Case Package January 14th, 2022 - Rotman Finance Lab

Case Package
January 14th, 2022

Copyright © 2021 Rotman Finance Research and Trading Lab (Rotman FRT-Lab). All rights reserved.

This document or any portion thereof may not be used, reproduced, or distributed in any manner
whatsoever without the express written permission of the Rotman FRT-Lab. The RIT Market Simulator
and associated Decision Cases, and the Rotman Portfolio Manager (RPM) are custom applications
under the Simulation-Based Learning Portfolio managed by Rotman FRT-Lab. To know more, please
visit our website at financelab.utoronto.ca/cases.asp

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Table of
Contents

IMPORTANT INFORMATION .................................................................................................................................. 4
 PRACTICE SERVERS .................................................................................................................................................. 4
 SCORING METHODOLOGY ......................................................................................................................................... 4
 SCHEDULE AND TIMELINE .......................................................................................................................................... 4
CASE SUMMARIES.................................................................................................................................................. 5

 SALES AND TRADER CASE .......................................................................................................................................... 5
 ALGORITHMIC TRADING CASE .................................................................................................................................... 5

SALES & TRADER CASE ........................................................................................................................................... 6
 OVERVIEW ............................................................................................................................................................ 7
 DESCRIPTION ......................................................................................................................................................... 7
 MARKET DYNAMICS ................................................................................................................................................ 7
 CALCULATION OF THE PROFIT OR LOSS ......................................................................................................................... 8
 TRADING LIMITS AND TRANSACTION COSTS ................................................................................................................. 10
 POSITION CLOSE-OUT ............................................................................................................................................ 10
 KEY OBJECTIVE ..................................................................................................................................................... 10
ALGORITHMIC TRADING CASE ............................................................................................................................. 11
 OVERVIEW ....................................................................................................................................................... 12
 DESCRIPTION ................................................................................................................................................... 12
 MARKET DYNAMICS ......................................................................................................................................... 12
 TRADING LIMITS AND TRANSACTION COSTS...................................................................................................... 13
 POSITION CLOSE-OUT ....................................................................................................................................... 14
 KEY OBJECTIVE ................................................................................................................................................. 14
SCORING METHODOLOGY.................................................................................................................................... 15

 OVERVIEW ....................................................................................................................................................... 16
 SCORING MECHANISM ..................................................................................................................................... 16
 FINAL SCORE .................................................................................................................................................... 17

 © Rotman School of Management | BMO Financial Group Finance Research and Trading Lab | 3

Important Information
Practice Servers
Practice servers will be made available starting on December 10th, 2021 and will operate 24 hours a
day, 7 days a week until the start of the competition.

Information on how to download and install the RIT v2.0 Client is available on the RIT website.

We have posted information on how to log in to the practice servers on the ROTC website. Remember
that on RIT you can type in any username and password and it will automatically create an account if
it does not exist. If you have forgotten your password or the username appears to be taken, simply
choose a new username and password to create a new account.

Scoring Methodology
The Scoring Methodology document is included at the end of this Case Package.

Schedule and Timeline
The competition is held online and will start at 4:00 pm EST on Friday, January 14th, 2021 and end
at approximately 6:00 pm EST. It will be run until the number of heats described further in this
document is completed. The ROTC Committee will not wait for anyone who is late. Competition
Servers will be set up 10 minutes before the start. In the event of a server failure, the case session will
be rerun and the scores from that session will not be kept.

 © Rotman School of Management | BMO Financial Group Finance Research and Trading Lab | 4

Case Summaries
Sales and Trader Case
The Sales and Trader 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 throughout the case. This will require
participants to make rapid judgments on the profitability and subsequent execution, or rejection, of
each offer. Profits can be generated by taking advantage of price differentials between market prices
and prices offered in the tender offers. Once any tender has been accepted, participants should aim
to efficiently close out the large positions to maximize returns.

Algorithmic Trading Case
The Algorithmic Trading Case is designed to challenge participants’ programming skills as they are
required to develop algorithms using RIT API to automate the market-making process and react to
changing market conditions. Throughout the case, these algorithms will submit orders to profit from
market-making and from any arbitrage opportunities that may arise. Due to the high-frequency nature
of the case, participants will have to develop algorithms to adapt to changes in market dynamics.

 © Rotman School of Management | BMO Financial Group Finance Research and Trading Lab | 5

Sales & Trader Case
Rotman Online Trading Competition 2022

The ‘Sales & Trader Case’, Copyright © Rotman Finance Research and Trading Lab, all rights reserved.
This case has been adapted from the ‘Liability Trading 3 – Dynamic Order Arrival’ Decision Case,
developed for the RIT Market Simulator platform (for details: rit.rotman.utoronto.ca/cases.asp)

 © Rotman School of Management | BMO Financial Group Finance Research and Trading Lab | 6

Overview
The Sales and Trader 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 throughout the case. This will require
participants to make rapid judgments on the profitability and subsequent execution, or rejection, of
each offer. Profits can be generated by taking advantage of price differentials between market prices
and prices offered in the tender offers. Once any tender has been accepted, participants should aim
to efficiently close out the large positions to maximize returns.

Description
The trading session will consist of five, 10-minute heats with each heat independently traded and
representing one month of calendar time. Each heat will have a unique objective and could involve up
to four securities with different volatility and liquidity characteristics.

 Parameter Value

 Number of trading heats 5
 Trading time per heat 600 seconds (10 minutes)
 Calendar time per heat 1 month (20 trading days)

Tender offers will be generated by computerized traders and distributed at random intervals to random
participants. Participants must subsequently evaluate the profitability of these tenders when accepting
or bidding on them. Order submission using the RIT API will be disabled. Only data retrieval via Real-
Time Data (RTD) links or the RIT API will be enabled.

Market Dynamics
There are five heats, each with unique market dynamics and parameters. Potential parameter changes
include factors such as spread of tender orders, liquidity, and volatility. Market dynamics and
parameter details regarding each heat can be found below, allowing participants to formulate trading
strategies.

 Heat 1
 Stock Price Commissions Tender Spread Volatility Liquidity
 MPL $15 $0.02 Medium Medium Medium
 TREE $30 $0.02 Medium Low High

 Heat 2
 Stock Price Commissions Tender Spread Volatility Liquidity
 YYZ $15 $0.02 Medium Medium Medium
 YVR $30 $0.05 Large High Medium

 Heat 3
 Stock Price Commissions Tender Spread Volatility Liquidity
 DWHT $25 $0.05 Large Medium Medium
 MCHL $30 $0.02 Low Medium Low
 CRED $40 $0.01 Large High High

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Sales & Trader Case
 Heat 4
 Stock Price Commissions Tender Spread Volatility Liquidity
 RCK $55 $0.03 Medium Medium Medium
 JZZ $45 $0.02 Medium High High
 HPHP $35 $0.02 Medium High Medium

 Heat 5
 Stock Price Commissions Tender Spread Volatility Liquidity
 LKRS $25 $0.05 Medium Medium Medium
 RPTS $30 $0.05 Large Medium High
 BCKS $20 $0.01 Large Low Medium
 CLPS $30 $0.02 Medium High Medium

During each sub-heat, participants will occasionally receive one of three different types of tender offers:
private tenders, competitive auctions, and winner-take-all tenders. Tender offers are generated by the
server and randomly distributed to random participants at different times. Each participant will get
the same number of tender offers with variations in price and quantity. No trading commission
will be paid on tenders.

Private Tenders are routed to individual participants and are offers to purchase or sell a fixed volume
of stock at a fixed price. The tender price is influenced by the current market price.

Competitive Auction offers will be sent to every participant at the same time. Participants will be
required to determine a competitive, yet profitable price to submit for a given volume of stock from the
auction. Any participant that submits an order that is better than the base-line reserve price (hidden
from participants) will automatically have their order filled, regardless of other participants’ bids. If
accepted, the fills will occur at the price that the participant submits.

Winner-take-all Tenders request participants to submit bids to buy or sell a fixed volume of stock. After
all prices have been received, the tender is awarded to the single highest bidder or lowest offer. The
winning price however must meet a base-line reserve price. If no offer meets the reserve price, then
the trade will not be awarded to anyone (i.e. if all participants bid $2.00 for a $10 stock, nobody will
win).

Calculation of the Profit or Loss
The prices generated by the RIT for this case follow a random walk process using a return drawn from
a normal distribution with a mean of zero. That is, at any point in the simulation, the probability that the
price will go up is equal to the probability that the price will go down. This means that participants
cannot predict the future price of the stocks without ‘taking a bet’. Therefore, the scoring committee
will consider buying (selling) stocks for reasons other than reducing the exposure associated with
accepting a tender offer to be equivalent to speculating (taking a bet) on the price movement. These
types of trades will be marked as ‘speculative trades’.

Participants will have time to think about the offer before they accept it. For example, one may receive
a tender offer at time = 0 and will have until = 30 to decide whether to accept. Any trades made

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by a participant during this time without accepting the tender offer will be considered as ‘front-running’1
since the participant had the advance knowledge of a pending institutional order. The scoring
committee will mark these trades as ‘front-running trades’.

This case is designed to only reward participants for identifying, accepting, and closing out2 tender
offer positions at a profit while managing liquidity risk and execution risk. Any other strategy will not be
considered. In particular, the total profit of each participant3 will be categorized into two parts: ‘profits
from tender offers’ and ‘profit from speculation’; the latter category includes the profits that are a result
of either speculative trades or front-running trades.

Profits from tenders are the profits (or losses) gained from efficiently closing out the position from
accepted tenders into the market. Profits from speculation are profits (or losses) generated through
trades that are not associated with tenders (speculative trades or front-running trades). An ‘adjusted
P&L’ will be calculated based on the following formula:

 & = + (0, )

Participants will be ranked and scored based on their & .

For example, consider a participant who has made $10,000 from tenders and $50,000 from
speculation, the total profit is $60,000 (= $10,000 + $50,000) but the & will be only
$10,000 [= $10,000 + (0, $50,000)] . Another example, consider a participant who has made
$35,000 from tenders and lost $20,000 from speculation ( = −$20,000); the
total profit is $15,000 ($35,000 − $20,000) and it is the same as the & [$15,000 =
 $35,000 + (0, −$20,000)]. From the last example, please note that any losses from speculation
will still be considered and, therefore, negatively affect your & .

The & will be calculated by the ROTC scoring committee at the end of each heat and will
not be included in the P&L calculation in RIT. However, participants will be provided with an Excel
tool4, the ‘Performance Evaluation Tool’, that will allow them to calculate the & .

1
 Front-running is the unethical and illegal practice of trading a security for your own account while
taking advantage of the information contained in the pending orders from your institutional clients.

2
 “Closing out” a position means that a participant is executing a trade that is the opposite of the
current position in order to eliminate the exposure.

3
 Total profit of each participant is the profit (or loss) that you can observe in the RIT at the end of
a heat/iteration.

4
 The ‘Performance Evaluation Tool’ is posted on the ROTC website.

 © Rotman School of Management | BMO Financial Group Finance Research and Trading Lab | 9

Sales & Trader Case
Trading Limits and Transaction Costs
Each participant will be subject to gross and net trading limits: the net and gross trading limits for all of
the versions are NET 250,000 shares, or GROSS 250,000 shares. The gross trading limit reflects the
sum of the absolute values of the long and short positions across all securities, while the net trading
limit reflects the sum of long and short positions such that short positions negate any long positions.
Trading limits will be strictly enforced and participants will not be able to exceed them.

The maximum trade size will be 25,000 shares, restricting the volume of shares transacted per trade
to 25,000.

There is a maximum stop loss of $1.5 Million per person for each trading heat. If a participant loses
more than $1.5 Million, he/she will be forced to stop trading for the remainder of the heat.

Position Close-Out
Any non-zero position will be closed out at the end of trading based on the last traded price. This
includes any long or short position open in any security. Computerized market makers will increase
the liquidity in the market towards the end of trading to ensure the closing price cannot be manipulated.

Key Objective
Evaluate the profitability of tender offers by analyzing the market liquidity. Participants will accept the
tenders that will generate positive profits while rejecting the others. Submit competitive, yet profitable,
bids and offers on the above reserve and winner-take-all tenders to maximize potential profits while
managing liquidity and market risk. There is a chance that the market may move away from your
transactions prices, so maintaining large short or long positions may result in losses. Use a
combination of limit, market orders and, marketable limit orders to mitigate any liquidity and price risks
from holding open positions.

 © Rotman School of Management | BMO Financial Group Finance Research and Trading Lab | 10

Algorithmic Trading Case
Rotman Online Trading Competition 2022

The ‘Algorithmic Trading Case’, Copyright © Rotman Finance Research and Trading Lab, all rights
reserved. This case has been adapted from the ‘Algorithmic Trading 1 – Algorithmic Arbitrage’ Decision
Case, developed for the RIT Market Simulator platform (for details: rit.rotman.utoronto.ca/cases.asp)

 © Rotman School of Management | BMO Financial Group Finance Research and Trading Lab | 11

OVERVIEW
The Algorithmic Trading Case is designed to challenge participants’ programming skills since they
are required to develop algorithms using RIT API to automate the market-making process and react
to changing market conditions. Throughout the case, these algorithms will submit orders to profit
from market-making and also from any arbitrage opportunities that may arise. Due to the high-
frequency nature of the case, participants will have to develop algorithms to adapt to changes in
market dynamics.

DESCRIPTION
There will be five, 5-minute heats with each heat independently traded and representing one day of
trading.

 Parameter Value

 Number of trading heats 5
 Trading time per heat 300 seconds (5 minutes)
 Calendar time per heat 1 day of trading

All trades must be automatically executed by a trading algorithm. Participants will not be allowed to
trade through the RIT Client once the case begins. However, participants are allowed and
encouraged to use and modify their algorithms in response to prevailing market conditions and
competition from the algorithms of other teams. In addition, there will be 2 minutes in between each
sub-heat to alter the algorithms. A base template algorithm will be provided for participants and can
be directly modified for use in the competition. Alternatively, participants can create their own
algorithms using RIT API.

MARKET DYNAMICS
This case will involve 3 stocks and 1 ETF with varying levels of volatility and liquidity. This dynamic
exposes participants to the basics of market microstructure in the context of algorithmic trading.
Participants can manage the market price impact of trades and automate market making operations
by dividing larger volume orders into smaller trades and submitting pairs of trades electronically. The
ETF pricing will reflect the following weighted sum of the 3 stocks traded, subject to periodic shocks
to its price.

 CND = BEAV + 2 ∗ MAPL + 2 ∗ COLD

Each participant will be able to trade 4 securities of which the details are shown below.

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Algorithmic Trading Case
 Ticker BEAV MAPL COLD CND
 Starting Price $15 $15 $15 $75
 Fee/share (Market orders) $0.01 $0.01 $0.01 $0.02
 Rebate/share (Limit/Passive
 $0.005 $0.005 $0.005 $0.015
 orders)
 Max order size 10,000 10,000 10,000 5,000
 Annualized volatility 26% 17% 35% 16%
 Liquidity Medium High Low Medium
 Type Stock Stock Stock ETF

There will be no information provided that will allow participants to predict the future price or direction
of any security. A fee-rebate structure will be instituted to compensate participants for the addition of
liquidity through limit orders. As such, participants will have the opportunity to generate returns by
market making.

TRADING LIMITS AND TRANSACTION COSTS

 Time of Sub-heat (tick) 0 ~ 240 240 ~ 299 300
 Gross/Net 200,000/50,000 100,000/50,000 100,000/0

Each participant will be subject to gross and net trading limits which will change over each heat. The
gross trading limit reflects the sum of the absolute values of the long and short positions across all
securities and the net trading limit reflects the sum of long and short positions such that short
positions negate any long positions. Trading limits will be strictly enforced and participants will not
be able to exceed them. Each position in stock will be counted towards trading limits with a multiplier
of 1, while each position in the ETF will be counted with a multiplier of 5 (i.e. if you long 100 shares
of any stocks, your gross and the net trading limits will increase by 100. If you long 100 positions of
CND, your gross and net trading limits will increase by 500 (100 positions * multiplier of 5).

Participants will be penalized for having a non-zero net position at the end of any individual heat.
This penalty will be levied against the final P&L for that heat. The calculation for the penalty is as
follows:

 Penalty = | =300 | * $0.50

The maximum trade size will be 10,000 shares for stocks and 5,000 shares for the ETF, restricting
the volume of shares transacted per trade to 10,000 shares for stocks and 5,000 shares for the ETF.
Transaction fees will be set at $0.01 per share for stocks and $0.02 per share for the ETF on all
market orders filled. Subsequently, a rebate of $0.005 per share for stocks and $0.015 per share for
the ETF will be given for all submitted limit orders that are filled. Due to this rebate structure, it is
possible for a participant to be profitable after buying and selling a security at the same price,
provided that the participant uses limit orders.

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POSITION CLOSE-OUT
Any non-zero position in either stock will be closed out at the end of trading based on the last traded
price. It is strongly suggested that participants close out their positions prior to the end of trading
period as open positions will be subject to the penalty described above.

KEY OBJECTIVE
Edit the template provided and optimize the trading parameters such that the algorithm efficiently
balances positions while submitting orders to profit from capturing bid-ask spreads and/or from
capturing arbitrage opportunities. Consider rewriting and redesigning the algorithm using your own
logic. Since the same template is being provided to all participants, there is a limitation on your ability
to differentiate yourself by simply modifying the base template.

 © Rotman School of Management | BMO Financial Group Finance Research and Trading Lab | 14

Scoring Methodology
Rotman Online Trading Competition 2022

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OVERVIEW

The scoring and ranking methodology is designed to translate absolute performance into relative
performance by the use of a ranking system. This ranking system is designed to discourage traders from
betting “the house” in one heat and generating very large absolute profits that will result in a clear win of
the entire competition. Instead, traders’ absolute performance in each case is converted into a series of
ordinal ranks which are subsequently converted into a final case ranking. These case rankings are mapped
to case scores and then combined under the following weights:

 Sales & Trader Algorithmic
 Case Trading Case

 50% 50%

The scoring system is not intended to be extremely complex. However, throughout the trading competition
there will be over 500 separate trading results. These results must then be averaged and ranked over
several iterations to compute a final ranking and score. This document describes that process.

The purpose of the system is to reward consistently high performance (i.e. a team that places 8th and 5th
will have a higher final score than a team that places 1st and 35th).

SCORING MECHANISM

For each heat, the final liquidated portfolio values5 of all team members (that is, the profits/losses of
all team members) are combined to form a dollar value of the team portfolio. The teams are then ranked
for each heat by the dollar values of the team portfolio with 1st given to the team with the highest dollar
value. In the event of a tie, the teams that have tied will be given the same rank. The teams below the tie
will be given a rank based on the number of teams that have scored better than them. Therefore, if three
teams tied for 2nd place, the ranking would be 1st, 2nd, 2nd, 2nd, and 5th.

Based on the above, each team will receive a rank for every heat. A team’s heat ranks are then averaged.
Teams are then ranked based on their average heat rank to determine their overall heat rank. The team
with the lowest average will be ranked first.

This case ranking is then mapped to a point score where the lowest rank (best score) is given a score of
n+1, where n is the number of teams below you plus the teams that tied with you (i.e. the first place team
out of 28 teams will get a score of 28, the last place team will get a score of 1). If you are tied for 2nd place
with 2 other teams, you will get a score of 27.

5
 P&L from each team member will be used for the Algorithmic Trading Case. For the Sales and
Trader Case, “Adjusted P&L” will be used as explained in the Case Package.

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FINAL SCORE

The final case scores are then multiplied by their case-weights to form a final weighted score. This final
weighted score is used to rank teams, where the highest score is the best score. In the case of two or more
teams having the same final weighted score, those teams will be ranked based on the variance of their final
case scores. The team with the lowest variance will be ranked ahead of the others. For example, if the top
3 teams have the following scores:

 Final Case Scores

 Team Final Weighted Score
 Sales & Trader Algorithmic Trading

 Team 28 27 27.5
 1
 Team 26 24 25
 2
 Team 27 23 25
 3

Team 1 will be ranked first as it has the highest weighted score. Team 2 and Team 3 have the same final
weighted score and will be ranked based on the variance of their case scores. The variance for Team 2 is
1 while the variance for Team 3 is 4, therefore Team 2 will be ranked second while Team 3 will be ranked
third.

 Team Final
 Rank
 Team 1 1
 Team 2 2
 Team 3 3

Two (or more) teams that have the same score and the same variance will tie. In the event of a tie, the
teams that have tied will be given the same rank. The teams below the tie will be given a rank based on the
number of teams that have scored better than them. Therefore, if three teams tied for 2nd place, the ranking
would be 1st, 2nd, 2nd, 2nd, and 5th.

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