Financial Data Analysis

Financial Data AnalysisProject description
MSO3610 Financial Data Analysis Coursework 2 Individual Coursework Issued 13 May 2015 Coursework 2 is an individual coursework and carries 30% of the total assessment. It is expected that you will use Excel, SPSS or Minitab and Word (or other suitable word processing software) to do this coursework. The coursework should be handed in to the UniHelp desk in the Shepherds Library no later than 4.00pm on 19 June 2015. The coursework is based on the subject of Time Series (Units 18, 19 and 20) which are covered in Week 13, 14 and 15 Lectures. However you should also draw on previous work we have covered especially Correlation (Unit 16) and Regression (Unit 17) covered in Weeks 11 and 12 as well as other previous lectures
Coursework
Go to UniHub MSO3610. On the Coursework page you will find a file called Coursework Data. In this file you will find an Excel file titled corn. From this file you will need to extract the following data: US Yellow Corn Kcty U$/BSH US Yellow Corn Mpls U$/BSH From 1 Jan-2012 to 31 Dec 2012. This should give you 522 prices.
Using various methods we have covered in lectures and seminars carry out a thorough analysis of the first 250 prices of each of the two data sets by drawing appropriate graphs and carrying out appropriate calculations and statistical analysis. (15%)
Write a short summary (up to 300 words) explaining what you have done and your findings. Explain any difficulties you encountered and how you dealt with them. Important areas to consider is the relationship between the two data sets and which one you consider more appropriate to use for forecasting. (15%)
Using various forecasting methods we have covered in lectures (Trend, Moving Average, Single Exponential Smoothing, Double Exponential Smoothing and Winters Method) and possibly others make forecasts for the following 11 time points from the data set you considered most appropriate to use for forecasting. Compare these forecasts to the actual prices using appropriate error calculations. Be particularly aware of the two types of forecasts involved, short term and long term. (30%)
Write a summary (up to 700 words) explaining what you have done, your findings and any conclusions you have arrived at. Explain any difficulties you encountered and how you dealt with them. Extra interesting and relevant work will attract marks. (30%)
Well written and well presented work carries 10%
1. Each coursework should come with a cover sheet carrying the course name, module leaders name, students name, student number and students signature.
2. When handing in coursework keep a copy and obtain a receipt.
3. Handwritten work is not acceptable.
4. This coursework must be the work of the individual student and nobody else. Any work that is a copy of another student will be reported to the Middlesex University Registry. This could result in a degree failure for all students concerned.
Overview of Data
Prices quoted are spot closing prices per bushel in U.S.Dollars or U.S.Cents. The corn prices are from different regions and are sometimes traded on different exchanges. They are usually classified according to their origin such as South Central, Kentucky, Memphis etc. Bushels are now most often used as units of mass or weight rather than of volume. The bushels in which grains are bought and sold on commodity markets or at local grain elevators, and for reports of grain production, are all units of weight. This is done by assigning a standard weight to each commodity that is to be measured in bushels. These bushels depend on the commodities being measured and the moisture content. Some of the more common ones are:
? OATS USA 32lb = 14.5150kg ? OATS Canada 34lb = 15.4221kg ? BARLEY 48lb = 21.7724kg ? MALTED BARLEY 34lb = 15.4221kg ? SHELLED MAIZE [CORN] (15.5% Moisture) 56lb = 25.4012kg ? WHEAT (13.5% Moisture) 60lb = 27.2155kg ? SOYBEANS (13% Moisture) 60lb = 27.2155kg

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