ABOUT HUSKY HOLD`EM

Welcome to Husky Hold`em, where teams code their way to poker glory. In this computerized tournament, autonomous pokerbots face off in a strategic clash of algorithms and chance. A fusion of economics, computer science, and math, pushing participants to showcase interdisciplinary talents. The tournament unfolds in two intense rounds—first, a 1v1 bot battle, and then a final round where winning teams send a representative for a roundtable poker showdown. Join us at the forefront of competitive gaming, where skill meets silicon in a thrilling poker revolution.

DATE May 4, 2024

LOCATION Oak Hall Denny Room
University of Washington

Problem Statement Build the best no-limit Texas Hold`em computer algorithm

ABOUT

ABOUT UW ALGORITHMIC TRADING

Established in 2019, the Algorithmic Trading Club, previously known as the Financial Engineering Club, ardently steers students through the dynamic realm of quantitative finance and financial engineering. Our unwavering dedication is centered on equipping members with practical proficiency, encompassing fundamental Python programming to sophisticated data science methodologies. Immersive workshops explore the intricacies of backtesting and deploying trading algorithms, constructing a resilient foundation for forthcoming professional pursuits. Beyond the confines of workshops, our vibrant community actively engages in compelling projects and benefits from insights shared by esteemed guest speakers. Thriving on intellectual challenges, we host competitions designed to showcase individual talents. Furthermore, through the orchestration of substantial industry events, members acquire exposure to avant-garde trends in the field.

WHY POKERBOTS

In the realm of incomplete information and uncertainty, poker emerges as a quintessential application of game theory principles and decision-making skills crucial to the art of trading. Traders, navigating the financial markets with imperfect information, draw parallels to poker players who contend with concealed elements, strategically weighing factors like expected value and probability distributions in their decision-making processes.