代做FINN2061 Programming for Finance 2023/24代写数据结构语言

日期：2024-04-01 11:56

FINN2061

Programming for Finance

Undergraduate Programmes 2023/24

SUMMATIVE ASSIGNMENT

Objective:

To understand the debate surrounding the predictability of stock market returns, particularly in the context of Fama’s Efficient Market Hypothesis (EMH) versus the claims made by Lettau and Ludvigson (2001). By the end of this assignment, you should be able to critically assess the validity of both arguments and form. your own opinion on the predictability of stock market returns.

Part A: Short Literature Review

· The Efficient Market Hypothesis (EMH)

· Briefly explain the three forms of EMH: weak, semi-strong, and strong.

· Outline Fama’s (1970) main arguments supporting the view that stock market returns are unpredictable using publicly available information.

· Predictability Claims

· Summarize the main arguments made by Lettau and Ludvigson (2001) regarding the predictability of stock market returns based on publicly available information.

· Highlight any specific metrics or indicators they identify as potentially useful for prediction.

Part B: Data Analysis

· Choose a specific stock market index (e.g., S&P 500) and gather data for the past 10 years, this can be monthly, weekly, or daily data.

· Descriptive Analysis

· Calculate and visualize basic statistics, including mean, median, standard deviation, and other relevant metrics for your chosen index.

· Identify any patterns or anomalies that may suggest predictability or randomness in returns.

· Using the past returns, in the form. of basic time series models, or by using a basic predictive framework, assess whether returns are predictable (examples may include, (i) using ARMA models to assess predictability, (ii) using data from the Kenneth French Data library, look at whether industry portfolios lead stock markets as in Hong et al. (2007), (iii) downloading the macroeconomic predictors from Welch and Goyal (2008) and seeing if predictability exists), these are just some ideas, you may find your own.

· Implement appropriate statistical methods to determine if these indicators can reliably predict stock returns.

Part C: Critical Assessment

· Comparative Analysis

· Discuss the evidence you found for or against the predictability of stock returns.

· Relate your findings to the claims made by Fama and Lettau and Ludvigson. Where does your analysis agree or differ from theirs?

· Limitations

· Identify any limitations in your analysis, including potential biases, data limitations, or methodological constraints.

· Discuss any broader market factors or events (e.g., financial crises, significant policy changes) that might have influenced stock market returns during your study period.

Conclusion

· Based on your literature review and empirical analysis, conclude whether stock market returns for your chosen index are predictable using publicly available information.

· Offer recommendations or future research directions to further explore this debate.

Overall word limit: 3000

This assignment is worth 70% of the overall module mark.

SUBMISSION INSTRUCTIONS

Your completed assignment must be uploaded to Ultra
no later than 12:00 midday on 26 April 2024

The assignment should be submitting using one of the following file types: .doc, docx or .pdf

A penalty will be applied for work uploaded after 12:00 midday as detailed in the Student Information Hub.  You must leave sufficient time to fully complete the upload process before the deadline and check that you have received a receipt. At peak periods, it can take up to 30 minutes for a receipt to be generated.

Assignments should be typed, using 1.5 spacing and an easy-to-read 12-point font. Assignments and dissertations/business projects must not exceed the word count indicated in the module handbook/assessment brief.

 The word count should:

§ Include all the text, including title, preface, introduction, in-text citations, quotations, footnotes and any other items not specifically excluded below.

§ Exclude diagrams, tables (including tables/lists of contents and figures), equations, executive summary/abstract, acknowledgements, declaration, bibliography/list of references and appendices. However, it is not appropriate to use diagrams or tables merely as a way of circumventing the word limit. If a student uses a table or figure as a means of presenting his/her own words, then this is included in the word count.

Examiners will stop reading once the word limit has been reached, and work beyond this point will not be assessed. Checks of word counts will be carried out on submitted work, including any assignments or dissertations/business projects that appear to be clearly over-length. Checks may take place manually and/or with the aid of the word count provided via an electronic submission. Where a student has intentionally misrepresented their word count, the School may treat this as an offence under Section IV of the General Regulations of the University. Extreme cases may be viewed as dishonest practice under Section IV, 5 (a) (x) of the General Regulations.

Very occasionally it may be appropriate to present, in an appendix, material which does not properly belong in the main body of the assessment but which some students wish to provide for the sake of completeness. Any appendices will not have a role in the assessment - examiners are under no obligation to read appendices and they do not form. part of the word count. Material that students wish to be assessed should always be included in the main body of the text.

Guidance on referencing can be found on Durham University website and in the Student Information Hub.

MARKING GUIDELINES

Performance in the summative assessment for this module is judged against the following criteria:

· Relevance to question(s)

· Organisation, structure and presentation

· Depth of understanding

· Analysis and discussion

· Use of sources and referencing

· Overall conclusions