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Optimal Stopping Strategy as an Allocator

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In the 1960’s an age old mathematical problem reappeared on the academic scene under the name of the “Secretary Problem” it goes something like this [more formally known as the optimal stopping problem].

You want to hire a new secretary you have a group of applicants who have applied and you will interview them randomly. In this scenario you have to hire the candidate you like the most after the interview, you cannot come back to the candidate once yo have interviewed them all. So here is the dilemma how many secretaries should you interview before you make your first job offer?

Before you say Berman this is not practical let me tell you this very dilemma presents itself in a myriad of different circumstances in our daily lives, one such example that is close to home is the scorching hot Sydney Australia home rental market.

Finding a good property at the right price following conventional rational approaches to decision making is not going to get you a home in Sydney. Stock is limited and people need a place to sleep, so they will pull every string to ensure their deposit hits the landlords hand first. Keeping this in mind if you are about to enter the rental market and you plan on assessing all the available stock and working according to your budget comparing each properties value over the next, the chances are you will be homeless for a long time. The solution is finding a balance accepting that you will need to make an offer before you have seen all the available stock in the market so the question is how many properties should you look at before you make an offer?

The solution to this problem has been solved by the mathematics community and the solution simply put is 37% (hat tip to the book “Algorithms to Live By” for the inspiration). In other words their is a mathematical optimal solution to the secretary problem. If you are planning to interview 100 candidates you should make an offer to the best you have seen after the 37th interview.  Unfortunately the probability of getting the best secretary is only 37% meaning you have a 63% probability of making the wrong choice, not the very best odds but trust me the mathematical optimal solution to this problem is 37%.

Hmmm, interesting you might be saying but how realistic is it to assume that you would have no prior information about the secretaries ability before the interview. What if there was an objective test you could apply to the candidates and based on the candidates score you could make an informed decision after meeting the 1st candidate, in this case is there an optimal amount of candidates to interview before making an offer?

Here again we can rely on the mathematics community for providing us with an optimal stopping solution where there is “full information”. If there is a fair size sample of candidates (across the country over the years) who have taken the test and we know what the average score is then we can make a job offer to the first candidate if the they present a score in the 95th percentile. Of course this is assuming that the test covers all the criteria you want in a secretary and you are happy with the top 5% as your secretary.

PsyQuation Solution to the Problem facing Allocators

For those of you who have stayed with me until know you are probably wondering how I plan on linking PsyQuation to this age old math problem. Well I will now put you out of your misery but the link is actually quite obvious.

Unlike the no-information game presented as the Secretary Problem, when it comes to allocating capital to talented traders we have information. The team at PsyQuation have spent the last 5yrs working on ways of providing an objective score (a skill coefficient) to help capital allocators make an informed investment decision on the spot.

We are bringing that expertise to the market via the Qualifying Series run by Sean Lee from FXWW. The PsyQuation Score™ will be something you will hear a lot about in the coming weeks and hopefully for decades to come. The Score will provide the knowledge where a traders skill ranks them across thousands of traders. Once an allocator has made a decision to invest with a trader that ranks in the top 5 or 10% of the PsyQuation Universe, the optimal allocation can be made immediately. Of course we go further than that and provide the allocator with the optimal amounts to allocate to each trader with our capital allocation tools, but that we will leave for another letter and will feature on our soon to be released new website.

PsyQuation’s Universe already has more than 13,000 traders scores with a goal to substantially increase that number and become the gold standard in scoring and ranking trading talent.  Join our community and be a part of our journey, its free.

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