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INV4801 Assignment 2 (COMPLETE ANSWERS) 2025 – DUE 29 August 2025; 100% correct solutions and explanations.

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INV4801 Assignment 2 (COMPLETE ANSWERS) 2025 – DUE 29 August 2025; 100% correct solutions and explanations.a) Volatility Dynamics in South African Equity Markets A portfolio manager at a Johannesburg-based investment firm is tasked with managing a fund heavily exposed to the South African Top 40 Index. Following a period of heightened market uncertainty due to geopolitical tensions and fluctuating commodity prices, the firm decides to model daily equity return volatility more accurately using a Time-Varying Volatility-ARCH Models. The portfolio manager gathered the following daily information: α = 0.07, γ = 0.000015, and β = 0.91. Given these parameters, the daily standard deviation is 1%. Suppose the previous period estimated variance was 0.0012 and the current period return is 4.5% above the expected value. (i) Compute the conditional variance for today. (5) (ii) Compute the conditional standard deviation for today. (2) (iii) What will happen to the variance if the current return is in line with expectation? (2) b) Multi manager strategy - University of Muchapatema Tawana, was recently hired by the University of Muchapatema which has a USD 50 million global diversified portfolio. In a meeting with the University’s CIO, the CIO asks Abigail which multimanager strategy, Fund-of-Fund and Multi-strategy Fund, provides better liquidity and more normally distributed returns. To address the CIO's concern regarding the return distribution, Tawana evaluates two optimization approaches to overall portfolio construction: • mean-variance optimization using a

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, INV4801 Assignment 2 (COMPLETE ANSWERS)
2025 – DUE 29 August 2025; 100% correct solutions
and explanations.

a) Volatility Dynamics in South African Equity Markets

𝑮𝒊𝒗𝒆𝒏

 𝛼 = 0.07, 𝛽 = 0.91, 𝜔 = 𝛾 = 0.000015\𝑎𝑙𝑝ℎ𝑎 = 0.07,\; \𝑏𝑒𝑡𝑎 =
0.91,\; \𝑜𝑚𝑒𝑔𝑎 = \𝑔𝑎𝑚𝑚𝑎 = 0.000015𝛼 = 0.07, 𝛽 = 0.91, 𝜔 = 𝛾 =
0.000015
 𝑃𝑟𝑒𝑣𝑖𝑜𝑢𝑠 𝑣𝑎𝑟𝑖𝑎𝑛𝑐𝑒: 𝜎𝑡 − 12 = 0.0012\𝑠𝑖𝑔𝑚𝑎_{𝑡 − 1}^2 = 0.0012𝜎𝑡 − 12 =
0.0012
 𝑅𝑒𝑡𝑢𝑟𝑛 𝑠ℎ𝑜𝑐𝑘: 𝜀𝑡 − 1 = 0.045\𝑣𝑎𝑟𝑒𝑝𝑠𝑖𝑙𝑜𝑛_{𝑡 − 1} = 0.045𝜀𝑡 − 1 =
0.045 (𝑖. 𝑒. , 4.5%4.5\%4.5%)
 𝑀𝑜𝑑𝑒𝑙: 𝜎𝑡2 = 𝜔 + 𝛼𝜀𝑡 − 12 + 𝛽𝜎𝑡 − 12\𝑠𝑖𝑔𝑚𝑎_𝑡^2 =\𝑜𝑚𝑒𝑔𝑎 +
\𝑎𝑙𝑝ℎ𝑎\𝑣𝑎𝑟𝑒𝑝𝑠𝑖𝑙𝑜𝑛_{𝑡 − 1}^2 +\𝑏𝑒𝑡𝑎\𝑠𝑖𝑔𝑚𝑎_{𝑡 − 1}^2𝜎𝑡2 = 𝜔 + 𝛼𝜀𝑡 − 12
+ 𝛽𝜎𝑡 − 12



(𝒊) 𝑪𝒐𝒏𝒅𝒊𝒕𝒊𝒐𝒏𝒂𝒍 𝒗𝒂𝒓𝒊𝒂𝒏𝒄𝒆 𝒕𝒐𝒅𝒂𝒚

1. 𝑆𝑞𝑢𝑎𝑟𝑒 𝑡ℎ𝑒 𝑠ℎ𝑜𝑐𝑘:
𝜀𝑡 − 12 = 0.0452 = 0.002025\𝑣𝑎𝑟𝑒𝑝𝑠𝑖𝑙𝑜𝑛_{𝑡 − 1}^2 = 0.045^2
= 0.002025𝜀𝑡 − 12 = 0.0452 = 0.002025
2. 𝑀𝑢𝑙𝑡𝑖𝑝𝑙𝑦 𝑏𝑦 𝛼\𝑎𝑙𝑝ℎ𝑎𝛼:
0.07 × 0.002025 = 0.000141750.07 \𝑡𝑖𝑚𝑒𝑠 0.002025
= 0.000141750.07 × 0.002025 = 0.00014175
3. 𝑀𝑢𝑙𝑡𝑖𝑝𝑙𝑦 𝑝𝑟𝑒𝑣𝑖𝑜𝑢𝑠 𝑣𝑎𝑟𝑖𝑎𝑛𝑐𝑒 𝑏𝑦 𝛽\𝑏𝑒𝑡𝑎𝛽:
0.91 × 0.0012 = 0.0010920.91 \𝑡𝑖𝑚𝑒𝑠 0.0012 = 0.0010920.91 × 0.0012
= 0.001092
4. 𝐴𝑑𝑑 𝑎𝑙𝑙 𝑝𝑎𝑟𝑡𝑠 𝑤𝑖𝑡ℎ 𝜔\𝑜𝑚𝑒𝑔𝑎𝜔:
0.000015 + 0.00014175 + 0.001092
= 0.001248750.000015 + 0.00014175 + 0.001092
= \𝑏𝑜𝑥𝑒𝑑{0.00124875}0.000015 + 0.00014175 + 0.001092
= 0.00124875

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