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Quantitative Methods

All Subjects>Computing and Mathematics> Quantitative Methods

C/C/74. How helpful is it to use computer based techniques for qualitative data analysis?

(2008, 2700 words)

The paper examines the usefulness of qualitative data analysis for academic research describing the stages of the research process, the basic research techniques, the areas of research strategy, etc. with reference to computer data mining (CDM). The benefits and problems associated with CDM are highlighted.

C/C/51. Quantitative Methods: Technical Analysis vs. Fundamental Analysis

(2008, 2000 words)

The paper examines the features of technical analysis (TA) as a quantitative method of investment selection providing definitions of TA, considering its difference from fundamental analysis, and discussing the assumptions of TA, the challenges and advantages of the method, and the trading rules and indicators used in TA.

C/F/306. Quantitative Methods

(2008, 1600 words)

The paper offers solutions to a set of exercises in investment evaluation related to quantitative methods. The methods of regression, linear programming and financial mathematics are used.

C/C/54. Quantitative Methods for Financial Services

(2008, 1200 words)

The paper presents the solutions to specific and defined questions on a computing course addressing three questions, i.e., the distribution of data sets, price indices and work on linear regression. References are not included due to the nature of the study.

C/C/19. MBA Quantitative Methods Assignment: Investigating the cross-sectional determinants of pay at Profserv

(2007, 2700 words)

This report is an investigation of the cross-sectional determinants of pay based on a fictitious data set. It outlines the development of the regression model in a series of stages. The starting point is a discussion of how to formulate an initial specification. This is followed by an analysis of the estimated results. The report then deals with the testing of the OLS assumptions and, in particular, the homoskedasticity assumption. This leads on to the implementation of a correction procedure, and the estimation of a transformed model. Further hypothesis tests (t-tests and F-tests) on the corrected model are then used to validate a final specification. All calculations are illustrated in Excel.

C/C/18. Introductory linear programming

(2007, 2400 words)

This report first motivates the basic principles behind linear programming. It then develops a fully worked example illustrating how to use the Simplex Method to solve a 3-D linear programming problem. Finally, it illustrates how to formulate and compute linear programming problems using Excel Solver. All calculations are attached

 

 

 
 

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