🌟 The 3rd Annual Hack4Her Event June 7-9, 2024 🌟

Challenge D from Optiver

Optiver Challenge: “Optibook” - Trading Companies with Strong DEI Practices on a Simulated Exchange

Challenge Summary

Did you know that studies have shown that “companies in the top quartile for gender diversity on executive teams were 25 percent more likely to have above-average profitability than companies in the fourth quartile”? Let’s translate this powerful insight into a profitable investment strategy that also champions companies with outstanding gender diversity. Enter Opti-DivInc-Fund, an Exchange Traded Fund (ETF) that bundles together a basket of companies with strong Diversity, Equity, and Inclusion (DEI) practices. In this hackathon challenge, you’ll learn how to trade the Opti-DivInc-Fund. By doing so, you’ll ensure this unique basket of companies remain accessible and attractive to a wide range of investors. Not only does this promote ethical investing, but it also has the potential to drive meaningful change in corporate culture. Let’s get started!

Objective

Build a trading algorithm in Python which trades in real-time against other participants on our simulated exchange called “Optibook”. The challenge is to develop a python algorithm that can profitably trade the Opti-DivInc-Fund . The team with the best performing algorithm wins our challenge! The challenge is a realistic but simplified version of our core business at Optiver. By participating you’ll discover how trading really works, and you’ll walk away with a greater understanding of stock markets, life at a trading company and the ability to build your own Python trading algorithm. Optiver mentors will be on hand over the weekend to answer your questions and help you along the way. Note: we don’t just look at PnL (profit & loss) alone to decide the winner, but it is a factor.

Tools and Technologies:

Only basic python knowledge is required to participate in this challenge. More importantly, you will have to think creatively to incrementally improve your trading algorithm as your observe it’s performance on our simulated exchange against the other participants.

Given (All Generated/Simulated):

You will get access to our simulated exchange with an online Visual Studio Code environment where you can write your own code in python. You won’t waste time on setting up your own environment as all necessary packages are pre-installed in your online Visual Studio Code environment on the Optibook platform. During the hackathon, you will be able to trade on this exchange using your python algorithm and experiment with different strategies as you observe how your algorithm performs against other participants.

Expected Deliverables

A trading algorithm in python that trades on our simulated exchange against other participating teams.

Judging Criteria

We will ask your team to present your trading strategy at the end of the Hackathon, explain how you tackled the problem, challenges you encountered, decisions and trade-offs you made when coming up with your solution. We will also ask you to a code-walkthrough of your strategy.

The following will be considered when judging the winning team:

• PnL (profit-and-loss) from the strategy during the challenge; there will be ample of time to experiment during the 2 days on the simulated exchange. On Sunday afternoon, we will re-set the exchange for a final round so that you can show what your algorithm can do on a clean slate!
• the design of the strategy, i.e. the method used, risk-management of the strategy
• code-quality of the strategy, i.e. is he code well structured, separates concerns, accounts for testing, etc.
• presentation quality, i.e. can they communicate their solution in an engaging way

Suggested Timeline

Saturday morning: we will explain you the challenge in detail, give you a quick introduction to some important concepts in trading and finance and guide you through setting up your first trading algorithm. Saturday afternoon & Sunday morning: you will keep improving your algorithm as you continuously trade against other participants and experiment. Sunday afternoon: We will re-set the exchange, so that you can see how your final trading strategy performs against others on a clean slate. We will ask you to walk us through your code. You will also spend some-time (we recommend ~1h) to prepare a presentation that explains how you tackled the problem, challenges you encountered, decisions and trade-offs you made when coming up with your solution.