An arms race has resumed amongst the world’s biggest hedge funds. Seeing the potential of the technologies produced at some of the most prolific Machine Learning groups in big tech companies such as Google and Facebook, a recent article notes that hedge funds are lifting lead Data Scientists to work on building better alpha strategies.
In the past, algorithmic trading prided itself on hiring highly skilled statisticians to sculpt informative signals and combine them in a state-of-the-art model to predict movements in prices. With the success of deep learning software, such as IBM’s Watson, hedge funds now see potential in throwing their financial big data at artificial intelligence at these artificial intelligence black boxes to predict alpha.
Bridgewater hired David Ferrucci, former lead engineer at IBM for developing Watson, Renaissance Technologies was founded by Bob Mercer and Peter Brown, former language recognition leads at IBM, and recently Blackrock hired Bill MacCartney, a former Google scientist.
For these robotics rockstars moving from Tech to Finance, one downside is that there work becomes a lot more secretive. The nature of algorithmic trading is very hush hush with all hedge funds in direct competition with each other. Compared to publishing research papers at IBM or Google, the traders at these funds will have to keep their advances to themselves – which is a loss for the rest of the scientific community.
As we move towards more technological capability and deferring judgement and decision to artificial intelligence, some difficult ethical questions will come up.
A recent article in TechnologyReview highlights how self-driving cars will be programmed to make tradeoffs in difficult situations. The use of the image to the left demonstrates the type of situation in which a self driving car may have to deliberately chose to kill one person to save many people.
It gets even more confusing when we think about one adult vs one child, a cyclist vs a car, a passenger vs a pedestrian. There will be a huge new body of research in practical ethics and applied philosophy that companies such as Google will be looking to for guidance.
I had the pleasure of video-conferencing into Kellogg‘s MBA class in Social Media at Northwestern University yesterday. Brayden King kindly invited me to talk about how Airbnb thinks about Trust and the challenges facing sharing economies.
We spoke about the role of Data Science at the company and how it has changed over the years. As the volume of data has grown, we have more often than not moved away from explanatory predictive models to Machine Learning algorithms.
One thing that stood out to me as top of mind for the students in the MBA class was the process of Trust development for first time users. How does a first time guest get accepted by a host on Airbnb? How does a first time host get selected by a guest?
At Airbnb we have a team of highly skilled Data Scientists and Engineers working on matching algorithms designed to help first time guests and hosts. And even more than this, the community are their own best resource. Experienced hosts help new hosts manage their listing and new guests book their first experience.
At the heart of everything data-related we work on at Airbnb is the community and enabling them to make more connections amongst themselves and new users.
I recently joined Cyberlaunch, the world’s leading accelerator for information security (Infosec) and machine learning (ML), as a Mentor for their startup companies.
Last week they launched a Startup Challenge to find the brightest solutions to challenging Infosec and ML problems. There are two prizes, each worth over $150,000.
Its sure to be a very competitive field and I am looking forward to the entries!
A recent survey by eFinancialCareers of their CV database has put Imperial College London at number 8 in the world wide rankings for best places to prepare for a financial career in Data Science. This is hot off the heels of the launch of their new Data Science Institute last year and the new MSc Business Analytics.
The usual East Coast (CMU, Columbia, NYU) and West Coast (Stanford, Berkeley) are also in the top 10, as well as Cambridge and Oxford from the UK.
In an exciting new partnership, Airbnb has teamed up with Kaggle to create an online Data Science data challenge. In this challenge we provide historical data on the first country guests book and then ask candidates to predict future first bookings.
Try the challenge yourself! You have until February 11th 2016 to submit your entries. And if you have any questions you can use the forum and I will respond as soon as possible. Good luck and hope you have fun playing with our data!
Along with a team of Stanford University Sociologists led by Karen Cook and Paolo Parigi, I am conducting a study on behalf of Airbnb to understand the social consequences of sharing goods and services with strangers.
Karen has published multiple books on the formation of Trust in modern societies and more recently on the role of Trust in the online world. Paolo is also interested in social networks and has conducted previous studies of Trust in the sharing economy.
Together we will be surveying Airbnb members to better understand Trust inside and outside of the sharing economy, as well as what drives changes in Trust. Stay tuned for more!