Author Archives: kchodorow

When a friend IM’d me and told me she saw an article saying that MongoDB had filed for IPO, I embarked on a months-long journey of discovering that I knew nothing about IPOs. I found it a bit difficult to get information about them, so I figured I’d write up what I learned. This is mostly from other people/things I read online, so please leave a comment if I got anything wrong/missed anything.

An IPO is a chance for the company to raise funds. Being a publicly-traded company also forces them to have more transparency in accounting and other good things, but the IPO itself is mostly a fundraising event: the company is selling X shares for $Y.

The first thing a company does is find some underwriters, which are large banks who try to sell the offering. Then the company files a confidential S-1 (probably). The confidential version lets them go back and forth with the SEC and iron out any details. Apparently there have been some embarrassing S-1s in the past where companies gave out trade secrets, had blatantly bad accounting, etc. Generally this stage will last a while, as the SEC tends to have suggestions. The SEC could come back with major issues and the company might decide not to file after all. Basically, at this point, you know nothing about anything. But there’s hope.

If all goes well with the SEC, the company will publicly file their S-1. You can find public S-1s on Edgar, the SEC database, but this will still give you approximately no information. Okay, it has profits and losses and risks and all sorts of information that you’re probably interested in if you’re an investor, but if you’re a techie you’re probably looking for the opening price and that probably won’t be there yet. This is because the company will keep amending the S-1 as the IPO approaches. I recommend subscribing: you can ask Edgar to alert you every time there’s activity for a given company.

At a certain point, the IPO date will be announced. You can find a calendar of upcoming IPOs on the stock exchange’s website (e.g., NASDAQ’s calendar). One thing I found confusing was that the day listed was actually the day before what I’d think of as the IPO: the day listed is the “pricing day” when they decide on the price to open at. About a week before this date, a possible opening price will be announced (i.e., the S-1 filing will be amended). This is subject to change, MongoDB’s original projection was $18-$20, then $22, then ended up opening at $24.

Some companies will do a “road show,” where they present what the company does to investors. Honestly, if MongoDB did one of these, I totally missed it. Of course, I’m not the target audience, so maybe it happened.

Around this time, the underwriters will find institutional investors to buy the initial offering. At the point the stock goes on sale, hopefully a large portion of offering has already been spoken for. However, the company doesn’t want the entire offering to be spoken for, so they can take advantage if the price “pops” on the opening day.

Another thing underwriters do is gauge excitement and try to choose a good opening price. A good opening price is as high as possible (to raise the maximum amount for the company) while still allowing it to “pop” sufficiently the first day. There is a psychological factor here (investors like it when the stock jumps the first day) and a practical one: the investors the underwriters convinced to invest in the IPO want to get a 20-30% return. In one day. This blows my mind: if you want to make money off of a startup, obviously the best way isn’t to be involved in one at all. Just work on Wall St. Sigh.

The next morning, at least for NASDAQ, you can look at the NASDAQ Facebook page to get a livestream of the event. It happened at ~10:30, although I thought the market opened at 9:30. So that was a little confusing. Some stock market guy will go up, say a couple of words, and introduce the company president. That guy will get up, say some stuff about the company (MongoDB’s the first DB company to go public in 27 years!). Then they get a bunch of people from the company onstage, there will be a countdown, the company president gets to “ring the bell” (which, AFAICT, is now touching a button on a touchscreen, which was a little sad) and then trading starts.

But not for you.

Remember the option agreements you signed? Me neither, but there’s a clause that’s called a “lock out period.” This is to prevent current/former employees (and investors) from dumping their stock and driving the overall price down. Since a main goal of an IPO is to raise money for the company (and, apparently, fat cats, grr), they don’t want a free-for-all when trading opens. Thus, you have to wait 6 months to start selling your equity. If you do not, the SEC will hunt you down and fine the crap out of you.

10 days after the IPO, the “quiet period” will end. This is when “insiders” (AFAICT, anyone on Wall St) will publish what they think of the company: buy/sell/hold recommendations. This is interesting and will give you an idea about what large banks think the price should be, but again, there are no guarantees.

At 6 months, the lock out period will expire. Generally around this time the stock will dip, as everyone’s expecting a lot of noobs to be dumping their equity.

All in all, it’s a very slow process. I expected it to be more fast-paced and dramatic, but it’s basically several months of speculation and then a few days of activity.

Resources:

• I found Seeking Alpha had good financial analysis before the event.

I was standing on the street corner with Domino and a group of schoolkids came up. “Hey, can I show you a magic trick?” one of them asked.

“Uh…”

“Think of a number,” he said.

“Ok.”

“Now add 4 to it.”

“Ok.”

“Now add 5 to it.”

“Ok.”

“Now add 1 to it.”

“Ok.”

“Now subtract your original number from it.”

“Ok.”

“Did you get 10?”

“Nope!”

“What? What number did you choose?”

“I was using a different base. If you’re using base 16, then 4, 5, and 1 don’t add up to 10. Don’t kid a kidder, kid.” Then I flipped him a nickel and his head exploded with the power of math.

Well, not really. I wish I had the presence of mind to do that. But next time an elementary school kid tries that, I’m so ready.

I’ve been reading P.T. Barnum’s autobiography and came across an interesting passage about when he was employed at Mr. Taylor’s (maybe of Lord & Taylor’s? Not sure) shop:

My employer manifested great interest in me, and treated me with the upmost kindness, but the situation did not suit me. The fact is, there are some persons so constituted that they can never be satisfied with labor for a fixed salary, let it be never so great. I am one of that sort. My disposition is, and ever was, of a speculative character, and I am never content to engage in any business unless it is of such a nature that my profits may be greatly enhanced by an increase of energy, perseverance, attention to business, tact, etc.

He also sounds like quite an ass and a racist, but it’s an interesting read.

I’ve been messing around with Keras, a ML library that makes it pretty easy to do AI experiments. I decided to try out image recognition, so I found a picture of Domino in a fez:

Then I wrote the following Python program which uses the existing ResNet50 image recognition library.

import numpy as np
from keras.preprocessing import image
from keras.applications import resnet50

# Load the image
img = image.load_img('fez.jpg', target_size=(224, 224))
input = image.img_to_array(img)
# Keras can process an array of images, but we're only passing one, so turn it into an array with one element.
input = np.expand_dims(input, axis=0)
# Normalize the RGB values into a 0-1 range, since ML algorithms get thrown off by big ranges.
input = resnet50.preprocess_input(input)

# Predict what's in the photo.
model = resnet50.ResNet50()
predictions = model.predict(input)
predicted_classes = resnet50.decode_predictions(predictions, top=10)

for _, name, liklihood in predicted_classes[0]:
    print("this is an image of {} {}".format(name, liklihood))

In addition to the obvious prereqs, you have to sudo apt-get install libhdf5-dev; pip install pillow certifi h5py.

This prints:

this is an image of Bouvier_des_Flandres 0.4082675576210022
this is an image of briard 0.3710797429084778
this is an image of Newfoundland 0.10781265050172806
this is an image of giant_schnauzer 0.04042242094874382
this is an image of Scotch_terrier 0.038422249257564545
this is an image of komondor 0.012891216203570366
this is an image of Tibetan_terrier 0.0026010528672486544
this is an image of affenpinscher 0.0024157813750207424
this is an image of standard_poodle 0.0021669857669621706
this is an image of Kerry_blue_terrier 0.002110496861860156

It’s pretty solid on “it’s a dog.” I’m disappointed in the lack of fez-related IDs. However, I like some of these as possible breeds for Domino:

So, still needs some work. But not bad for less than 30 lines of code.

Here is what my inbox look like each morning:

All those pink-tagged messages are emails from GitHub. Gmail cannot figure out which ones are important and GitHub’s notification stream, in my experience, is useless. It’s noisy and doesn’t clear the way I’d expect. The problem is, people actually do mention me on bugs. And I often have no idea.

So, I made my own notification system. It’s a Chrome extension that is a little ear that sits next to your location bar. If you have an unread GitHub notification, it turns red. If you’re all caught up, it’s green.

If this would be useful to you, please give it a try!

Download the Chrome extension here.

Feedback and suggestions welcome!