The following case package provides an overview of the content to be presented at the Rotman-UNIST Trading Competition 2021. 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.
Case Information
ALGORITHMIC STATISTICAL ARBITRAGE CASE:
The Algorithmic Statistical Arbitrage Case is designed to challenge participants’ programming skills by developing algorithms using the RIT API 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 by developing algorithms using the RIT API 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. Due to the high-frequency nature of the case, participants are encouraged to develop algorithms that can adapt to rapid changes in market dynamics using their selected programming languages.
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.
ELECTRICITY TRADING CASE:
The Electricity Trading Case provides the opportunity for participants to work in a role-based team environment to engage in an electricity trading market controlled by a strict regulatory policy. Participants are required to forecast supply and demand for electricity, and execute strategies accordingly while reacting to prevailing market events. Each team will participate in a closed supply and demand market for electricity by producing it using power plant assets and distributing it to customers, and will also have access to a forward market. Through the full cycle of electricity markets, participants will need to dynamically formulate their role-based strategies and optimally perform trade executions.
The RIT Market Simulator and associated Decision Cases are custom applications under the Simulation-Based Learning Portfolio managed by Rotman FRT-Lab. To know more, please visit our website at https://rit.rotman.utoronto.ca/cases.asp
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