Study of Horse Handicappers

December 10, 2020 |

Big Al writes:

Behavioral Problems of Adhering to a Decision Policy Paul Slovic Oregon Research Institute, Eugene, Oregon  Paper presented at the Institute for Quantitative Research in Finance May 1, 1973, Napa, California

https://scholarsbank.uoregon.edu/xmlui/bitstream/handle/1794/23607/928.pdf?sequence=3&isAllowed=y

Another example of inconsistency comes from a study of expert horse-race handicappers, which we are currently conducting at the Oregon Research Institute. We're not really interested in horse-race predictions, we're studying the stresses caused by information overload, and horse racing provides an appropriate context in which to  do this. We expect that the results will generalize to any domain in which the skilled integration of large masses of quantitative information is performed by means of human judgment. For horse-race

handicapping is an information game, much as investment analysis is an information game, and although there are many differences between these two domains of risk-taking, there are many similarities as well.  Figure 1 shows a typical past-performance chart, which gives detailed  information about each horse’s recent performances. It doesn't take too much imagination to see the similarities between these kinds of charts and the data sources used in some forms of financial analysis. Our judges in this study were eight individuals, carefully selected for heir expertise as handicappers. Each judge was presented with a list of 88 variables culled from the pastperformance charts. He was asked to indicate which five variables out of the 88 he would wish to use when handicapping a race, if all he could have was five variables.

He was then asked to indicate which 10, which 20, and which 40 he would use if 10, 20, or 40 were available to him.  Before examining inconsistency, though, let's look at how accuracy and  confidence varied with amount of information as shown in Figure 4 of  the handout. We see that accuracy was as good with five variables as  it was with 10, 20, or 40. The flat curve is an average over eight subjects and is somewhat misleading. Three of the eight actually showed a decrease in accuracy with more information, two improved, and  three stayed about the same. All of the handicappers became more confident in their judgments as information increased.

In Table 1, we see a comparison of the amount of inconsistency in our handicappers’ judgments at low and high levels of information.

Consistency was measured in three ways—by the number of times the first-place horse was changed when the race was judged the second  time, by the number of changes in any of the five ranks, and by the  sum of the differences in ranks from one time to the next. Each of  these measures told the same story—there was considerable inconsistency in the rankings, and this inconsistency increased as the amount of available information increased.

These results should give some pause to those of us who believe we're better off by getting as many items of information as possible, prior to making a decision.

US voters largely hold as good mechanics, if it ain't broke don't fix it. For Boris if still here opening lines of AC tell a lot about the topical, unintentionally; something for Lindsey and Schumer and maybe to close it, he ain't no boss. And like science, music takes political sides it seems; I disdain - wish someone would just show me the lists what I'm suppose to believe and what to say. I do get reverence to one's fellow carbon forms btw.

most for skimming:

Big Al got me moving on this, I still have much more, but it's locked in my brain vaguely and still can't get to the speaking or typing part.  As usual, others can translate below or even my vague thoughts, still in labor. And few have already.

If this gentleman, Allan Lichtman has already been shot down, scuse.

More important is the set or transit ors (a cleverism to make binarys as a set against impeders) seismic shifts shake the status quo at the top, making the presentation and focus of false ones more understandable for me about the process. Five or fewer keys false, incumbent wins; (6, in this case 7 keys false) incumbent loses.  –so far, unless SCOTUS wants political upheaval, and they're made to hate politics while endorsing their view on lawful governance.

begin @1:30

2)"wik:The 13 Keys

"The Keys to the White House is a checklist of thirteen true/false statements that pertain to the circumstances surrounding a US presidential election:

Midterm gains: After the midterm elections, the incumbent party holds more seats in the U.S. House of Representatives than after the previous midterm elections.

No primary contest: There is no serious contest for the incumbent party nomination.

Incumbent seeking re-election: The incumbent party candidate is the sitting president.

No third party: There is no significant third party or independent campaign.

Strong short-term economy: The economy is not in recession during the election campaign.

Strong long-term economy: Real per capita economic growth during the term equals or exceeds mean growth during the previous two terms.

Major policy change: The incumbent administration effects major changes in national policy.

No social unrest: There is no sustained social unrest during the term.

No scandal: The incumbent administration is untainted by major scandal.

No foreign/military failure: The incumbent administration suffers no major failure in foreign or military affairs.

Major foreign/military success: The incumbent administration achieves a major success in foreign or military affairs.

Charismatic incumbent: The incumbent party candidate is charismatic or a national hero.

Uncharismatic challenger: The challenging party candidate is not charismatic or a national hero.

When five or fewer of the above statements about an upcoming election are false, the incumbent party candidate is predicted to win the election. When six or more are false, the incumbent party candidate is predicted to lose the election.

By "incumbent party", Lichtman means the party to which the incumbent President belongs. In the 2016 election, the Democratic Party was the incumbent party as then-President Barack Obama was a Democrat. Obama was in his second term and thus was ineligble for re-election, so Hillary Clinton ran as the candidate for the Democratic Party, i.e. she was the incumbent party candidate. Donald Trump was the candidate for the Republican Party, i.e. he was the challenging party candidate.

Some of these keys can be judged using objective metrics, such as economic growth, and some of these keys are of rather subjective nature, such as candidate charisma. In the latter case, a forecaster must evaluate the circumstances of all past elections together so that his judgments are at least consistent if not objective, and then observe how his judgments retroactively predict historical election outcomes so that he can refine his subjective standards into something reliably predictive for future elections.[1]"

3)other - one scientific answer may be better suited to another science:

"While predictions of earthquakes eluded his methods and algorithms, they seem to have succeeded in another, completely unrelated field. In 1981 the Russian Keilis-Borok teamed up with an American 26 years his junior. His partner was Allan Lichtman, a political historian at the American University in Washington, D.C. Together they applied the algorithms which would ultimately fail in predicting earthquakes to the US election system. In November 1981 the duo published its results in an article with the very long, unwieldy title "Pattern recognition applied to presidential elections in the United States, 1860-1980: Role of integral social, economic, and political traits" in the Proceedings of the National Academy of Sciences in Washington (Vol. 78, pg. 7230).

And what happened? Using this method, Allan Lichtman has correctly predicted the outcomes of the past eight presidential elections in the United States. And now - in contrast to all other pollsters and talking heads - he was the only one to consistently tell all of us who wanted to listen, that the 45th president of the United States was going to be Donald J. Trump. With his statements Allan Lichtman was the lone voice in the desert and has posthumously vindicated the work of Keilis-Borok, who passed away three years ago in his home in Culver City in the Los Angeles Area."

https://seismo.berkeley.edu/blog/2016/11/13/predicting-presidents-and-not-earthquakes.html

`SELECT * FROM wp_comments WHERE comment_post_ID = '13111' AND comment_approved = '1' ORDER BY comment_date`