Your competition is not your peer group.

It is some random kid in a random corner of the world who will out work, out think and out smart you, move for move.

Without either of you being aware of each others existence.

Till the day you come face to face and drop the match point
I haven't found an easy way of explaining this to the talent I work with.

I have to beat it into them.

Junior national champions on tartan track, road runner, graduate and undergraduate students, founders, established tech company CEOs.

It is not enough to win locally.
Even if you win the local game, one day you will have to step outside.

Or the random kid will show up on your home field and show you how to really play the game.

The only way to beat him or her, when that happens is to keep on improving your game.
When it comes to setting standards and benchmarks look outward.

Your team will call it tough love. My students and mentees call me the fat bastard.

But I would rather that they hate me now then lose that bid to the other guy, just because he had a better, meaner, nastier coach.
If in the last 26 years our paths have crossed and I have been unreasonable, rude or difficult, now you know.

I don't want you to drop the ball. I don't want to pamper or cajole you. I just want you to be someone you can be.

Yes it hurts, yes it's difficult. And yes you hate me
One day you will understand. I don't enjoy being rude. Or being angry. I feel bad for hours afterwards.

You will never forgive me.

One day the work you didn't want to do will open doors you didn't think would open for you.

You still won't forgive me, but you will understand.

• • •

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More from @rebootdude

29 Apr
In the modeling world we use a term marking a model to market.

If you have a pricing model and use that to estimate price of a security, how far off are your estimates compared to the market?

The mismatch between the model price and the market price is your model error. Image
With some models we let the error ride. With others we need to calibrate it down to zero.

A family of models where the pricing model is calibrated to match current market prices is called an arbitrage free model.

Remember the BTC model we built a few days ago. Not arb-free. Image
You can see the fit is not strong. There is a significant mismatch between actual market prices and model prices.

Here are two variations of the same model with market price calibration related adjustments. Still not arbitrage free, but much better fit. Image
Read 7 tweets
28 Apr
Happy birthday @AminFarid14 and @fawzia71

Here is a walk down memory lane with our school drives play list.

1 - I want to talk about me.

Our favorite - the one that mama and I always loved playing. Still do.

2- I hope you dance -
And now for one of your. The one that was too loud for us but you eventually won us over.

3 - Gotta be somebody

Read 7 tweets
27 Apr
What is the 3rd moment? The @GoldmanSachs question that floored me 23 years ago.

Let's say you are modeling Bitcoin prices. You want to get a better sense of how much prices can move in a given day.

You have the price series. You calculate daily price changes. You plot both.
It is a good first step, better than raw data but you can do better than this.

You use the Excel function to organize daily price changes into something more meaning full.

You organize, bucket and plot the daily price change frequency and end up with a histogram.
You now have a sense of the most common change (between -1% and 2.6%) and the extreme changes (-14% and 15.5%)

The histogram is a plot of this table. A ordered tabulation of the price change series that you had calculated above.

The both describe the statistical distribution
Read 29 tweets
27 Apr
In recruiting the person sitting on the other side can tell when you don't want the job.

I have only interviewed a few time for roles as a prospective employee. In tech, banking and consulting.

I have interviewed many times more as an employer in tech, sales and consulting.
Here is a stroll down memory lane for those who are still looking for roles in a really hard year.

Interviewed with 2 leading consulting firms. One in Boston, one in New York.

Loved the one in NYC. Got the offer.

Didn't care about the one in Boston. Didn't get the offer.
A year earlier had interviewed with @GoldmanSachs in London for a pre-MBA internship. They picked four of us across Europe and Asia for London.

I had fallen in love with modeling by then. Yet tripped on a basic question. How would you explain 3rd moment to your grandmother?🤦
Read 15 tweets
27 Apr
New stuff I learned in year of Covid-19.

This is my father's favorite question, what did you learn this week, month, year? Helps internalize learning.

The promised professional version.
Figured how to sound proof office library and turn it into a recording studio.

@MasterMoltyFoam sheets. Cut into squares and rectangles with ridges etched into them.

Tried a recording box but that just deadened sound.

The key is reflecting surfaces. Find them. Kill them.
You don't have to stick them on the walls or roof. Tried that, didn't work.

Spread the foam squares on your table, edges and corners and it works just as well.
Read 25 tweets
26 Apr
This summer marks my 34th year of playing with numbers.

As an actuary, a model builder, a computer science and computational finance specialist.

My first model, 1988. A financial model on a Lotus 123 spreadsheet.

I was a teenage intern at Next Hardware Shop. Image
3 internships had seen me grow from answering phones, filing paperwork to being useful when I was not blowing up power supplies.

To be honest I was replicating a paper model on Lotus 123. Not rocket science but linking cells on a screen was more fun than stuff I had done before.
Across 3 decades, I have realized that us quantitative types often keep equations in our head that drive our behavior, our responses, our actions.

Good old give and take. I will put this much effort in, I will get this much back. Plus, minus.

It makes us transactional beings.
Read 16 tweets

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