Anyone have any opinions on how self-insured employers consider innovative healthcare offerings to pass on to their employees?
As I understand it, by shouldering the financial risk, self-insured employers can curate a list of more relevant benefits ... (1/10)
I'm thinking about benchmarking to Accolade's average contract value for self-insured employers, as well as the savings it generates, to help dimension how cancer screening could diffuse into this market. (9/10)
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I’m torn on how to approach the idea of luck. I’m the first to admit that I am one of the luckiest people on the planet. To be born into a prosperous American family in 1960 with smart parents is to start life on third base. The odds against my very existence are astronomical.
I’ve always felt that the luckiest people I know had a talent for recognizing circumstances, not of their own making, that were conducive to a favorable outcome and their ability to quickly take advantage of them.
In other words, dumb luck was just that, it required no awareness on the person’s part, whereas “smart” luck involved awareness followed by action before the circumstances changed.
So, was I “lucky” to be born when I was—nothing I had any control over—and that I came of age just as huge databases and computers were advancing to the point where I could use those tools to write “What Works on Wall Street?” Absolutely.
Was I lucky to start my stock market investments near the peak of interest rates which allowed me to spend the majority of my adult life in a falling rate environment? Yup.
Ironies of Luck https://t.co/5BPWGbAxFi
— Morgan Housel (@morganhousel) March 14, 2018
"Luck is the flip side of risk. They are mirrored cousins, driven by the same thing: You are one person in a 7 billion player game, and the accidental impact of other people\u2019s actions can be more consequential than your own."
I’ve always felt that the luckiest people I know had a talent for recognizing circumstances, not of their own making, that were conducive to a favorable outcome and their ability to quickly take advantage of them.
In other words, dumb luck was just that, it required no awareness on the person’s part, whereas “smart” luck involved awareness followed by action before the circumstances changed.
So, was I “lucky” to be born when I was—nothing I had any control over—and that I came of age just as huge databases and computers were advancing to the point where I could use those tools to write “What Works on Wall Street?” Absolutely.
Was I lucky to start my stock market investments near the peak of interest rates which allowed me to spend the majority of my adult life in a falling rate environment? Yup.
Nano Course On Python For Trading
==========================
Module 1
Python makes it very easy to analyze and visualize time series data when you’re a beginner. It's easier when you don't have to install python on your PC (that's why it's a nano course, you'll learn python...
... on the go). You will not be required to install python in your PC but you will be using an amazing python editor, Google Colab Visit https://t.co/EZt0agsdlV
This course is for anyone out there who is confused, frustrated, and just wants this python/finance thing to work!
In Module 1 of this Nano course, we will learn about :
# Using Google Colab
# Importing libraries
# Making a Random Time Series of Black Field Research Stock (fictional)
# Using Google Colab
Intro link is here on YT: https://t.co/MqMSDBaQri
Create a new Notebook at https://t.co/EZt0agsdlV and name it AnythingOfYourChoice.ipynb
You got your notebook ready and now the game is on!
You can add code in these cells and add as many cells as you want
# Importing Libraries
Imports are pretty standard, with a few exceptions.
For the most part, you can import your libraries by running the import.
Type this in the first cell you see. You need not worry about what each of these does, we will understand it later.
==========================
Module 1
Python makes it very easy to analyze and visualize time series data when you’re a beginner. It's easier when you don't have to install python on your PC (that's why it's a nano course, you'll learn python...
... on the go). You will not be required to install python in your PC but you will be using an amazing python editor, Google Colab Visit https://t.co/EZt0agsdlV
This course is for anyone out there who is confused, frustrated, and just wants this python/finance thing to work!
In Module 1 of this Nano course, we will learn about :
# Using Google Colab
# Importing libraries
# Making a Random Time Series of Black Field Research Stock (fictional)
# Using Google Colab
Intro link is here on YT: https://t.co/MqMSDBaQri
Create a new Notebook at https://t.co/EZt0agsdlV and name it AnythingOfYourChoice.ipynb
You got your notebook ready and now the game is on!
You can add code in these cells and add as many cells as you want
# Importing Libraries
Imports are pretty standard, with a few exceptions.
For the most part, you can import your libraries by running the import.
Type this in the first cell you see. You need not worry about what each of these does, we will understand it later.
