RETC 2020

Rotman European Trading Competition 2020

From Thursday August 27th to Saturday August 29th, 2020

RETC 2020 – Tentative Schedule
August 27th – 29th, 2020
Thursday, August 27th, 2020
5:00 PM Registration Starts
5:00 – 6:00 PM Puzzle Contest
6:00 – 6:30 PM Welcome
6:30 – 7:00 PM Break
7:00 – 7:15 PM Social Outcry Tutorial
7:15 – 8:00 PM Social Outcry Case
8:00 – 8:15 PM Presentation
8:15 – 9:30 PM Dinner
9:30 PM Social Outcry Results | Group Social
Friday, August 28th, 2020
8:00 – 10:00 AM Breakfast
9:00 AM – 10:00 AM Algorithmic Trading Case (preliminary rounds)
10:00 – 12:30 AM Quantitative Outcry Trading Case
12:30 – 2:00 PM Lunch
2:00 – 2:30 PM Presentation
2:30 – 5:00 PM ENEL Electricity Case
5:00 – 5:30 PM Presentation
5:30 – 8:00 PM Intesa Sanpaolo Liquidity Risk Case
8:00 – 9:30 PM Dinner
9:30 PM Group Social
Saturday, August 29th, 2020
8:00 – 10:00 AM Breakfast
9:00 AM – 10:00 AM Algorithmic Trading Case (preliminary rounds)
10:00 – 12:30 AM Credit Risk Case
12:30 – 2:00 PM Lunch
2:00 – 4:30 PM EIB Interest Rate Case
4:30 AM – 5:30 PM Algorithmic Trading Case (final rounds)
5:30 – 8:00 PM Break
8:00 – 11:00 PM Gala Dinner
11:00 – 11:30 PM Awards Ceremony
11:30 PM Concluding Social
RETC 2020 – Cases
The opening event of the competition gives participants their first opportunity to make an impression on sponsors, faculty members, and other teams in this fun introduction to the Rotman European Trading Competition. Each participant trades against one another as well as faculty and experienced professionals from industry, trying to make his/her case and showcasing his/her outcry skills by making fast and loud trading decisions.
Building on the experience of the frantic Social Outcry Case market, this case requires teams to optimize their trading, analytical, and risk management skills. Participants will use news releases that provide quantitative economic forecasts, as well as qualitative micro and macro data, to predict the futures market on the RT100 index. Analyzing macroeconomic indicators, participants should be able to gain an understanding of the impact of the factors on the index and generate profitable trades.
The Enel Electricity Case challenges the ability of participants to interact with one another in a closed supply and demand market for electricity. Electricity production and its consumption will form the framework for participants to engage in direct trade to meet one another’s objectives. The case will test each individual’s ability to understand sophisticated market dynamics and optimally perform his/her role, while stressing teamwork and communication.
The Intesa Sanpaolo Liquidity Risk Case challenges participants to put their critical thinking and analytical abilities to the test in an environment that requires them to evaluate the liquidity risk associated with different tender offers. Participants will be faced with multiple tender offers requiring participants to make rapid judgments on the profitability and subsequent execution of these offers. Profits can be generated by taking advantage of price premiums and discounts associated with large tender offers compared to the market.
The Credit Risk Case challenges participants to build and apply a credit risk model in a simulation where corporate bonds are traded. Participants will use both a Structural Model and the Altman ZScore to predict potential changes to companies’ credit ratings. Periodic news updates will compel participants to make appropriate adjustments to the assumptions in their models and rebalance their portfolios accordingly. This case tests participants’ abilities to develop a credit risk model, assess the impact of news releases on credit risk, and execute trading strategies accordingly to profit from mispricing opportunities.
The EIB Interest Rate Case challenges traders’ understanding of bond pricing based on news and benchmark interest rates derived from 4 non-tradable EIB zero-coupon bonds. Traders have to price 3 tradable coupon bonds based on the benchmark rates and news. The news, released throughout the case, may have an impact on the benchmark rates, and thus also have an impact on the fair prices of the tradable coupon bonds. Traders should forecast the impact of news on the benchmark rates and exploit any bond mispricing opportunities to generate profits.
The Algorithmic Trading Case is designed to challenge participants’ programming skills by developing algorithms using RIT API to automate trading strategies and react to changing market conditions. Throughout the case, these algorithms will submit orders to profit from arbitrage opportunities and private tender offers. Due to the high-frequency nature of the case, participants are encouraged to develop algorithms that can adapt to rapid changes in market dynamics.