BUSI70567代做、代写c/c++，Python程序

日期：2025-05-09 11:03

BUSI70567 Applied Quantitative Macro Strategies

Applied Quantitative Macro Strategies: Course Research

Project

Create, research and critique a systematic macro strategy

• Propose a sound ex-ante hypothesis. Source idea can be from literature or inspiration Acquire appropriate datasets required for your strategy (input data, asset returns etc.)-

Clean, analyse and interpret the input dataset - Run analysis to show forecasting power

of the dataset/idea

• Transform the raw data into a tradable signal by applying appropriate filters, scaling,

portfolio construction and risk management steps

• Analyse, interpret and critique the return behaviour of the strategy

• Suggest further improvements that can be made to the strategy

Important note

The project will NOT be judged on the forecasting power/information ratio of the strategy. It will

be marked on the quality of the research and the intuition shown

Create, research and critique a systematic macro strategy

• Project to be carried out in teams of 5 or 6 (see Insendi for groups)

• Project accounts for 50% of your total grade for this module

• Project deliverables

Oral Presentation (3rd June 2025, deadline for submission 2nd June 2025 @ 14:00)

• Strategy thesis, research approach, results and suggestions (10%)

• 15-minute (maximum!) PowerPoint presentation

• 15-minute questions/discussion

Written research report (deadline for submission 10th June 2025 @ 14:00)

• Detailed analysis, methodology, and results (40%)

• No more than 20 sides of A4 including figures. Include pertinent information only.- Note:

Team members within teams will be graded equally. Please make sure you all contribute

to the presentation and the research report.

Note: Team members within teams will be graded equally. Please make sure you all

contribute to the presentation and the research report.

Example template for research report

Investment hypothesis

• Set out your ex-ante hypothesis clearly

BUSI70567 Applied Quantitative Macro Strategies

• Make references to any evidence supporting your hypothesis

Data sourcing and analysis

• Explain in detail where your data was sourced and why it is suitable for the model•

Analysis to include any lags/revisions/missing periods etc. - Signal construction and

analysis

• Explain the transformation functions used in the signal construction

• Carry out parameter sensitivity, lead/lag and jackknife analysis

• Discuss in-sample versus out-of-sample behaviour of signal - Conclusions and

summary

• Critically review the strategy - suggest improvements or extensions