Lessons from Aneel Bhusri

While at Workday this summer, I had the pleasure of attending a fireside chat featuring the company’s co-founder and CEO, Aneel Bhusri. Below are my annotated notes.


  • An MBA is not that valuable unless it is from a big name school where the network makes it worthwhile.
  • Mentors are everything.
  • No one has any idea how the markets will play out.
  • For choosing a place to work, culture is more important than the product.
  • Social media has had both good and bad impact, Workday makes businesses better and people more productive.
  • [Aneel] would work at Amazon, Jeff Bezos is “brilliant”.
  • Always ask: how can you make society better?
  • Workday has 30% of Fortune 500, Oracle/SAP 7%, rest undecided
  • Questions matter: best to ask great questions and then shut up and listen.
  • Questions to ask when choosing a first job:
    • Where are the best mentors?
    • What size company do I work best in? What is my risk tolerance?
    • What do they do that is defensible?
    • Do I like their tech stack?
  • Startups/SV are in a bubble now, super overfunded.
  • Workday moving from SaaS -> PaaS -> DaaS a la Amazon and Salesforce
    • Want startups to be able to form in the Workday ecosystem
    • $1B revenue from platform predicted (timeframe?)
  • Take care of your customers and employees: “Best place to work” correlates with stock price.
  • Your best salespeople are your existing clients.
  • Great employees are the lead domino.
    • Leads to taking care of customers and building a great product
  • Employees join companies and leave managers.
  • Workday’s moat: tying together the plan, execute, analyze cycle into one solution.
  • AI and ML are just tools, you need to focus on the problem first.
  • Best use of ML right now still has humans in the loop for decision making.
  • Better writer equals better communicator equals better leader/manager
    • Workday adopted Amazon’s practice of writing reports for meetings.
  • Founder led companies are generally more innovative than professional-CEO led companies.
  • Recruiting is always the hardest part.
  • Need to stay ahead of technology disruptions (how?)
  • On being a great leader:
    • Optimism
    • Work within your own personal leadership style
    • Learn to manage different types of people (salespeople vs engineers)
  • Learn as much as you can from great mentors.
  • Need to define and incentivize your core values if you want people to follow them
  • The hardest thing is letting people go who are talented, but don’t fit the core values.

Takeaways from Jane Street’s Electronic Trading Challenge

Last weekend, I had the pleasure of attending Jane Street’s Electronic Trading Challenge. Two fellow interns and I formed a team to compete in a simulated market to see whose bot could generate the most money. We took third place in the first part of the competition, but didn’t do so hot in the second part. Unfortunately, there were only prizes for the first place team in the second part, so we didn’t win anything :(. Regardless, I had an awesome time and it was fun to learn about something that I’d previously had very little exposure to.

You can see our code here: https://github.com/charlieyou/jsetc


Competition Setup

It’s a 10 hour competition split into two parts: the first being nine hours, running continuously; the second being the last one hour where everyones’ points reset back to zero.

There is a simulated market containing seven securities available to trade: GOOG, AAPL, MSFT, NOKIA, BOND, NOKADR, and XLK. GOOG, AAPL, MSFT, and NOKIA each had fair values that were random and unknown. BOND’s fair value was known to be 100, NOKADR was an ADR of NOKIA, and XLK was an ETF of the four first securities. The price of each security on the market was random around it’s underlying fair value. The ADR and ETF had the same fair value of the sum of it’s underlying securities, but were much less liquid.

For five minutes, you and another bot trade against each other in this simulated market to see who can walk away with the most money.

What We Did

First, we traded BOND whenever the ask was below 100 or the bid was above 100. This gave us some profit to start, but not much. We then moved onto parallel development of three other strategies: ADR pair trading, mean reversion, and fair value prediction.

The NOK* ADR pair had the same underlying value, so when their prices would diverge, we traded both in the direction of the other. Like trading BOND, this was fast and easy to implement, but didn’t give us that much profit.

Mean reversion was the main thing I worked on, but ultimately could not get it to be profitable enough to deploy. This is because the price of the securities was stochastic and therefore not predictable with mean reversion. Unfortunately, I didn’t reflect on this during the competition, so lots of time was wasted implementing and testing this.

Fair value prediction was our main money-maker but was also very finicky. We would use an exponential moving average to try and predict the fair values of the first four securities, then trade them in the direction towards this fair value. There was lots of tuning done with the exact way that we calculated the prediction and the high computation involved led our both to be quite slow.

Because we got such an early start in getting something to work, we jumped to second place and stayed there for the majority of the competition until we were moved to third by the team that would ultimately take first in both the first and second parts. Our performance in the second part was lackluster at best: we finished in the middle of the pack (15/30). I hypothesize that this was because our bot was slower than most and thus couldn’t keep up with the trading speeds of the other final bots. However this doesn’t explain how we did so well in the first part. I attribute this to us getting a large head start on everyone at first and to randomness. Unfortunately, we’ll never know the exact reasons.

What the Best Team Did

One team absolutely dominated everyone else in the second portion of the competition: they scored over one hundred thousand points where the next best team was at thirty thousand with most in the under ten thousand range. Afterwards, I asked them what their strategy was and they graciously shared with me:

Like us, they started with only trading BOND to get something going as quick as possible, then moved onto NOK* ADR pair trading. Our strategies differed in that they didn’t simply average the two symbols, they weighted the more liquid one higher.

They made the majority of their money with a strategy that we tried to implement, but ultimately ran out of time to: ETF arbitrage. Whenever the price of the ETF and the sum of it’s underlying securities would diverge, they would trade the ETF in the direction of the difference. They hedged this trade 5:1 and could control the frequency of trading by adjusting the threshold by which a trade was made.

Three other things that they did that gave them an edge:

  1. Coded everything in C++, which made them faster than whoever they were trading against (almost everyone else used Python or Java).
  2. Limited the orders on the book to only two, canceling any orders that were made based on old information.
  3. Kept track of what was in their portfolio at all times, letting them execute some optimizations based on the holding limits.

Other Takeaways

One thing we did well was to setup our codebase so that everyone could easily develop and test strategies independent of one another. The strategies used on each test or deployment were specified on the command line, so no additional code changes were needed besides adding the file containing the subclass were needed.

What we didn’t do such a good job of was our actual deployment system onto the server. We would push code to git and then pull it on the server. This was perhaps the worst way to do it. It caused lots of unnecessary commits and made us get lazy with our version control, leading to multiple problems later on. In addition, we had separate folders for each person’s working code on the server, but they were not named very distinctly. There were times when someone would accidentally overwrite something in someone else’s folder, causing issues with lost code and developer time due to confusing errors.


Overall, the event was extremely well run and I highly recommend that anyone attend it if they can. I will definitely be applying for Jane Street’s summer internship as I’d like to get a better sense of the work that they do as well as the tech behind it.

Update (2017-09-06): Jane Street rejected me for a summer internship :(.

Speaker Notes from Internapalooza 2017

Last Tuesday, I had the pleasure of being able to attend Internapalooza, a large gathering of interns in the Bay Area. While definitely not a flawless event (see my recommendations at the bottom, it was definitely worth checking out!
It started out with a Q&A with one of my favorite influencers, Naval Ravikant, followed by Dropbox CEO Drew Houston. In the middle were some not-so-great speakers, but there was a strong finish with a Q&A with Andrew Ng. My notes from the three named speakers above are below followed by some of my recommendations for the event.

Speaker Notes

Naval Ravikant:

  • What you work on is more important than how you work on it
  • Don’t let anyone control you, don’t try to live up to anyone else’s expectations, don’t be afraid to change your mind
  • Deep understanding of the basics will take you farther than just the specifics of just one thing
  • Be the hero of your own movie
  • Reframe setbacks as growth opportunities

Drew Houston:

  • Ask for responsibility, take initiative
  • Compound your learning
    • Learn to learn
    • Always find opportunities for learning
    • Ask people to book recommendations, things to learn
    • Take the path that optimizes for learning
    • Throw yourself into the deep end
    • Run towards the discomfort
  • Networking pays off in ways you can’t expect

Andrew Ng:

  • Follow good mentors
  • Be wary of joining a company that won’t tell you your team/boss until after you sign
  • Read papers and try to replicate state of the art results
  • Have a significant project
  • AI is the new electricity, every industry will be changed
  • Healthcare, education most promising/underhyped
  • Transfer learning interesting, GANs, RL as well
  • Most economic value in supervised learning
  • Large companies have advantage for larger verticals (search, etc) bc of larger datasets
  • More specific verticals super viable for startups, can form data accumulation loop
  • Go to San Francisco or Beijing
  • Don’t necessarily need advanced degree, company experience fine as long as you learn, increasingly more based on what you can do
  • Be a lifelong learner

Recommendations

There are three things I would change to improve Internapalooza (besides removing the ‘a’ in the middle of the name).

Make it a premium event. Because it was free, I don’t think most attendees gave the speakers the respect they deserved. If it was paid, there would have been a smaller but much more engaged audience. I felt that there were far too many people there for the space anyways. At times it was hard to even walk around without pushing your way through. In addition, it would have been nice to have food there since the event occurred during dinner time. I understand that this was not possible because of financial reasons, and this is yet another reason to sell paid tickets.

Having company booths there felt like an afterthought. It seemed to have been pitched to us as a career fair-type event, but resumes were not allowed and the experience from booth to booth was very inconsistent. Some were taking names, some were just there to provide information, and some were demoing their tech. It’s as if companies were not told what to expect as well.

The speakers who were sandwiched in between the keynotes seemed not to have prepared very much for it. As a result, their presentations were boring at best. At one point, a speaker started to pitch us his startup as if we were a crowd of VCs. Know your audience!

Although, overall, it was definitely worth going to just for the three speakers I took notes for and I look forward to seeing what it becomes in the future.