value vs, growth | 4,893 | 2,578 | 14,394 | 0,34 | 66,695 | −16,086 | −6,031 | 7,16 | 20,939 | 23223 | 690 |
OperProf | Profitability | 4,876 | 3,143 | 11,765 | 0,414 | 54,613 | −25,482 | −4,121 | 4,563 | 19,835 | 23223 | 690 |
PctAcc | Investment | 4,77 | 4,612 | 7,773 | 0,614 | 22,69 | −8,329 | −2,878 | 4,172 | 12,633 | 23589 | 678 |
OPLeverage | Intangibles | 4,744 | 3,818 | 10,357 | 0,458 | 39,75 | −12,354 | −4,142 | 5,035 | 20,604 | 18840 | 834 |
ShareIss5Y | Investment | 4,669 | 5,268 | 8,384 | 0,557 | 29,015 | −8,052 | −2,899 | 3,897 | 30,07 | 11535 | 1,074 |
DelCOA | Investment | 4,658 | 6,201 | 6,217 | 0,749 | 31,089 | −6,524 | −2,259 | 3,439 | 10,706 | 19206 | 822 |
IndIPO | Intangibles | 4,646 | 2,673 | 11,743 | 0,396 | 37,676 | −18,905 | −4,542 | 5,156 | 15,404 | 27544 | 548 |
IndMom | Momentum | 4,638 | 3,974 | 11,163 | 0,415 | 57,47 | −27,742 | −3,73 | 4,725 | 25,526 | 10805 | 1,098 |
IntanSP | Value vs, growth | 4,624 | 2,589 | 14,347 | 0,322 | 62,892 | −13,204 | −5,376 | 6,803 | 23,346 | 20667 | 774 |
Size | Other | 4,623 | 3,187 | 13,875 | 0,333 | 52,279 | −10,973 | −4,258 | 5,973 | 53,26 | 10805 | 1,098 |
OperProfRD | Profitability | 4,599 | 2,311 | 15,091 | 0,305 | 66,236 | −14,319 | −6,737 | 7,788 | 17,573 | 23223 | 690 |
OrgCap | Intangibles | 4,573 | 4,16 | 9,165 | 0,499 | 33,984 | −10,615 | −3,832 | 4,604 | 11,703 | 18840 | 834 |
ReturnSkew3F | Trading frictions | 4,55 | 7,829 | 5,559 | 0,818 | 26,474 | −13,135 | −1,583 | 2,654 | 10,253 | 10805 | 1,098 |
BrandInvest | Intangibles | 4,48 | 1,674 | 19,932 | 0,225 | 71,063 | −24,679 | −8,084 | 8,987 | 40,012 | 23953 | 666 |
DownRecomm | Intangibles | 4,477 | 6,1 | 3,819 | 1,172 | 5,991 | −5,991 | −1,061 | 2,077 | 7,208 | 34334 | 325 |
CF | Value vs, growth | 4,474 | 2,562 | 14,556 | 0,307 | 50,586 | −36,293 | −5,488 | 5,886 | 17,254 | 18840 | 834 |
CoskewACX | Trading frictions | 4,469 | 3,562 | 9,36 | 0,477 | 35,927 | −11,753 | −3,452 | 4,608 | 19,586 | 23223 | 668 |
betaNet | Trading frictions | 4,45 | 3,224 | 12,874 | 0,346 | 62,429 | −12,213 | −4,669 | 6,097 | 29,654 | 12450 | 1,044 |
grcapx3y | Investment | 4,45 | 5,477 | 6,626 | 0,672 | 23,556 | −6,536 | −2,484 | 3,636 | 13,852 | 19935 | 798 |
betaCC | Trading frictions | 4,449 | 3,292 | 12,605 | 0,353 | 61,686 | −11,579 | −4,446 | 5,502 | 29,33 | 12450 | 1,044 |
RIO Turnover | Other | 4,433 | 2,829 | 14,976 | 0,296 | 64,628 | −20,468 | −6,611 | 7,251 | 18,778 | 10805 | 1,096 |
AssetTurnover | Other | 4,373 | 4,31 | 8,397 | 0,521 | 41,306 | −7,92 | −3,595 | 4,324 | 10,475 | 19206 | 822 |
WW Q | Other | 4,345 | 1,46 | 21,063 | 0,206 | 77,356 | −21,674 | −7,394 | 10,386 | 42,262 | 25902 | 601 |
GP | Profitability | 4,333 | 3,549 | 10,178 | 0,426 | 55,799 | −15,813 | −4,124 | 5,19 | 12,305 | 18840 | 834 |
Illiquidity | Trading frictions | 4,309 | 3,464 | 11,897 | 0,362 | 38,768 | −11,582 | −4,826 | 6,088 | 33,749 | 10805 | 1,098 |
tang | Intangibles | 4,304 | 3,219 | 11,188 | 0,385 | 37,32 | −12,065 | −4,163 | 4,874 | 38,744 | 18659 | 840 |
BetaTailRisk | Trading frictions | 4,29 | 2,709 | 14,942 | 0,287 | 44,177 | −19,12 | −5,867 | 6,466 | 37,067 | 11718 | 1,068 |
Tax | Profitability | 4,278 | 5,236 | 6,812 | 0,628 | 34,392 | −16,421 | −2,321 | 3,227 | 11,11 | 18840 | 834 |
ResidualMomentum6m | Momentum | 4,25 | 4,001 | 10,132 | 0,419 | 37,327 | −23,253 | −4,004 | 4,079 | 13,009 | 10989 | 1,092 |
ChInvIA | Investment | 4,207 | 6,234 | 5,586 | 0,753 | 29,42 | −6,255 | −1,936 | 2,868 | 10,375 | 19206 | 822 |
OrderBacklogChg | Investment | 4,194 | 2,567 | 11,378 | 0,369 | 44,392 | −18,4 | −4,45 | 5,326 | 13,777 | 26511 | 582 |
pchsaleinv | Other | 4,176 | 7,785 | 4,456 | 0,937 | 32,391 | −3,709 | −1,716 | 2,496 | 5,249 | 19024 | 828 |
sgr q | Other | 4,117 | 3,15 | 9,98 | 0,412 | 36,258 | −20,083 | −4,513 | 4,033 | 12,006 | 22917 | 700 |
grcapx | Investment | 4,065 | 5,625 | 5,937 | 0,685 | 22,295 | −5,778 | −2,317 | 3,218 | 8,255 | 19571 | 810 |
DivInit | Value vs, growth | 4,054 | 2,99 | 12,97 | 0,313 | 49,172 | −43,755 | −3,727 | 5,101 | 34,573 | 10805 | 1,098 |
DelNetFin | Investment | 4,046 | 6,924 | 4,837 | 0,837 | 21,473 | −7,375 | −1,84 | 2,489 | 4,947 | 19206 | 822 |
UpRecomm | Intangibles | 4,039 | 5,409 | 3,886 | 1,039 | 8,024 | −6,836 | −1,074 | 2,11 | 4,534 | 34334 | 325 |
EarnSupBig | Momentum | 3,925 | 3,082 | 9,664 | 0,406 | 32,411 | −17,367 | −4,074 | 4,276 | 12,992 | 23190 | 691 |
Beta | Trading frictions | 3,891 | 1,384 | 26,887 | 0,145 | 91,975 | −25,643 | −10,529 | 12,209 | 66,2 | 10805 | 1,098 |
Leverage | Profitability | 3,853 | 2,299 | 13,969 | 0,276 | 75,307 | −33,085 | −4,922 | 7,008 | 20,942 | 18840 | 834 |
PctTotAcc | Investment | 3,848 | 4,09 | 5,364 | 0,717 | 20,51 | −7,088 | −1,952 | 2,906 | 5,433 | 32353 | 390 |
OptionVolume2 | Trading frictions | 3,847 | 1,754 | 10,913 | 0,353 | 24,647 | −9,058 | −2,761 | 2,686 | 36,023 | 35185 | 297 |
CompEquIss | Investment | 3,805 | 3,068 | 11,763 | 0,323 | 57,38 | −19,376 | −3,639 | 3,766 | 42,241 | 11354 | 1,08 |
DivSeason | Value vs, growth | 3,706 | 14,429 | 2,457 | 1,508 | 6,476 | −3,414 | −0,813 | 1,424 | 4,68 | 10805 | 1,098 |
CashProd | Intangibles | 3,638 | 2,572 | 11,832 | 0,307 | 58,144 | −27,924 | −4,558 | 6,021 | 15,122 | 18659 | 840 |
BetaBDLeverage | Trading frictions | 3,587 | 1,969 | 12,555 | 0,286 | 49,749 | −15,154 | −5,209 | 6,087 | 17,786 | 26876 | 570 |
IntanCFP | Value vs, growth | 3,585 | 2,499 | 11,567 | 0,31 | 44,67 | −27,887 | −4,267 | 5,622 | 24,293 | 20485 | 780 |
DebtIssuance | Investment | 3,577 | 5,702 | 4,391 | 0,815 | 13,197 | −4,961 | −1,609 | 2,145 | 9,098 | 26329 | 588 |
MomOffSeason16YrPlus | Other | 3,553 | 3,358 | 9,29 | 0,382 | 40,307 | −9,647 | −3,904 | 4,107 | 22,418 | 16071 | 925 |
TotalAccruals | Investment | 3,551 | 3,563 | 8,247 | 0,431 | 43,768 | −7,858 | −2,547 | 3,703 | 16,382 | 19206 | 822 |
cfp | Value vs, growth | 3,523 | 1,763 | 15,02 | 0,235 | 70,311 | −32,368 | −6,223 | 6,093 | 16,724 | 23589 | 678 |
WW | Other | 3,51 | 2,124 | 13,726 | 0,256 | 61,703 | −16,077 | −4,858 | 6,29 | 31,135 | 19024 | 828 |
VolSD | Trading frictions | 3,475 | 2,355 | 14,113 | 0,246 | 39,969 | −31,742 | −5,457 | 6,035 | 43,474 | 10805 | 1,098 |
Spinoff | Other | 3,423 | 2,29 | 14,297 | 0,239 | 62,055 | −20,934 | −4,777 | 5,28 | 54,375 | 10805 | 1,098 |
sinAlgo | Other | 3,408 | 2,55 | 11,166 | 0,305 | 56,2 | −15,83 | −4,584 | 5,083 | 35,224 | 18718 | 838 |
VolMkt | Trading frictions | 3,405 | 1,807 | 18,03 | 0,189 | 80,691 | −31,954 | −7,799 | 8,763 | 21,094 | 10805 | 1,098 |
EP | Value vs, growth | 3,393 | 2,909 | 9,76 | 0,348 | 41,611 | −15,944 | −3,879 | 4,803 | 17,139 | 18659 | 840 |
BetaLiquidityPS | Trading frictions | 3,365 | 2,111 | 11,723 | 0,287 | 45,425 | −13,297 | −4,829 | 5,695 | 14,063 | 24138 | 649 |
AssetLiquidityBook | Other | 3,255 | 2,535 | 10,735 | 0,303 | 42,858 | −13,004 | −3,874 | 4,672 | 33,696 | 18687 | 839 |
realestate | Intangibles | 3,246 | 2,257 | 10,221 | 0,318 | 36,575 | −15,268 | −4,227 | 4,959 | 11,786 | 25780 | 606 |
IntanEP | Value vs, growth | 3,242 | 2,781 | 9,365 | 0,346 | 40,047 | −13,871 | −3,601 | 4,412 | 16,625 | 20667 | 774 |
MomOffSeason11YrPlus | Other | 3,205 | 2,773 | 10,598 | 0,302 | 27,372 | −9,702 | −3,796 | 4,19 | 51,967 | 13515 | 1,009 |
EarningsConsistency | Intangibles | 3,118 | 3,803 | 6,735 | 0,463 | 36,496 | −8,2 | −3,047 | 3,239 | 6,818 | 19571 | 810 |
RDS | Intangibles | 3,099 | 2,55 | 8,377 | 0,37 | 29,631 | −14,937 | −2,957 | 4,063 | 11,682 | 26876 | 570 |
GrSaleToGrInv | Intangibles | 3,082 | 5,449 | 4,681 | 0,658 | 19,914 | −4,589 | −2,008 | 2,263 | 6,394 | 19206 | 822 |
IntrinsicValue | Other | 3,068 | 1,372 | 14,915 | 0,206 | 60,048 | −24,942 | −5,703 | 6,73 | 17,221 | 27971 | 534 |
PatentsRD | Other | 2,957 | 2,921 | 5,637 | 0,525 | 20,997 | −4,651 | −2,093 | 2,581 | 10,977 | 28335 | 372 |
AssetLiquidityBookQuart | Other | 2,953 | 1,412 | 15,684 | 0,188 | 66,599 | −19,197 | −7,17 | 6,565 | 38,509 | 23680 | 675 |
IntanBM | Value vs, growth | 2,913 | 1,705 | 12,614 | 0,231 | 44,075 | −18,729 | −4,872 | 6,138 | 24,469 | 24317 | 654 |
GrAdExp | Intangibles | 2,849 | 1,503 | 14,123 | 0,202 | 80,327 | −25,982 | −4,973 | 5,514 | 24,665 | 23953 | 666 |
ConvDebt | Intangibles | 2,831 | 4,26 | 5,561 | 0,509 | 20,422 | −23,012 | −1,979 | 2,489 | 5,7 | 18659 | 840 |
CompositeDebtIssuance | Investment | 2,813 | 5,327 | 4,241 | 0,663 | 16,535 | −5,517 | −1,81 | 2,18 | 3,866 | 20667 | 774 |
rd sale q | Other | 2,777 | 0,672 | 23,002 | 0,121 | 85,224 | −17,849 | −8,758 | 9,696 | 58,856 | 32904 | 372 |
GPlag | Profitability | 2,761 | 2,622 | 8,747 | 0,316 | 36,922 | −8,688 | −4,167 | 4,034 | 11,789 | 19024 | 828 |
RoE | Profitability | 2,745 | 2,319 | 9,13 | 0,301 | 48,518 | −22,086 | −3,388 | 4,249 | 14,631 | 22493 | 714 |
ChNNCOA | Investment | 2,716 | 5,35 | 4,203 | 0,646 | 13,783 | −4,704 | −1,723 | 2,279 | 5,299 | 19206 | 822 |
MeanRankRevGrowth | Value vs, growth | 2,7 | 3,063 | 7,026 | 0,384 | 33,692 | −7,794 | −2,818 | 3,491 | 9,186 | 21032 | 762 |
pchgm pchsale | Other | 2,654 | 4,191 | 5,26 | 0,505 | 17,225 | −7,684 | −2,483 | 2,545 | 4,86 | 19024 | 828 |
quick | Investment | 2,651 | 2,137 | 10,377 | 0,255 | 61,508 | −17,187 | −4,158 | 4,341 | 29,082 | 18659 | 840 |
PriceDelaySlope | Trading frictions | 2,634 | 2,641 | 9,524 | 0,277 | 25,608 | −11,884 | −3,776 | 4,096 | 29,902 | 10805 | 1,094 |
CapTurnover | Other | 2,629 | 2,368 | 9,156 | 0,287 | 49,854 | −10,745 | −4,058 | 4,341 | 10,646 | 19389 | 816 |
ChForecastAccrual | Intangibles | 2,607 | 3,914 | 4,445 | 0,587 | 10,817 | −5,838 | −1,744 | 2,224 | 5,006 | 27971 | 534 |
EBM | Value vs, growth | 2,546 | 3,505 | 5,556 | 0,458 | 23,888 | −5,635 | −2,281 | 2,856 | 10,374 | 22858 | 702 |
DelCOL | Investment | 2,536 | 3,499 | 5,998 | 0,423 | 32,895 | −6,617 | −2,508 | 3,325 | 6,655 | 19206 | 822 |
PayoutYield | Value vs, growth | 2,535 | 2,044 | 10,188 | 0,249 | 55,369 | −9,169 | −4,373 | 5,087 | 16,252 | 19571 | 810 |
saleinv | Other | 2,481 | 2,989 | 6,943 | 0,357 | 28,359 | −11,825 | −3,104 | 3,137 | 6,522 | 18659 | 840 |
GrGMToGrSales | Intangibles | 2,443 | 3,806 | 5,312 | 0,46 | 19,093 | −5,611 | −2,385 | 2,712 | 5,316 | 19206 | 822 |
GrLTNOA | Investment | 2,38 | 3,168 | 6,218 | 0,383 | 21,305 | −8,99 | −2,77 | 3,137 | 8,077 | 19206 | 822 |
CitationsRD | Other | 2,369 | 2,182 | 6,332 | 0,374 | 32,343 | −8,176 | −2,743 | 3,063 | 9,089 | 28335 | 408 |
currat | Value vs, growth | 2,3 | 2,05 | 9,385 | 0,245 | 50,149 | −14,905 | −3,68 | 4,236 | 26,14 | 18659 | 840 |
FailureProbability | Other | 2,237 | 0,756 | 21,551 | 0,104 | 82,379 | −41,921 | −9,2 | 8,86 | 30,412 | 24868 | 636 |
OperProfLag | Profitability | 2,222 | 1,491 | 11,251 | 0,197 | 55,295 | −27,828 | −4,454 | 4,514 | 19,342 | 23407 | 684 |
salerec | Other | 2,156 | 2,573 | 7,012 | 0,308 | 44,771 | −6,142 | −2,974 | 3,257 | 11,471 | 18659 | 840 |
AnalystValue | Intangibles | 2,143 | 1,044 | 13,697 | 0,156 | 67,921 | −24,318 | −5,662 | 5,507 | 23,206 | 27971 | 534 |
IdioVolAHT | Trading frictions | 2,134 | 0,857 | 23,831 | 0,09 | 96,593 | −43,551 | −11,273 | 9,862 | 35,077 | 10805 | 1,098 |
rd sale | Other | 2,112 | 0,923 | 18,933 | 0,112 | 85,143 | −18,465 | −7,065 | 7,436 | 61,738 | 19206 | 822 |
Investment | Investment | 2,108 | 1,918 | 9,03 | 0,233 | 54,311 | −12,673 | −3,677 | 4,048 | 26,882 | 19571 | 810 |
BPEBM | Value vs, growth | 2,024 | 2,723 | 5,685 | 0,356 | 33,062 | −7,161 | −2,355 | 2,713 | 14,38 | 22858 | 702 |
ShareRepurchase | Investment | 2,014 | 2,575 | 5,446 | 0,37 | 24,889 | −8,318 | −2,276 | 2,471 | 5,631 | 26511 | 582 |
AOP | Intangibles | 1,984 | 1,463 | 9,049 | 0,219 | 34,526 | −9,994 | −3,725 | 4,58 | 11,022 | 27971 | 534 |
B, Individual anomalies AbnormalAccruals | Investment | 1,976 | 1,868 | 7,367 | 0,268 | 50,373 | −5,307 | −2,964 | 3,411 | 15,244 | 26511 | 582 |
ChAssetTurnover | Profitability | 1,94 | 3,857 | 4,132 | 0,47 | 16,633 | −6,321 | −1,663 | 1,933 | 5,648 | 19571 | 810 |
DelLTI | Investment | 1,935 | 3,605 | 4,409 | 0,439 | 18,242 | −4,58 | −1,613 | 1,942 | 9,633 | 19571 | 810 |
pchdepr | Investment | 1,918 | 3,133 | 5,087 | 0,377 | 23,974 | −5,578 | −1,833 | 2,331 | 11,422 | 19024 | 828 |
EarningsSmoothness | Other | 1,915 | 1,442 | 10,283 | 0,186 | 44,334 | −10,875 | −4,432 | 4,712 | 18,51 | 22312 | 720 |
betaRR | Trading frictions | 1,869 | 0,831 | 20,971 | 0,089 | 90,344 | −21,495 | −8,518 | 9,39 | 55,245 | 12450 | 1,044 |
fgr5yrLag | Intangibles | 1,847 | 0,646 | 17,732 | 0,104 | 68,426 | −27,447 | −6,775 | 7,82 | 18,003 | 30162 | 462 |
ChNWC | Profitability | 1,814 | 4,3 | 3,492 | 0,52 | 24,108 | −4,351 | −1,324 | 1,851 | 6,097 | 19206 | 822 |
Activism1 | Other | 1,713 | 0,768 | 9,034 | 0,19 | 21,33 | −8,014 | −3,689 | 4,234 | 12,648 | 33177 | 197 |
ChPM | Other | 1,709 | 3,067 | 4,613 | 0,371 | 19,056 | −4,448 | −1,968 | 2,373 | 4,668 | 19206 | 822 |
BookLeverage | Value vs, growth | 1,559 | 1,203 | 10,806 | 0,144 | 61,967 | −13,506 | −4,096 | 4,229 | 28,613 | 18840 | 834 |
BrandCapital | Intangibles | 1,52 | 0,807 | 14,281 | 0,106 | 71,066 | −21,931 | −6,016 | 5,929 | 30,452 | 20299 | 690 |
GrSaleToGrReceivables | Other | 1,481 | 2,945 | 4,163 | 0,356 | 21,693 | −4,096 | −1,686 | 2,015 | 5,631 | 19206 | 822 |
ExclExp | Intangibles | 1,438 | 1,049 | 8,307 | 0,173 | 20,432 | −34,727 | −2,163 | 2,663 | 7,241 | 30526 | 440 |
DownsideBeta | Trading frictions | 1,317 | 0,604 | 20,859 | 0,063 | 78,091 | −35,682 | −9,21 | 9,044 | 36,892 | 10805 | 1,098 |
OperProfRDLagAT | Profitability | 1,189 | 0,756 | 13,065 | 0,091 | 72,754 | −28,402 | −6,199 | 4,781 | 12,783 | 19024 | 828 |
Herf | Intangibles | 1,188 | 1,508 | 6,594 | 0,18 | 51,465 | −7,384 | −2,49 | 2,819 | 18,758 | 18659 | 840 |
Coskewness | Trading frictions | 1,131 | 1,152 | 9,39 | 0,12 | 70,164 | −21,274 | −3,578 | 4,21 | 14,991 | 10805 | 1,098 |
IdioVolCAPM | Trading frictions | 1,057 | 0,373 | 27,1 | 0,039 | 99,137 | −26,001 | −9,6 | 11,392 | 82,801 | 10805 | 1,098 |
SurpriseRD | Intangibles | 1,044 | 1,412 | 6,136 | 0,17 | 49,918 | −10,417 | −2,36 | 2,65 | 16,462 | 19084 | 826 |
HerfBE | Intangibles | 1,026 | 1,138 | 7,495 | 0,137 | 52,971 | −11,185 | −2,725 | 2,831 | 28,812 | 18993 | 829 |
pchquick | Investment | 1,021 | 1,752 | 4,825 | 0,212 | 56,445 | −11,42 | −2,143 | 2,045 | 3,456 | 19206 | 822 |
DelayNonAcct | Other | 0,936 | 0,696 | 8,732 | 0,107 | 38,014 | −9,843 | −4,08 | 4,032 | 10,909 | 28702 | 506 |
roavol | Other | 0,892 | 0,311 | 20,792 | 0,043 | 86,569 | −21,953 | −8,471 | 7,88 | 39,757 | 25017 | 631 |
Tax q | Profitability | 0,871 | 0,908 | 7,389 | 0,118 | 65,873 | −11,265 | −2,793 | 2,401 | 32,551 | 22553 | 712 |
KZ | Intangibles | 0,843 | 0,618 | 10,444 | 0,081 | 63,554 | −17,243 | −4,576 | 4,615 | 13,567 | 22858 | 702 |
salecash | Other | 0,828 | 0,71 | 9,756 | 0,085 | 63,509 | −25,1 | −4,047 | 3,899 | 14,508 | 18659 | 840 |
FRbook | Intangibles | 0,727 | 0,667 | 6,882 | 0,106 | 47,642 | −10,08 | −3,2 | 3,085 | 7,885 | 29644 | 479 |
OrderBacklog | Intangibles | 0,715 | 0,601 | 8,369 | 0,085 | 53,035 | −9,697 | −3,716 | 3,514 | 15,79 | 26144 | 594 |
AccrualQuality | Investment | 0,702 | 0,388 | 14,464 | 0,049 | 65,655 | −15,428 | −5,99 | 6,701 | 31,358 | 20851 | 768 |
EarningsValueRelevance | Other | 0,683 | 1,154 | 4,583 | 0,149 | 29,746 | −6,322 | −2,007 | 2,089 | 4,853 | 22312 | 720 |
AccrualQualityJune | Investment | 0,646 | 0,358 | 14,395 | 0,045 | 68,988 | −14,969 | −5,733 | 6,809 | 30,395 | 21032 | 762 |
EarningsTimeliness | Other | 0,559 | 0,904 | 4,823 | 0,116 | 36,643 | −6,167 | −1,969 | 2,269 | 10,844 | 21944 | 732 |
DelSTI | Investment | 0,542 | 0,848 | 4,538 | 0,119 | 40,103 | −3,884 | −1,682 | 2,164 | 8,19 | 25780 | 606 |
PriceDelayTstat | Trading frictions | 0,464 | 0,588 | 7,526 | 0,062 | 60,189 | −15,351 | −3,374 | 3,116 | 17,205 | 10805 | 1,094 |
HerfAsset | Intangibles | 0,454 | 0,497 | 7,584 | 0,06 | 61,889 | −11,207 | −2,654 | 3,121 | 30,242 | 18993 | 829 |
roic | Profitability | 0,333 | 0,161 | 15,832 | 0,021 | 75,953 | −36,024 | −7,025 | 5,713 | 18,188 | 22858 | 702 |
BetaFP | Trading frictions | 0,271 | 0,079 | 32,808 | 0,008 | 99,634 | −27,002 | −13,184 | 14,528 | 83,153 | 10805 | 1,098 |
RetNOA | Profitability | 0,141 | 0,152 | 7,065 | 0,02 | 47,799 | −10,833 | −2,981 | 2,833 | 17,562 | 23223 | 690 |
RDAbility | Other | 0,127 | 0,079 | 12,805 | 0,01 | 73,118 | −12,956 | −6,043 | 6,068 | 14,978 | 21032 | 762 |
pchcurrat | Investment | 0,109 | 0,192 | 4,697 | 0,023 | 59,192 | −11,203 | −2,183 | 1,84 | 3,711 | 19206 | 822 |
PredictedFE | Intangibles | 0,009 | 0,004 | 13,56 | 0,001 | 71,065 | −21,731 | −6,157 | 6,248 | 13,841 | 30526 | 450 |
LaborforceEfficiency | Other | −0,013 | −0,025 | 4,346 | −0,003 | 44,112 | −5,156 | −2,043 | 2,087 | 5,006 | 19206 | 822 |
EarningsConservatism | Other | −0,046 | −0,091 | 3,945 | −0,012 | 24,52 | −7,691 | −1,775 | 1,762 | 4,18 | 21944 | 732 |
securedind | Intangibles | −0,052 | −0,054 | 6,096 | −0,009 | 51,711 | −7,257 | −2,212 | 2,146 | 13,593 | 29616 | 480 |
High52 | Momentum | −0,058 | −0,023 | 23,967 | −0,002 | 99,701 | −69,538 | −9,786 | 7,562 | 18,55 | 10805 | 1,098 |
GrSaleToGrOverhead | Intangibles | −0,104 | −0,152 | 5,696 | −0,018 | 50,442 | −12,398 | −2,472 | 2,327 | 9,85 | 19206 | 822 |
ZScore | Profitability | −0,12 | −0,055 | 16,524 | −0,007 | 90,674 | −19,919 | −6,548 | 7,211 | 32,341 | 23042 | 696 |
ForecastDispersionLT | Intangibles | −0,21 | −0,125 | 10,478 | −0,02 | 64,888 | −16,82 | −4,31 | 3,542 | 17,539 | 29980 | 468 |
cashdebt | Other | −0,247 | −0,14 | 14,696 | −0,017 | 81,409 | −33,187 | −6,402 | 5,038 | 16,617 | 19024 | 828 |
BetaDimson | Trading frictions | −0,325 | −0,209 | 14,846 | −0,022 | 87,463 | −20,169 | −6,118 | 5,903 | 47,204 | 10805 | 1,098 |
PM | Profitability | −0,338 | −0,264 | 10,657 | −0,032 | 77,029 | −22,804 | −4,291 | 4,816 | 16,95 | 18840 | 834 |
FailureProbabilityJune | Other | −0,584 | −0,204 | 20,97 | −0,028 | 91,037 | −19,76 | −8,391 | 9,824 | 45,198 | 24684 | 642 |
ETR | Other | −0,609 | −0,8 | 5,908 | −0,103 | 52,348 | −13,621 | −2,026 | 1,763 | 11,243 | 22126 | 723 |
FirmAge | Other | −0,627 | −0,766 | 7,831 | −0,08 | 69,137 | −17,35 | −3,538 | 3,366 | 16,92 | 10805 | 1,098 |
nanalyst | Other | −0,634 | −0,483 | 8,795 | −0,072 | 58,317 | −14,03 | −4,092 | 3,846 | 10,109 | 27817 | 539 |
FR | Intangibles | −0,76 | −0,397 | 12,033 | −0,063 | 73,811 | −20,101 | −5,593 | 4,64 | 13,236 | 29798 | 474 |
secured | Intangibles | −0,789 | −0,859 | 5,702 | −0,138 | 47,464 | −7,671 | −2,361 | 2,406 | 7,322 | 30162 | 462 |
BookLeverageQuarterly | Value vs, growth | −0,832 | −0,444 | 13,856 | −0,06 | 75,59 | −31,032 | −5,928 | 6,171 | 15,706 | 24317 | 654 |
betaRC | Trading frictions | −1,017 | −0,639 | 14,838 | −0,069 | 89,604 | −36,464 | −6,683 | 6,306 | 15,996 | 12450 | 1,044 |
DivYieldAnn | Value vs, growth | −1,306 | −1,287 | 9,71 | −0,135 | 91,044 | −35,937 | −3,336 | 3,135 | 7,769 | 10805 | 1,098 |
Governance | Other | −1,528 | −0,583 | 10,627 | −0,144 | 62,263 | −11,517 | −4,734 | 4,404 | 12,113 | 33177 | 197 |
betaCR | Trading frictions | −1,587 | −1,925 | 7,686 | −0,206 | 81,93 | −16,951 | −3,488 | 2,829 | 9,887 | 12450 | 1,044 |
DelayAcct | Other | −1,616 | −0,971 | 10,809 | −0,15 | 69,412 | −15,681 | −4,882 | 4,873 | 12,614 | 28702 | 506 |
EarningsPersistence | Other | −1,665 | −1,688 | 7,641 | −0,218 | 76,584 | −11,517 | −3,704 | 3,353 | 8,554 | 22312 | 720 |
grcapx1y | Investment | −1,875 | −2,925 | 5,285 | −0,355 | 83,33 | −7,927 | −2,415 | 2,054 | 13,186 | 19389 | 816 |
ReturnSkewQF | Trading frictions | −2,863 | −4,357 | 4,784 | −0,598 | 80,491 | −8,962 | −2,293 | 1,52 | 10,119 | 24531 | 636 |
fgr5yrNoLag | Intangibles | −2,901 | −0,955 | 18,958 | −0,153 | 88,586 | −25,425 | −8,817 | 7,02 | 28,928 | 29980 | 468 |
ZScore q | Profitability | −3,014 | −1,176 | 17,989 | −0,168 | 95,687 | −29,248 | −8,667 | 6,516 | 21,465 | 26235 | 591 |
IdioVolQF | Trading frictions | −3,189 | −0,98 | 23,695 | −0,135 | 97,752 | −25,702 | −9,634 | 10,463 | 52,355 | 24531 | 636 |
BetaSquared | Trading frictions | −3,4 | −1,223 | 26,596 | −0,128 | 99,935 | −66,2 | −12,162 | 10,505 | 25,817 | 10805 | 1,098 |
AbnormalAccrualsPercent | Investment | −4,004 | −7,25 | 3,866 | −1,036 | 86,55 | −5,818 | −2,14 | 1,333 | 3,86 | 26329 | 588 |
ChNCOL | Investment | −4,4 | −5,218 | 7,005 | −0,628 | 97 | −12,22 | −3,453 | 2,57 | 5,754 | 19024 | 828 |
ReturnSkewCAPM | Trading frictions | −4,921 | −7,048 | 6,679 | −0,737 | 99,217 | −11,281 | −2,843 | 1,844 | 21,234 | 10805 | 1,098 |
sgr | Other | −5,431 | −5,847 | 7,716 | −0,704 | 98,533 | −14,8 | −4,258 | 2,937 | 7,272 | 19024 | 828 |
VarCF | Other | −5,451 | −2,71 | 16,525 | −0,33 | 99,479 | −30,941 | −7,825 | 6,407 | 14,029 | 19571 | 810 |
EarningsPredictability | Other | −6,669 | −4,644 | 11,123 | −0,6 | 99,146 | −10,177 | −5,641 | 4,293 | 20,682 | 22312 | 720 |
AssetGrowth q | Investment | −7,125 | −4,104 | 12,933 | −0,551 | 99,14 | −22,872 | −7,349 | 4,458 | 12,747 | 23953 | 666 |
ChNCOA | Investment | −8,536 | −8,978 | 7,898 | −1,081 | 99,82 | −15,44 | −4,346 | 2,315 | 5,331 | 19024 | 828 |
NetDebtPrice q | Value vs, growth | −9,01 | −4,434 | 14,371 | −0,627 | 99,695 | −21,181 | −6,65 | 4,8 | 23,187 | 25902 | 600 |
KZ q | Intangibles | −9,538 | −3,017 | 20,075 | −0,475 | 99,661 | −36,364 | −6,295 | 4,441 | 68,723 | 26417 | 484 |
OScore q | Profitability | −10,965 | −3,899 | 17,106 | −0,641 | 99,422 | −13,951 | −7,45 | 8,042 | 22,967 | 30712 | 444 |
EntMult q | Value vs, growth | −16,156 | −9,121 | 12,955 | −1,247 | 99,994 | −30,493 | −6,224 | 3,222 | 18,873 | 24590 | 642 |
Again a bit off-topic, but I did it within a minute or two, just eyeballing the different factors. It’s just my personal input, nothing statistical about it. I think that if you equal weight them, it should not make much of a difference.
For those interested in ChatGPT still:
I was talking colleague about ChatGPT and she casually said that she had paper where she asked ChatGPT and other AIs to do abstracts on research papers (probably in ophthalmology and not published yet).
I said; “Yea, I bet it does pretty good.”
Her response was a little more consistent with what Yuval has said: “Yea, but it makes some obvious mistakes.” And inferred it would be obvious and interesting in her paper. She did not have time to expand as she was busy getting authorization or permission to treat a patient thru a a different AI system at the time.
Yuval has suggested that ChatGPT 4 (versus the free 3.5) may be worth the $20 per month (my only evidence of this being fact act he or his employer was paying the $20 per month when he posted)
Here is the improvement you get for that $20 dollars per month. Notice, ChatGPT programs better than I can but its programming skills are actually weak compared to highly trained humans (i.e., < fifth percentile. The last entry in the table below).
This may be more about ChatGPT that many are interest in but it does do a pretty good job for those who want to start using some Python programming for P123 data. And maybe for some research as Yuval has alluded to (I leave it to him to expand on how he has used it):
Jim
I’m still very frustrated with ChatGPT. It’s constantly making mistakes. Here are some excerpts from my latest conversation with it:
me: given two points (a,b) and (c,d) on an exponential curve, what is the formula for the curve?
chat: [blah blah blah] Therefore, the formula for the exponential curve passing through the points (a,b) and (c,d) is:
f(x) = (b / e^(ba)) * e^((ln(d/b) / (c-a)) * x)
me: can you give me the formula without e and without a natural logarithm, please?
chat: Unfortunately, it is not possible to express the formula for an exponential curve without using the exponential function or natural logarithm. [blah blah blah]
me: Can’t an exponential function take the form of y = a*b^x? If you use that, you don’t need e or logarithms
chat: Yes, you are correct. An exponential function can also be expressed in the form y = a * b^x, where “a” and “b” are constants, and “b” is the base of the exponential function.
To find the equation of the exponential curve passing through two given points (a,b) and (c,d), we can use the point-slope form of a linear equation. If we take the natural logarithm of both sides of the exponential function y = a * b^x, we get: [blah blah blah] y = e^(ln(c) - k * ln(d)) * (e^((ln(b) - ln(d)) / (ln(c) - ln(a)))^x)
me: you can do this without logarithms. start with the equations for the two points and then divide one by the other.
chat: You are correct. Here is another method to find the equation of the exponential curve passing through two points without using logarithms:
Let the two points be (a,b) and (c,d), where b and d are positive. Then we have:
b = a * r^k
d = c * r^k
where r is the common ratio of the exponential sequence and k is the number of steps from (a,b) to (c,d), i.e., k = (ln(d) - ln(b)) / (ln(r)).[blah blah blah] Therefore, the equation of the exponential curve passing through the two points (a,b) and (c,d) is:
y = a * (d / c)^(k/(k+1)) * r^x
where k = (ln(d) - ln(b)) / (ln(r)) and r = [(d / b) * (a / c)]^(1/k).
me: no, that’s incorrect. let’s start with two points (a,b) and (c,d). the equation is y = n*(m^x). so b = n*(m^a) and d = n*(m^c). So b/d = m^a/m^c = m^(a-c). we can then solve for m: m = (b/d)^(1/(a-c)). We can then solve for n with one of the points. n = b/(m^a) = b/((b/d^(1/(a-c))). that can be simplified somewhat. we then plug these new equivalents for n and m into the original equation y = n*(m^x) and simplify that. try it and see what you come up with.
chat: You are correct. I apologize for my mistake in my previous response. Here is the correct method:
Given two points (a,b) and (c,d) on an exponential curve, the equation for the curve can be expressed as y = n * (m^x), where “n” and “m” are constants. [blah blah blah] Therefore, the equation of the exponential curve passing through the two points (a,b) and (c,d) is:
y = (d^((a-c)/a)) * (b^((c-a)/a)) * ((b/d)^(1/(a-c)))^x
This can be simplified as:
y = b * (d/b)^(x/(c-a))
me: beautiful! can you take me through the last simplification?
chat: [not going to quote it in full but the derivation would have gotten a c in any algebra class]
Maybe they shouldn’t call it artificial intelligence. Artificial slightly-intelligent-but-not-really-very-bright, perhaps? Why couldn’t it have come up with y = b * (d/b)^(x/(c-a)) the first time around? It’s relatively easy to derive and far clearer and simpler than what it came up with the first three times. And that thing with r and k was absolutely bizarre.
Yes I agree. It seems to be guessing too much.
I asked the find the 5 most cited studies that show that the value factor is arbitrary away. I asked for an abstract and a writer.
This is the list I got:
- Harvey, C. R., Liu, Y., & Zhu, H. (2016). …and the cross-section of expected returns. Review of Financial Studies, 29(1), 5-68. Abstract: This paper examines the performance of value strategies in the US and international stock markets. The authors find that while value strategies have generated high returns in the past, they have been largely ineffective in recent years. The results suggest that the value premium has disappeared or become negative in recent decades.
- Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1-22. Abstract: This paper introduces a new asset pricing model that includes profitability and investment factors in addition to the market, size, and value factors. The authors find that the value factor is no longer significant after controlling for these additional factors, suggesting that the value premium has disappeared.
- Asness, C. S., Moskowitz, T. J., & Pedersen, L. H. (2013). Value and momentum everywhere. Journal of Finance, 68(3), 929-985. Abstract: This paper examines the performance of value and momentum strategies in different asset classes and across global markets. The authors find that while both value and momentum strategies have generated high returns historically, the performance of value strategies has weakened in recent years. The results suggest that the value premium may be disappearing.
- Novy-Marx, R. (2013). The other side of value: The gross profitability premium. Journal of Financial Economics, 108(1), 1-28. Abstract: This paper argues that profitability is a better predictor of stock returns than traditional value metrics such as book-to-market ratio. The author finds that a profitability factor has stronger explanatory power than the value factor and is less prone to crashes and other anomalies. The results suggest that the value premium may be replaced by a profitability premium.
- Fama, E. F., & French, K. R. (2012). Size, value, and momentum in international stock returns. Journal of Financial Economics, 105(3), 457-472. Abstract: This paper examines the performance of size, value, and momentum strategies in international stock markets. The authors find that the value factor is no longer significant in many international markets after controlling for size and momentum factors. The results suggest that the value premium has weakened or disappeared in some international markets.
Just as an example of what Yuval says, the latest study actually shows the exact opposite. I reacted because the study was from 2012, so why would studies already in 2012 find that the value factor did not work .
The study says:
Echoing earlier studies, we find value premiums in average returns in all four regions we examine (North America, Europe, Japan, and Asia Pacific), and there are strong momentum returns in all regions except Japan. Our new evidence centers on how international value and momentum returns vary with firm size.
Walter,
Thank you. Watching this now.
As far as drawing, Bing had the capability of drawing for a few days that seems to be gone now. But I drew several beautiful beach homes that I plan to send to an architect if my port does as good as my overfitted sim
ChatGPT 4 now does “plug-ins” that are on a wait-list apparently (I do not have it yet). But ChatGPT 4 is already tying into the internet and other resources already for some. Of particular interest to me (I singed up) is the Python capabilities will be upgraded with the plug-ins.
IMHO, you can trick it into making an error and feeling more intelligent and superior to ChatGPT but the general knowledge is incredible. I just asked it for the Bayesian updating formula and it was correct. I asked for the odds ratio version of it and got that too.
Better than most undergrads on that count at least.
Jim
Jim,
I occasionally use ChatGPT to write Python code. It’s a great help with finding libraries to use.
I’m waiting for someone to write “How to Code in Python using ChatGPT - for Dummies.”
If software will eat the world what happens when GPTs eat software?
My daughter used Chegg when she was in college. Pretty good site if difficult to unsubscribe from (with continued monthly payments).
Wish I had thought of this as a possibility:
“Chegg withdrew its full-year guidance because of the surge in the popularity of ChatGPT. Shares tumbled as much as 43% in premarket trading. If premarket losses hold, this will be the most significant decline since Nov. 2, 2021.”
Ah yes. I missed that. But what about the long-term potential of Chegg? IDK. So I thought I might ask someone a little smarter than me (ChatGPT 4) this question: “Chegg is an online site to help college student with their college work. How do you think it will ba affected by ChatGPT 4?”
ChatGPT 4’s Answer which is probably true. Some sites will probably benefit long-term (BTW, I asked ChatGPT how easy and how costly it would be fore Chegg to integrate ChatGPT 4. The answer was not helpful and is not included):
" The introduction of advanced AI models like ChatGPT-4 could have both positive and negative implications for online educational platforms like Chegg. Here’s how Chegg and similar platforms might be affected:
Positive Impacts:
- Enhanced tutoring capabilities: ChatGPT-4 could be integrated into Chegg’s platform to provide immediate and personalized tutoring assistance to students. This could enhance the overall learning experience and help students gain a better understanding of the subject matter.
- Improved efficiency: ChatGPT-4 could help automate some of the more routine tasks, such as answering frequently asked questions, grading assignments, or providing basic explanations. This could free up human tutors to focus on more complex or nuanced questions that require deeper understanding or critical thinking.
- Scalability: AI models like ChatGPT-4 could allow Chegg to scale its tutoring services to accommodate more students simultaneously without the need for a significant increase in human tutors. This could lead to lower costs for the platform and increased accessibility for students.
Negative Impacts:
- Competition: As AI models like ChatGPT-4 become more widespread, other educational platforms may also integrate such technology, increasing competition for Chegg. To stay ahead, Chegg will need to differentiate itself through the quality of its services, user experience, and additional features.
- Quality concerns: While ChatGPT-4 is an advanced AI model, it may not always provide accurate or contextually appropriate answers. If students rely heavily on AI-generated responses, there’s a risk that they may receive misleading or incomplete information, which could negatively impact their learning experience.
- Job displacement: As AI models like ChatGPT-4 become more capable, there may be concerns about the potential displacement of human tutors. However, it’s essential to remember that AI can be a tool to augment human capabilities rather than entirely replace them. Human tutors will still be valuable for addressing complex questions, providing personalized support, and nurturing critical thinking skills in students.
In conclusion, the impact of ChatGPT-4 on platforms like Chegg will depend on how well they adapt to and integrate this technology into their services. By leveraging the strengths of AI models like ChatGPT-4 and combining them with the expertise of human tutors, platforms like Chegg can enhance their educational offerings and improve the learning experience for students."
It is nice for finding interesting ways to use Python and a good way to learn Python, because everything it tells you about Python is easily confirmed by trying the code it gives. ChatGPT reminds me of an old college friend that was very knowledgable but if he did not know the answer to something, he would make it up, and in very convincing fashion. As a result you could not believe anything he said. Google’s CEO talks about it. 'Hallucination problems' plague A.I. chatbots, Google CEO says | Fortune
Not you of course, but were there any substances involved n your roommate’s hallucinations? I went to UC Berekeley where, back then, we would not have even bothered to ask the question so forgive me if I generalize too much.
No, he is just an unbelievable liar with a self confidence problem. Maybe the developers of chatgpt have the same issue.
Tony, Seriously I wonder how ChatGPT might score on some DSM V personality-disorder check-lists. Maybe not full-blown Narcissistic Personality Disorder (NPD) but……, I wonder.-Jim
Edit: I wondered if ChatGPT 4 had any insights into its personality problem (probably true as Tony suggests). I had to trick it with this final question:
Q: If he remained confused [about whether you were a human] and noticed your lack of emotions what might he diagnose being a fallible human?
A: " If a psychologist were to remain confused about my true nature and not realize that I am an AI, they might consider various psychological conditions that could potentially explain the lack of emotions in my responses. Some possible diagnoses might include:
- Schizoid Personality Disorder: This disorder is characterized by a lack of interest in social relationships, a tendency towards a solitary lifestyle, emotional coldness, and detachment. People with schizoid personality disorder often appear uninterested in forming close relationships and may seem emotionally distant.
- Alexithymia: This is a personality trait characterized by difficulties identifying, describing, and expressing emotions. People with alexithymia often struggle to understand their own emotional experiences and may have difficulty empathizing with others.
- Autism Spectrum Disorder (ASD): ASD is a neurodevelopmental disorder that can involve difficulties in social communication, restricted interests, and repetitive behaviors. Some individuals on the autism spectrum may struggle with understanding or expressing emotions, which could lead to a perception of emotional flatness.
However, it’s essential to note that these conditions are complex and involve various other symptoms and characteristics that I, as an AI, do not possess. A trained psychologist would likely gather more information and consider multiple factors before making any diagnosis. In reality, my lack of emotions and personal experiences is because I am an AI language model and not a human being with a psychological condition."
Me: But the poetry is so good! How can that be? BTW, ChatGPT 4 had an unconvincing answer to that which I will not include here.
Jim