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MAN00134M: Quantitative Methods for Finance

MAN00134M: Quantitative Methods for Finance

Module Leader: Lewis Ramsden
Assessment Type: Open
Word Count: 1,500 words (±5%)
Weighting: 50%
Deadline: 11am, Monday 11th August 2025


Key Information

Submission Guidelines

  • Formatting:
    • Font: Arial, size 12
    • Line spacing: Double
    • Margins: Minimum 2cm
  • Word Count Includes:
    • Main text, in-text citations, quotations
  • Excluded from Word Count:
    • Appendices, title page, tables/figures, reference lists

Late Submission Policy

Delay Period Penalty
≤1 hour -5 marks
1–24 hours -10 marks
Each subsequent 24h -10 marks (max 5 days)
>5 days Non-submission (0 marks)

Exceptional Circumstances

  • Claims must be submitted before the deadline with evidence.
  • Post-submission claims accepted within 7 days of the deadline.

Academic Integrity

  • AI use must comply with University guidelines.
  • Misconduct will be penalized.

Assessment Structure

Part 1: Analysis of Returns (50 marks)

Task: Analyze daily log-returns for:

  1. GLOBAL UK
  2. YORKTECH LTD
  3. GREENFOODS INC
  4. Equally Weighted Portfolio

Questions:

  1. Calculate daily Sharpe ratios (risk-free rate: 4% p.a.). [6 marks]
  2. Compare assets and recommend the best investment. [8 marks]
  3. Estimate mean (µ) and variance (σ²) for GLOBAL UK returns. [4 marks]
  4. Estimate P(0% ≤ return ≤ 0.02%) for GLOBAL UK. [6 marks]
  5. Assess normality assumption for GLOBAL UK returns. [3 marks]
  6. Hypothesis test: YORKTECH LTD mean return = 0.00025 (α=5%). [6 marks]
  7. Calculate test power if true mean = 0.00027. [7 marks]

Part 2: Regression Modelling (50 marks)

Task: Evaluate linear relationship:

  • Sales (dependent) vs. Advertising Spend (independent).

Questions:

  1. Compute correlation coefficient. [5 marks]
  2. Explain OLS estimation method. [5 marks]
  3. Interpret β₁ (intercept) and β₂ (slope). [6 marks]
  4. Assess model fit quality. [5 marks]
  5. Distinguish between estimator vs. estimate. [4 marks]
  6. State distribution of OLS estimator for β₂. [4 marks]
  7. Derive 99% CI for β₂. [6 marks]
  8. Test significance of advertising spend. [6 marks]
  9. Explain purpose of error terms (ε). [5 marks]
  10. Predict sales for £110k advertising spend. [4 marks]
  11. Propose logarithmic model with “Advertising Type” (Social Media/TV/Radio). [10 marks]

Additional Requirements

  • Report Style: Formal, client-facing with clear recommendations.
  • Mathematical Content: Formulae excluded from word count.
  • Appendices: For supplementary data (not marked beyond word limit).

Total Marks: 100

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