2019년

The following case package provides an overview of the content to be presented at the Rotman-UNIST Trading Competition 2019. Each case has been specifically tailored to topics in university level classes and real-life trading simulations. We hope you enjoy your experience at the competition.

The Case Package can be downloaded here : pdf
RIT Installation Guide and User Guide documents : zip
Base Algorithm for Algorithmic Statistical Arbitrage Case : xlsm
Base Algorithm for Algorithmic  ETF Trading Case : xlsm
Scoring methodology : pdf

Case Information

SOCIAL OUTCRY CASE :

This is the opening event of the competition, giving participants the opportunity to make their first impression on sponsors, faculty members, and other teams in this fun start to the Rotman- UNIST Trading Competition. Each participant has the opportunity to trade against professors and experienced professionals from the industry, trying to make his/her case against them and showcasing his/her outcry skills by making fast and loud trading decisions.

 

ALGORITHMIC STATISTICAL ARBITRAGE CASE:

The Algorithmic Statistical Arbitrage Case is designed to challenge participants’ programming skills in developing algorithms using MATLAB, Excel VBA or Python to automate trading strategies and react to changing market conditions. Throughout the case, these algorithms will submit orders to capitalize on any statistical arbitrage opportunities that may arise. Because of the high-frequency nature of the case, participants are encouraged to develop algorithms that can adapt to rapid changes in market dynamics.

 

ALGORITHMIC ETF TRADING CASE

The Algorithmic ETF Trading Case is also designed to challenge participants’ programming skills in developing algorithms using MATLAB and/or Excel VBA or Python to automate trading strategies and react to changing market conditions. Throughout the case, these algorithms will submit orders to profit from private tender offers and arbitrage opportunities. Because of the high-frequency nature of the case, participants are encouraged to develop algorithms that can adapt to rapid changes in market dynamics.

 

NATURAL GAS TRADING CASE:

The Natural Gas Trading Case challenges the ability of the participants to respond to the highly dynamic world of commodities trading. In this case, participants will analyze different types of news releases affecting the supply and demand of natural gas. In response, participants buy and sell futures contracts for different natural gas delivery months. Participants will earn profits by correctly forecasting future supply and usage of natural gas, and consequently its fair value.

 

CRUDE OIL TRADING CASE:

The Crude Oil Trading Case challenges the ability of participants to trade in a closed supply and demand market for crude oil. Natural crude oil production and its consumption will form the framework for participants to engage in direct trade to meet each other’s objectives. The case will test each participant’s ability to understand sophisticated market dynamics and optimally perform his/her role, while stressing teamwork and communication. The case will involve crude oil production, refinement, storage, as well as the sale of its synthesized physical products.