Individual Assignment 2: Security Allocation Course: MSc MGT 6120 | Objective Building on Assignment 1's sector targets, select individual securities and weights within our 18-stock universe. You will build a classic mean-variance optimized
Individual Assignment 2: Security Allocation
Course: MSc MGT 6120 |
Objective
Building on Assignment 1's sector targets, select individual securities and weights within our 18-stock universe. You will build a classic mean-variance optimized (MVO) portfolio, then build a second portfolio using the Black-Litterman (BL) model, with your views grounded in a fundamental valuation (e.g., DCF and/or relative valuation). You will compare the two and present a recommended portfolio to the Investment Committee (IC). You are allowed to use AI, and it is recommended for the coding. You will need to submit a copy of all AI conversations relevant to this assignment.
Tasks
1. Data collection. Download 3–5 years of monthly total returns for all 18 securities in the universe below, plus the 70% TSX / 30% S&P 500 blended benchmark used in Assignment 1.
2. Classic MVO. Estimate μ (historical average) and Σ, then solve the constrained optimization: long-only, fully invested, 7.5% per-security cap.
3. Valuation-based views. For a minimum of 3 and up to 5 securities of your choice (motivate the choice), estimate a 12-month target price using a valuation model (e.g. DDM, DCF, relative valuation). Convert each target price into an expected-return view, stating the horizon and your confidence level explicitly.
4. Reverse-optimized prior. Compute equilibrium (implied) returns Π from market-cap weights and Σ, to serve as the Black-Litterman prior for every security — including those without a view.
5. Black-Litterman optimization. Blend the prior with your views (specify P, Q, Ω, and τ), then re-solve the same constrained optimization using the BL-blended expected returns.
6. Compare and interpret. Contrast the Classic MVO and Black-Litterman weights. Identify which securities moved most and why, and relate this to MVO's known sensitivity to noisy expected-return inputs.
7. Investment Committee report. Present your recommended security weights with a clear justification for each material position. Report the resulting sector exposure alongside Assignment 1's benchmark weights (no hard sector constraint here — this is for discussion only).
Security Universe
|
Security |
Ticker |
Sector |
|
|
AGNICO-EAGLE MINES LTD COM |
AEM |
Materials |
|
|
APOLLO GLB MGMT
RG |
APO |
Financials |
|
|
BIOMARIN PHARMACEUTICAL
INC COMMON |
BMRN |
Health Care |
|
|
BLACKROCK RG |
BLK |
Financials |
|
|
FAIRFAX FINANCIAL
HOLDINGS LTD SUB VTG |
FFH |
Financials |
|
|
HONEYWELL |
HON |
Industrials |
|
|
JPMORGAN CHASE
& CO |
JPM |
Financials |
|
|
MDA SPACE RG |
MDA |
Industrials |
|
|
MICROSOFT CORP |
MSFT |
Information Technology |
|
|
NEXTERA ENERGY
INC COMMON |
NEE |
Utilities |
|
|
ROYAL BANK OF
CANADA |
RY |
Financials |
|
|
S&P GLOBAL
INC COMMON |
SPGI |
Financials |
|
|
STELLA-JONES INC |
SJ |
Materials |
|
|
TAKE-TWO
INTERACTIVE SOFTWARE INC COMMON |
TTWO |
Communication
Services |
|
|
TOPICUS COM INC |
TOI |
Information
Technology |
|
|
UBER TECHNOLOGIES
INC |
UBER |
Industrials |
|
|
WASTE MANAGEMENT
INC |
WM |
Industrials |
|
|
WSP GLOBAL INC
COMMON |
WSP |
Industrials |
|
|
Deliverables • A short written report summarizing your
methodology, results, and IC recommendation. • Required exhibits: μ/Σ, implied returns Π,
your view summary table (target prices, sources, horizon, confidence), BL
posterior returns, the Classic MVO vs. BL weight comparison, and the
resulting sector-exposure comparison. •
The
supporting spreadsheet or code file, and your AI conversation log. |
Submission • Submit the report and supporting file(s)
via Brightspace by the due date above. • Individual submission. •
Late
submissions are subject to the course's standard late-penalty policy. |
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