Trexquant

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Start date: January 3, 2018
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Learn to beat the market.

Every year, the Trexquant Alpha team hosts an alpha competition to teach the next generation of quantitative researchers how to find alphas -- profitable and reproducible trading signals that power quantitative hedge funds. We’ll provide the data, cloud computers, backtesting platform and the lessons. Are you up for the challenge?

Background

To participate in the competition, all that is required is an interest in financial markets and enough programming experience to allow you to translate your ideas into Python code. The objective of the competition is to create a variety of uncorrelated signals, which we call Alphas, that are profitable across varying market conditions.

Competition participants will use our intuitive web-based platform, Trexsim, to develop and backtest Alphas, which are statistical arbitrage signals for trading global equities.

Trexsim has a variety of pre-cleaned data and built-in functions available, along with a framework to develop custom functions for data manipulation, which allows participants to rapidly iterate and backtest a variety of ideas. Competition participants thus avoid time-consuming data cleaning and simulation development effort, and instead directly focus on working with a variety of data to create useful trading signals.

The competition lasts for eight weeks. At the conclusion of the event, we will score the Alphas created by each entrant, rank each candidate, and award prizes to the top performers.

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Prizes

1st place $7,000
2nd place $5,000
3rd place $4,000
4th place $3,000
5th place $2,000
6-10th place $1,000

In addition to the prizes above, we will hold a raffle for 3 iPad Pros for all non-winner participants. See the Rules page for more details.

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Timeline

January 3, 2018 - Competition begins
January 14, 2018 - Registration deadline
February 28, 2018 - Competition ends

TREXQUANT

Trexquant is a statistical arbitrage hedge fund headquartered in Connecticut, United States. We use thousands of signals, called Alphas, to trade a broad universe of stocks with the goal of delivering strong absolute and risk-adjusted performance.

We continuously seek to improve in the areas of data collection, signal development, portfolio management, and trade execution. Our research atmosphere across these four areas emphasizes quantitative rigor, creativity, collaboration, and diligence.

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